Regulation of Transcription in Plants (Annual Plant Reviews, Volume 29)

Regulation of Transcription in Plants Edited by KLAUS D. GRASSER Department of Life Sciences Aalborg University Aalborg,...

Author: Klaus D. Grasser

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Regulation of Transcription in Plants Edited by KLAUS D. GRASSER Department of Life Sciences Aalborg University Aalborg, Denmark

Regulation of Transcription in Plants

Regulation of Transcription in Plants Edited by KLAUS D. GRASSER Department of Life Sciences Aalborg University Aalborg, Denmark

C

2006 by Blackwell Publishing Ltd

Editorial Ofﬁces: Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK Tel: +44 (0)1865 776868 Blackwell Publishing Professional, 2121 State Avenue, Ames, Iowa 50014-8300, USA Tel: +1 515 292 0140 Blackwell Publishing Asia Pty Ltd, 550 Swanston Street, Carlton, Victoria 3053, Australia Tel: +61 (0)3 8359 1011 The right of the Author to be identiﬁed as the Author of this Work has been asserted in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. First published 2006 by Blackwell Publishing Ltd ISBN-13: 978-14051-4528-2 ISBN-10: 1-4051-4528-5 Library of Congress Cataloging-in-Publication Data Grasser, Klaus (Klaus D.) Regulation of transcription in plants / Klaus Grasser. – 1st ed. p. cm. Includes bibliographical references and index. ISBN-13: 978-1-4051-4528-2 (hardback : alk. paper) ISBN-10: 1-4051-4528-5 (hardback : alk. paper) 1. plant genetic regulation. I. title. QK981.4G73 2006 572.8 845—dc22 2006012521 A catalogue record for this title is available from the British Library Set in 10/12 pt Times by TechBooks, New Delhi, India Printed and bound in Singapore by Markono Print Media Pte. Ltd The publisher’s policy is to use permanent paper from mills that operate a sustainable forestry policy, and which has been manufactured from pulp processed using acid-free and elementary chlorine-free practices. Furthermore, the publisher ensures that the text paper and cover board used have met acceptable environmental accreditation standards. For further information on Blackwell Publishing, visit our website: www.blackwellpublishing.com

Contents Contributors Preface 1

2

General transcription factors and the core promoter: ancient roots WILLIAM B. GURLEY, KEVIN O’GRADY, EVA CZARNECKA-VERNER and SHAI J. LAWIT 1.1 Introduction 1.2 Origins of the eukaryotic promoter 1.3 Organization of the eukaryotic promoter 1.3.1 TATA-less promoters 1.4 Transcription factor IID 1.5 Role of TFIID in development 1.6 Mediator 1.6.1 Tail module 1.6.2 Middle complex 1.6.3 Head module 1.6.4 CDK8/Srb8-11 module 1.6.5 Mediator subunits unique to metazoans and plants 1.7 Transcription factor IIB 1.8 Summary References Transcription factors of Arabidopsis and rice: a genomic perspective JOSE´ LUIS RIECHMANN 2.1 Introduction 2.2 Arabidopsis and rice genomes: the angiosperm complement of transcription factors 2.2.1 General considerations for genome-wide analyses 2.2.2 Arabidopsis transcription factors 2.2.3 Rice transcription factors: a comparison to Arabidopsis 2.2.4 Gene duplications, functional redundancy, and the transcription factor phenome 2.3 Plant promoters References

xiii xv

1

1 1 4 8 8 9 11 12 15 16 16 17 18 19 21

28 28 29 29 30 35 38 40 43

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4

CONTENTS

Chromatin-associated architectural HMGA and HMGB proteins assist transcription factor function KLAUS D. GRASSER and DORTE LAUNHOLT 3.1 Introduction 3.2 HMGA proteins 3.2.1 Structure and expression 3.2.2 DNA and chromatin interactions 3.3 HMGB proteins 3.3.1 Structure and expression 3.3.2 DNA and chromatin interactions 3.4 Dynamic interaction of histone H1 and HMG proteins with chromatin 3.5 HMGA and HMGB proteins as architectural assistant factors Acknowledgements References Histone modiﬁcations and transcription in plants YII LENG CHUA and JOHN C. GRAY 4.1 Introduction 4.2 Histone acetylation and transcriptional activation 4.2.1 Plant histone acetyltransferases 4.2.1.1 GNAT/MYST family 4.2.1.2 TAFII 250 family 4.2.1.3 P300/CBP family 4.2.2 Bromodomain proteins 4.2.2.1 Bromodomain extra-terminal proteins 4.2.2.2 Plant bromodomain proteins 4.2.3 Plant histone deacetylases 4.2.3.1 RPD3/HDA1 family 4.2.3.2 HD2 family 4.2.3.3 SIR2 family 4.2.4 Histone acetylation/deacetylation and environmental adaptation 4.3 Histone methylation 4.3.1 Plant SET-domain proteins 4.3.1.1 E(Z)- and Trithorax-type HMTases 4.3.1.2 Su(var)3-9-type HMTases 4.3.1.3 ASH1-type and plant-speciﬁc HMTases 4.3.2 Histone demethylase 4.4 Interplay between histone acetylation and methylation in transcriptional regulation 4.5 Conclusions References

54 54 55 55 57 59 59 64 66 67 72 72 79 79 83 85 86 87 87 88 89 90 90 90 92 92 93 93 95 96 97 99 99 100 102 103

CONTENTS

5

6

Chromatin remodeling and histone variants in transcriptional regulation and in maintaining DNA methylation J.C. REYES, J. BRZESKI and A. JERZMANOWSKI 5.1 Introduction 5.2 ATP-dependent chromatin remodeling 5.2.1 SWI/SNF-like complexes in plants 5.2.2 Other ATPases of the SNF2 family that control plant development 5.3 Chromatin remodeling and DNA methylation 5.3.1 The effects of ddm1 mutation differ from those caused by met1 5.3.2 The model of DDM1 action 5.3.3 DDM1 and methylation of histone H3 5.3.4 Models of DDM1 targeting 5.3.5 DRD1 – another SNF2 family protein involved in control of DNA methylation 5.4 Histone variants in the regulation of chromatin functions 5.4.1 Occurrence and functional role of core histone variants 5.4.2 Role of H1 histone in chromatin and signiﬁcance of nonallelic H1 variants References Matrix attachment regions and transcriptional gene silencing WILLIAM F. THOMPSON, STEVEN SPIKER and GEORGE C. ALLEN 6.1 Introduction 6.2 Costs and consequences of transgene expression variation 6.3 Position effects 6.4 Gene silencing 6.4.1 Post-transcriptional gene silencing 6.4.2 Transcriptional gene silencing 6.4.3 Repeats and rearrangement effects 6.5 Matrix attachment regions 6.6 MARs and transgene expression 6.6.1 MARs reduce gene silencing 6.6.2 MARs have a dual effect 6.6.3 Hypotheses to explain MAR effects 6.7 MAR effects in Arabidopsis 6.7.1 Testing the effect of developmental stage 6.7.2 How might MARs decrease net transgene expression? 6.7.3 MAR effects in PTGS mutants 6.8 Conclusions References

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112 112 113 115 119 120 121 121 123 124 124 125 125 128 130 136

136 137 137 138 138 139 140 140 142 142 148 149 151 152 152 153 153 153

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8

9

CONTENTS

Polymerase I transcription ´ ´ JULIO SAEZ-V ASQUEZ and MANUEL ECHEVERR´IA 7.1 Introduction 7.2 Organization of rRNA genes 7.3 Ribosomal RNA transcription and the nucleolus 7.4 rRNA gene promoters and transcription factors 7.5 RNA pol I holoenzymes: evidence and controversies 7.6 Coupling rDNA transcription and processing of pre-rRNA 7.7 Growth and hormonal control of RNA pol I transcription 7.8 Nucleolar dominance 7.9 Final remarks Acknowledgements References Transcription of plastid genes ¨ KARSTEN LIERE and THOMAS BORNER 8.1 Introduction 8.2 RNA polymerases 8.2.1 NEP: Nuclear-encoded RNA polymerase 8.2.2 PEP: Plastid-encoded RNA polymerase 8.3 Plastidial promoters 8.3.1 PEP promoters 8.3.2 NEP promoters 8.3.3 tRNAs with internal promoters 8.4 Regulation 8.4.1 Role of diverse and multiple promoters in developmental regulation of gene expression 8.4.2 Transcription factors for selective promoter recognition 8.4.2.1 Nuclear-encoded plastidial σ -factors 8.4.2.2 Role of σ -factor diversity in transcriptional regulation 8.4.2.3 NEP transcription factors 8.4.3 Effects of environmental factors and crosstalk between plastids and nucleus References Control of ﬂowering time STEVEN VAN NOCKER and MARIA JULISSA EK-RAMOS 9.1 Introduction 9.2 Regulation of FLC expression through the ‘autonomous pathway’ 9.3 Chromatin-related pleiotropic regulators of FLC 9.4 Vernalization-associated repression of FLC 9.5 Transcriptional repression of ﬂowering by FLC

162 162 162 163 166 169 171 172 173 176 176 177 184 184 185 187 188 189 189 190 192 192 193 196 196 198 203 204 209 225 225 225 229 232 235

CONTENTS

Transcriptional regulation in the photoperiodic induction of ﬂowering 9.7 Activation of SOC1 by CO 9.8 Chromatin-related mechanisms of photoperiod pathway regulation 9.9 Transcriptional activation of AP1 by FT and FD 9.10 Transcriptional mechanisms in the promotion of ﬂowering by GAs 9.11 PcG-mediated repression of ﬂoral homeotic genes 9.12 Summary and prospects Acknowledgements References

ix

9.6

10

11

12

Combinatorial control of ﬂoral organ identity by MADS-domain transcription factors ¨ GUNTER THEIßEN and RAINER MELZER 10.1 Introduction 10.2 ABC: early genetic models of ﬂoral organ identity 10.3 From the ABC to the ABCDE model 10.4 Elective afﬁnities of homeotic proteins: the ﬂoral quartet model 10.5 Beyond the ﬂoral quartets sensu stricto: multimeric complexes of other MIKC-type proteins 10.6 Outlook: the devil is always in the details – what we still don’t know about ﬂoral quartets 10.7 Summary Acknowledgements References Networks of transcriptional regulation underlying plant defense responses toward phytopathogens IMRE E. SOMSSICH 11.1 Introduction 11.2 Defense transcriptome 11.3 Regulatory sequences mediating defense gene expression 11.4 Transcription factors involved in defense gene regulation 11.5 Transcriptional networks 11.6 Defense gene suppression by pathogens 11.7 Summary and outlook Acknowledgements References Temperature-regulated gene expression ¨ FRIEDRICH SCHOFFL and TRESSA JACOB PANIKULANGARA 12.1 Heat stress

236 237 238 240 242 243 244 244 244

253 253 253 256 257 260 261 263 263 263

266 266 267 268 270 275 277 277 279 279 285 285

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12.1.1 Introduction 12.1.2 Heat stress sensing and signaling 12.1.3 Heat stress transcription factors: structure and function 12.1.4 Class A HSF: immediate early regulators of the heat-shock response 12.1.5 Second-level regulation 12.1.6 Heat stress target genes 12.1.7 Common stress-response genes and pathways 12.2 Cold stress 12.2.1 Introduction 12.2.2 Low-temperature sensing and signaling 12.2.3 Transcription factors in ABA-independent pathways 12.2.4 Transcription factors in ABA-dependent pathways 12.2.5 Cold stress target genes 12.3 Perspectives for plant biotechnology References 13

14

Applications of inducible transcription in plant research and biotechnology BRIAN TOMSETT, ANGELA TREGOVA and MARK CADDICK 13.1 Introduction 13.2 Conditional expression of transgenes 13.2.1 The principles of regulated expression 13.2.2 Generic mechanisms 13.2.3 Physical stimuli for activation 13.2.4 Chemical activators related to plant metabolism 13.2.5 Chemical activators unrelated to plant metabolism 13.2.6 The conditional expression tool kit and its further development 13.3 Applications to plant functional genomics 13.3.1 Conditional over-expression 13.3.2 Conditional knockout/knockdown 13.3.3 Conditional complementation 13.4 Potential applications to plant biotechnology 13.5 Conclusions References Modulation of transcriptional networks in crop plants TONG ZHU 14.1 Introduction 14.2 Genes, regulatory factors, regulatory pathways, regulatory nodes, and regulatory networks 14.3 Functional characterization of transcription factor genes 14.4 Reverse engineering of transcription regulatory network

285 285 286 288 289 290 291 292 292 292 296 298 298 300 302

309 309 309 310 310 312 314 316 319 320 321 321 322 322 324 324 329 329 330 331 333

CONTENTS

14.5 Transcription network in crop plants 14.6 Transcription factors as gene switches for genetic engineering 14.7 Perspectives References Index The colour plate section appears after Page 142

xi 337 339 340 342 347

Contributors Dr George C Allen Department of Crop Science and Horticultural Science, 1203 Partners II (ofﬁce), Campus Box 7550, North Carolina State University, Raleigh, NC 27695–7550, USA Dr J Brzeski Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5a, 02-106 Warsaw, Poland Professor Thomas B¨orner Institute of Biology/Genetics, Humboldt University Berlin, Chausseestraße 117, 10115 Berlin, Germany Dr Mark Caddick School of Biological Sciences, The University of Liverpool, Biosciences Building, Liverpool L69 7ZB, UK Dr Yii Leng Chua Hutchinson MRC Research Centre, Department of Pathology, University of Cambridge, Hills Road, Cambridge CB2 2XZ, UK Professor Eva Czarnecka-Verner Department of Microbiology and Cell Science, University of Florida, PO Box 110700, Gainesville, FL 32611-0700, USA Professor Manuel Echeverr´ıa Laboratoire G´enome et D´eveloppement des Plantes, UMR CNRS-IRD 5096, Universit´e de Perpignan, 52, Avenue de Villeneuve, 66860 Perpignan Cedex, France Dr Mar´ıa Julissa Ek-Ramos Departamento de Bioqu´ımica, Facultad de Qu´ımica, Universidad Nacional Aut´onoma de Mexico, Ciudad Universitaria, 04510 M´exico, DF, M´exico Professor Klaus D Grasser Department of Life Sciences, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark Professor John C Gray Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK Professor William B Gurley Department of Microbiology and Cell Science, University of Florida, PO Box 110700, Gainesville, FL 32611-0700, USA Professor A Jerzmanowski Laboratory of Plant Molecular Biology, Warsaw University, Pawinskiego 5a, 02-106 Warsaw, Poland Dr Dorte Launholt Department of Life Sciences, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark Dr Shai J Lawit Pioneer Hi-Bred International, Inc., a DuPont Company, 7300 NW 62nd Ave., PO Box 1004, Johnston, IA 50131–1004, USA Dr Karsten Liere Institute of Biology/Genetics, Humboldt University Berlin, Chausseestraße 117, 10115 Berlin, Germany Dr Rainer Melzer Lehrstuhl f¨ur Genetik, Friedrich-Schiller-Universit¨at Jena, Philosophenweg 12, D-07743 Jena, Germany Dr Kevin O’Grady Department of Microbiology and Cell Science, University of Florida, PO Box 110700, Gainesville, FL 32611-0700, USA

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CONTRIBUTORS

Dr Tressa Jacob Panikulangara ZMBP, Allgemeine Genetik, Universit¨at T¨ubingen, Auf der Morgenstelle 28, D-72076 Tuebingen, Germany Dr Jos´e C Reyes Instituto de Bioqu´ımica Vegetal y Fotos´ıntesis, Consejo Superior de Investigaciones Cient´ıﬁcas – Universidad de Sevilla, Av Am´erico Vespucio 49, 41092 Sevilla, Spain Dr Jos´e Luis Riechmann Division of Biology, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA Dr Julio S´aez-V´asquez Laboratoire G´enome et D´eveloppement des Plantes, UMR CNRS-IRD 5096, Universit´e de Perpignan, 52, Avenue de Villeneuve, 66860 Perpignan Cedex, France Professor Friedrich Sch¨ofﬂ ZMBP, Allgemeine Genetik, Universit¨at T¨ubingen, Auf der Morgenstelle 28, D-72076 Tuebingen, Germany Dr Imre E Somssich Department of Plant Microbe Interactions, Max-PlanckInstitute for Plant Breeding, Carl-von-Linn´e Weg 10, D-50829 Koeln, Germany Professor Steven Spiker Department of Genetics, North Carolina State University, Box 7614, Raleigh, NC 27607, USA Professor Gunter ¨ Theißen Lehrstuhl f¨ur Genetik, Friedrich-Schiller-Universit¨at Jena, Philosophenweg 12, D-07743 Jena, Germany Professor William F Thompson Departments of Plant Biology, Genetics, and Crop Science, Campus Box 7550, North Carolina State University, Raleigh, NC 27607, USA Professor Brian Tomsett School of Biological Sciences, The University of Liverpool, Biosciences Building, Liverpool L69 7ZB, UK Dr Angela Tregova School of Biological Sciences, The University of Liverpool, Biosciences Building, Liverpool L69 7ZB, UK Professor Steven van Nocker Department of Horticulture, 390 Plant and Soil Sciences Building, Michigan State University, East Lansing, MI 48824, USA Dr Tong Zhu Syngenta Biotechnology, Inc., 3054 Cornwallis Road, Research Triangle Park, NC 27709, USA

Preface The regulation of transcription is a central step in the control of gene expression in plants and it therefore plays an essential role in development and in the way plants cope with environmental inﬂuences. Through combinatorial control, a wide variety of transcription factors precisely determines the transcription level of target genes as well as their spatial and temporal expression pattern. It has emerged in recent years that the nuclear environment of the genome critically affects the regulated transcription of genes. Thus, genes are packaged into a complex nucleoprotein structure termed chromatin, generally repressing their transcription. At the same time the dynamic chromatin structure offers an opportunity for the regulation of gene expression mediated, for instance, by histone modiﬁers and chromatin-remodelling activities. In this volume, authors from leading laboratories have prepared chapters addressing the different mechanisms that cooperate in the regulation of transcription in plants, and links between transcriptional regulation and biotechnological applications have also been considered. The book begins with chapters describing the structure and function of transcription factors and assistant architectural proteins as well as their interplay with promoter regions (Chapters 1–3). These chapters provide insights into the protein– DNA and the protein–protein interactions that are crucial for the regulation of transcript initiation. Chapters 4 and 5 focus on the role of histone modiﬁcations, histone variants and chromatin remodelling, priming the chromatin for transcription. Various effects of DNA methylation on transcription are addressed in Chapters 5 and 7. Chapter 6 is devoted to matrix attachment regions and their connection to transcriptional gene silencing. In Chapters 7 and 8, the special features of transcription by RNA polymerase I and the transcription of plastid genes are described. In the following chapters some well-studied examples of transcriptional regulation in plants are explored. Chapter 9 deals with the transcriptional regulation of ﬂowering time, while Chapter 10 describes how ﬂoral organ identity is under the combinatorial control of MADS-domain transcription factors. Chapter 11 focuses on plant defense responses that are regulated by transcriptional networks. In Chapter 12, the temperature-regulated expression of genes upon heat- and cold-stress is described. The ﬁnal two chapters are dedicated to the discussion of some aspects related to applied plant biotechnology. Chapter 13 summarises the principles and applications of inducible transcription systems for research and biotechnology. In Chapter 14, the potential of engineering transcriptional networks in crop plants is discussed. Through the availability of genome sequences and ‘high-throughput’ approaches, the research in the ﬁeld of transcriptional regulation is currently moving in a new direction. This volume considers the ‘genomic perspectives’ as well as the

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PREFACE

thorough ‘case-by-case’ studies that have revealed many of the principles known about the regulation of transcription in plants. The book is intended to provide a guide into this exciting topic for researchers and teachers in the ﬁeld of plant biology. I would like to thank all the authors for their outstanding contributions, and the editorial staff of Blackwell Publishing for the pleasant collaboration on this project. Klaus D. Grasser

Annual Plant Reviews A series for researchers and postgraduates in the plant sciences. Each volume in this series focuses on a theme of topical importance and emphasis is placed on rapid publication. Editorial Board: Prof. Jeremy A. Roberts (Editor-in-Chief), Plant Science Division, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD, UK; Dr David Evans, School of Biological and Molecular Sciences, Oxford Brookes University, Headington, Oxford, OX3 0BP, UK; Prof. Hidemasa Imaseki, Obata-Minami 2419, Moriyama-ku, Nagoya 463, Japan; Dr Michael T. McManus, Institute of Molecular BioSciences, Massey University, Palmerston North, New Zealand; Dr Jocelyn K.C. Rose, Department of Plant Biology, Cornell University, Ithaca, New York 14853, USA. Titles in the series: 1. Arabidopsis Edited by M. Anderson and J.A. Roberts 2. Biochemistry of Plant Secondary Metabolism Edited by M. Wink 3. Functions of Plant Secondary Metabolites and their Exploitation in Biotechnology Edited by M. Wink 4. Molecular Plant Pathology Edited by M. Dickinson and J. Beynon 5. Vacuolar Compartments Edited by D.G. Robinson and J.C. Rogers 6. Plant Reproduction Edited by S.D. O’Neill and J.A. Roberts 7. Protein–Protein Interactions in Plant Biology Edited by M.T. McManus, W.A. Laing and A.C. Allan 8. The Plant Cell Wall Edited by J.K.C. Rose 9. The Golgi Apparatus and the Plant Secretory Pathway Edited by D.G. Robinson 10. The Plant Cytoskeleton in Cell Differentiation and Development Edited by P.J. Hussey 11. Plant–Pathogen Interactions Edited by N.J. Talbot 12. Polarity in Plants Edited by K. Lindsey 13. Plastids Edited by S.G. Moller 14. Plant Pigments and their Manipulation Edited by K.M. Davies 15. Membrane Transport in Plants Edited by M.R. Blatt 16. Intercellular Communication in Plants Edited by A.J. Fleming 17. Plant Architecture and its Manipulation Edited by C. Tuurnbull 18. Plasmodesmata Edited by K.J. Oparka 19. Plant Epigenetics Edited by P. Meyer

20. Flowering and Its Manipulation Edited by C. Ainsworth 21. Endogenous Plant Rhythms Edited by A. Hall and H. McWatters 22. Control of Primary Metabolism in Plants Edited by W.C. Plaxton and M.T. McManus 23. Biology of the Plant Cuticle Edited by M. Riederer 24. Plant Hormone Signaling Edited by P. Hadden and S.G. Thomas 25. Plant Cell Separation & Adhesion Edited by J.R. Roberts and Z. Gonzalez-Carranza 26. Senescence Processes in Plants Edited by S. Gan 27. Seed Development, Dormancy and Germination Edited by K.J. Bradford and H. Nonogaki 28. Plant Proteomics Edited by C. Finnie 29. Regulation of Transcription in Plants Edited by K. Grasser 30. Light and Plant Development Edited by G. Whitelam 31. Plant Mitochondria Edited by D. Logan

1 General transcription factors and the core promoter: ancient roots William B. Gurley, Kevin O’Grady, Eva Czarnecka-Verner and Shai J. Lawit

1.1

Introduction

Transcription is an ancient process that has its origins near the beginning of life on this planet, nearly 3.5 billion years ago. It is, therefore, no surprise that the basic components of the transcriptional apparatus and the underlying mechanisms of gene activation of modern organisms comprise a mixture of the very old interspersed with recent adaptation. Plants share a common heritage of transcriptional regulation with all Eukaryota. In this chapter, we examine the fundamentals of promoter structure and activated transcription, building on what is known from other eukaryotes and exploring the implications with respect to higher plants. Where information is available, we describe how plants have utilized and exploited the most basic components of the transcriptional machinery to meet their unique needs in the regulation of gene expression.

1.2

Origins of the eukaryotic promoter

Promoter regions of genes comprise the DNA sequences that are involved in regulating transcriptional activity. For eukaryotes, sequence elements (cis-elements) within the DNA of the promoter regulate transcriptional activity by determining the type, afﬁnities, and spatial arrangement of regulatory proteins (transcription factors) that nucleate on the DNA near the start site of transcription. For genes read by RNA polymerase II (pol II), most promoter elements are clustered upstream from the start site of transcription. There are two major classes of transcription factors that regulate RNA pol II: those common to the expression of most genes (general transcription factors (GTFs)), and those that regulate speciﬁc subsets of genes (transactivators). The GTFs bind in a complex with the DNA of the promoter to form a preinitiation complex (PIC) immediately upstream from the start site (+1 nt). The promoter can be thought of as a scaffold that regulates gene activity by specifying the type and physical arrangement of proteins that assemble for transcription. In eubacteria, promoter DNA often plays an additional role in affecting the rate of DNA melting, which, in turn, affects the kinetics of transcriptional initiation by RNA polymerase. However, this direct involvement in transcriptional regulation appears to be minimal in eukaryotes.

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REGULATION OF TRANSCRIPTION IN PLANTS

Traces of the archetypal eukaryotic promoter can be clearly seen in the conﬁguration of archaeal promoters (Figure 1.1). This is not surprising since the basal transcriptional apparatus of the eukaryotic nucleus is closely related to that found in this group of prokaryotic organisms, and current evolutionary theory suggests that the archaea contributed to the formation of the eukaryotic cell (Margulis et al., 2000). For example, the subunit composition of archaeal RNA polymerase is complex and very similar to that present in eukaryotes: both have the same 12 subunits versus the 4 present in eubacteria (Werner and Weinzierl, 2002). The major differences are that in archaea, the largest two subunits of the eukaryotic polymerase are present as two proteins (A , A and B , B ), and the two eukaryotic subunits, RBP8 and RBP9, are absent in archaeal enzyme. These common components of the transcriptional apparatus are reﬂected in shared features in promoter design between archaea and eukaryotes. The archaeal promoter contains several DNA elements that are components of modern eukaryotic promoters: an A/ T-rich TATA-like element centered 25–30 bp upstream from the start of transcription where TATA-binding protein (TBP) binds, and an element immediately upstream of the TATA that interacts speciﬁcally with TFB (equivalent to eukaryotic transcription factor IIB (TFIIB)) known as the TFB response element (BRE) (Geiduschek and Ouhammouch, 2005). As in eukaryotes, TFIIB makes contact with TBP within the C-terminal stirrup (Nikolov et al., 1995; Nikolov and Burley, 1997), thus ﬁxing the relative locations of the two promoter contact sites in the TBP–TFB protein complex. It is interesting that the TATA in archaea is most often in the inverted orientation (5 -TTATA-3 ) with respect to the BRE. TBP in both archaea and eukaryotes can bind to either orientation; hence, the polarity of transcription is determined by the relative location of the BRE with respect to the TATA (Cox et al., 1997; Bell et al., 1999), with the BRE always positioned upstream of the TATA in the promoter. As in the archaea, the eukaryotic promoter determines the direction of transcription by providing the transcriptional apparatus at least two points of contact with the template. In contrast to the usual perception of upstream cis-elements being ﬂexible in position, the location of these upstream activation sequences (UASs) in archaea is spatially constrained (Ouhammouch et al., 2005). The general strategy of inducing transcription by binding regulatory proteins upstream of the core promoter can be traced back to the eubacteria, where positive transcriptional regulators such as cyclic AMP-binding protein (CAP) bind to spatially constrained sites upstream of the core promoter elements at the –10 and –35 positions (Busby and Ebright, 1999). In the case of eubacteria, the transcription factor recruits RNA polymerase directly by making contacts with the α-subunit. The location of the bacterial UAS is critical to ensure the proper positioning of RNA polymerase at the start site. In archaea, it appears that at least some promoters initially recruit TBP (or perhaps TFB), which subsequently recruits RNA polymerase (Ouhammouch et al., 2005). As in eubacteria, this direct recruitment of a protein that makes speciﬁc contact with the DNA of the core promoter imposes strict spatial constraints on the placement of the UAS. The general strategies for promoter design evident in the eubacteria and

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

3

Figure 1.1 Schematic comparison of the archaeal and eukaryotic promoter structure. (A) The archaeal promoter shares two core elements with eukaryotic promoters, the binding sites for the general transcription factors TBP and TFB. Another similarity is the positioning of upstream activation sequences 5 and proximal to the BRE. (B) Eukaryotic promoters typically contain at least one of the core archaeal elements, and sometimes additional elements for binding subunits of TFIID (TAFs). Abbreviations: BRE, TFB response element; Inr, initiator region; DPE, downstream promoter element.

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REGULATION OF TRANSCRIPTION IN PLANTS

archaea are (1) the presence of an A/T-rich sequence upstream of the start site, (2) the placement of UASs upstream of the core promoter, and (3) the involvement of ciselements proximal to the core promoter to facilitate the precise positioning of RNA polymerase. Each of these features of promoter architecture has been conserved in eukaryotes, especially with respect to genes transcribed by RNA pol II.

1.3

Organization of the eukaryotic promoter

Typically, the eukaryotic promoter is more complex than the archaeal promoter in terms of the types of elements and their location. As seen in Figure 1.1B, there are certain features in common with the archaeal promoter regarding elements proximal to the start site of transcription (speciﬁcally the core promoter). For example, the TATA and sometimes the BRE are present, and their location is spatially constrained in a fashion reminiscent of that seen in archaea. Additional spatially constrained elements are sometimes seen in metazoan core promoters such as the initiator region (Inr) centered around +1, and the downstream promoter element (DPE), located in the 5 -untranslated region (UTR). In Drosophila four classes of core promoters are common: those containing TATA, TATA-Inr, Inr, and Inr-DPE (Smale and Kadonaga, 2003). The last two categories lack a TATA, but still initiate transcription with a precise start site and the correct polarity. However, TBP may still be recruited to these promoters via TBP-associated factors (TAFs), since both the Inr and DPE are recognized by speciﬁc groups of TAFs. TAFs 1 and 2 bind the Inr (Chalkley and Verrijzer, 1999), and TAFs 6 and 9 recognize the DPE (Burke and Kadonaga, 1997). The lack of Inr and DPE elements in archaea is consistent with the lack of TAFs in these organisms. Few, if any, eukaryotic promoters contain all of the possible sites of the core promoter. Since only two points of contact with the promoter are required to establish the polarity of transcription, only one to two elements are normally present in the core promoter. In those cases where there is only a single spatially constrained site, the determination of transcriptional polarity is more problematic and requires input from elements upstream of the core promoter. Although the second site of contact with the PIC is usually upstream of the core promoter, the spacing and orientation of this second element may be more ﬂexible. Transactivators are predicted to orient the PIC by making contacts with GTFs that do not directly bind DNA and are, thus, more adaptable with regard to alignment and spacing. Most eukaryotic cis-elements exhibit considerable ﬂexibility in orientation and spacing with respect to core promoter elements. There are, however, many examples of cis-elements that are located within 15–20 bp upstream of the TATA motif where direct contacts with TBP and TFIIB are possible. It is reasonable that these TATA-proximal elements may be involved in the precise alignment of the PIC by binding transactivators that make direct contact with either TBP or TFIIB. Although DNA looping may bring distal sites in close proximity with the core promoter (Blackwood and Kadonaga, 1998; Bulger and Groudine, 1999), the expectation is that transactivators bound to more distal cis-elements recruit (but do not precisely position) the PIC through contacts with proteins that do not directly

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

5

bind the core promoter. However, transactivators bound at TATA-proximal elements may participate in the direct recruitment of TBP and TFIIB, as is the case in the archaea. A close examination of one of the best analyzed promoters in eukaryotes, the Endo16 promoter from sea urchin (Yuh et al., 1998), will serve as an introduction of what we may expect in plants. The Endo16 gene encodes a polyfunctional secreted protein (Soltysik-Espanola et al., 1994) expressed in the primordial endoderm cells present in the midgut and late embryo and larval stages (Nocente-McGrath et al., 1989; Ransick et al., 1993). It is also speciﬁcally repressed in adjacent cell lineages. The full promoter includes the core promoter and 2300 bp of additional upstream sequences. Although 15 different proteins have been shown to bind speciﬁc ciselements within the upstream promoter, most have not been identiﬁed beyond their molecular weight and DNA-binding afﬁnities. The general term ‘cis-element’ is used here to distinguish between those sites that may activate, synergize, or repress transcription as opposed to those that are known simply to activate transcription (UASs). A detailed mutational analysis of the upstream regions of the promoter (Yuh et al., 1998) revealed an underlying structure in terms of function and spatial organization of the cis-elements (Figure 1.2). Elements in the Endo16 promoter are organized into seven clusters, or modules. The term ‘module’ is preferred here to ‘enhancer’, since modules can either activate or repress. Although enhancers are also composed of clusters of cis-elements, they are usually associated with the activation of genes. The upstream modules in the Endo16 promoter are responsible for the developmental timing of gene activation and repression, and in marking speciﬁc cells for expression (spatial expression). It is noteworthy that all activities of modules B–G (both positive and negative) either require a functional TATAproximal element (module A), or rely on this proximal module for their synergistic enhancement. In addition to integrating inputs from other modules, it also appears that module A functions as a two-position switch that either accepts or blocks

Figure 1.2 Modular organization of the upstream cis-elements in the eukaryotic promoter. The core promoter includes binding sites for the basal transcriptional apparatus (GTFs). In plants, where little evidence exists for core elements other than TATA and the Inr, the core promoter typically extends from −45 to a little beyond +1. In other eukaryotes the core promoter includes additional cis-elements such as the BRE, initiator, and the DPE. The upstream regulatory region includes all sequences upstream of the core promoter involved in regulating expression of the gene and often extends 1–2 kb upstream (proximal and distal promoters). Note that the upstream cis-elements are organized into clusters referred to as ‘modules’. A module may contain like elements or a variety of different types of elements. The TATAproximal module (module A above) may integrate inputs from other modules positioned upstream.

6

REGULATION OF TRANSCRIPTION IN PLANTS

input from the adjacent module B. An important lesson that can be taken from the functional organization of the Endo16 promoter is the dominant inﬂuence of the TATA-proximal module. This is logical since module A is best positioned to have direct input to the basal transcriptional apparatus – a theme that can be traced back to the archaeal and bacterial roots of all eukaryotic promoters. It is also worth noting that only one of the seven modules is involved in spatial expression; the rest are dedicated to operation of the logic system of the promoter. This logic system is involved in regulating the timing of activation, synergistic enhancement, and in repression. This should serve as a caveat for promoter studies that focus only on identiﬁcation of tissue-speciﬁc modules in plants and in other systems. How do plant promoters differ from the typical eukaryotic promoter? A compilation of plant core promoter elements is presented in Figure 1.3. The most obvious difference is the lack of evidence for core elements other than the TATA and Inr (sometimes called the ‘transcription start sequence motif’; TSS-motif) (Shahmuradov et al., 2003, 2005). This absence of additional core elements, however, does not imply that plant TFIIB and subunits of TFIID (TAFs) do not make contact with the core promoter, only that the contacts may not be base pair speciﬁc. Upstream cis-elements are not generally found closer to the TATA than about 15 bp, suggesting that TFIIB may occupy the intervening space by nonspeciﬁc general afﬁnity for the DNA instead of speciﬁcally recognizing the BRE consensus. Computer-based analysis of a large number of eukaryotic core promoters and 5 ﬂanking sequences has revealed an additional element, known as the ‘CCAAT box’, that has an optimal location immediately upstream of the core promoter (Benoist et al., 1980; Bucher, 1990; Mantovani, 1998). The CCAAT box is present in 25– 30% of eukaryotic promoters and is functional in both the forward and the reverse orientations. Its prevalence is slightly higher in TATA-less promoters, where it is often found in the reverse orientation. In some TATA-less promoters, it is closer to +1 and may even overlap the start site (Mantovani, 1998). The consensus in animals is 5 -CCA a/t t/a c/g a/g-3 , while in plants it simply reads ‘5 -CAAT3 ’ (Shahmuradov et al., 2003). In 71 unrelated plant promoters containing the CAAT box, this element was distributed between positions –46 and –106, with the average centered at −75 bp. The plant CAAT box was found to be present in 131 unrelated promoters: 71 in TATA-containing promoters and 60 in TATA-less promoters. Unexpectedly, recent ﬁndings indicate that from 40 to 50% of eukaryotic CCAAT boxes may also be found outside of the proximal promoter in introns or at far distant positions (both 5 and 3 ) (Testa et al., 2005). Nuclear factor Y (NF-Y) binds the CCAAT box and activates transcription in animals (Hooft van Huijsduijnen et al., 1987; Mantovani, 1999). NF-Y binds DNA as a trimer formed between the three subunits, NF-YA, NF-YB, and NF-YC (Sinha et al., 1995). Subunits NF-YB and NF-YC contain a conserved histone-fold domain involved in a tight interaction between these two subunits (Baxevanis et al., 1995). DNA binding requires all three subunits. Transcriptional activation in mammals is dependent on glutamine-rich (Q-rich) and serine–threonine-rich regions in the Cterminal domain (CTD) of NF-YB and a Q-rich domain in NFY-B (Coustry et al., 1995, 1996). Homologs to all three subunits have been cloned as multiple isoforms

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

7

General eukaryotic TATAAA GTATAAAAGGCGGGG C T TT TACGCCCC TATAAA from 171 plant promoters cTATAAATAcc TA General eukaryotic Inr TCAGTCTT G TTCTCC CA G TSS-motif (Inr) in 217 dicot promoters WnTCAw = +1 atcw TSS-motif (Inr) in 70 monocot promoters aNnCA TSS-motif (Inr) in 171 plant TATA promoters TCAnM c TSS-motif (Inr) in 130 plant TATA-less promoters TYAat a cca tg CCAAT box in general eukaryotes TCTAGCCAATCA ctcga tagg CCAAT box in 131 plant promoters nCAAT a cca Figure 1.3 Elements present in the core promoter of plants. This information is based on the results of Shahmuradov et al. (2003) obtained from computer analysis of a plant promoter database (PlantProm DB). The consensus sequences are represented in bold text, with the highest consensus positions capitalized. Alternate nucleotides are given below the preferred sequence. Abbreviations: W, A or T; N, any nucleotide; TATAAA, binding site for TBP usually located from −45 to −25 bp from the start of transcription; Inr, initiator region; recognition site for TAFs 1 and 2 which spans the transcription start site in yeast and metazoans; TSS, transcription start site – consensus of sequences that include and ﬂank the initiation site of plant genes. It is roughly equivalent to the Inr, but has been derived from homology comparisons instead of analyses of promoter function; CCAAT box, promoter element that is often located upstream and proximal to the core promoter in eukaryotes.

8

REGULATION OF TRANSCRIPTION IN PLANTS

(7 NF-YAs, 10 NF-Ybs, and 9 NF-YCs) from Arabidopsis (Gusmaroli et al., 2001, 2002). Of these, only ﬁve plant isoforms of NF-YC contain Q-rich domains. Consistent with the occurrence of CCAAT boxes in the proximal promoter (where direct contact with GTFs is facilitated) is the ﬁnding that NF-YB and NF-YC subunits show in vitro afﬁnity for TBP (Bellorini et al., 1997).

1.3.1

TATA-less promoters

In Drosophila almost half of the promoters contain a TATA motif spaced 25–30 bp upstream of the start site. Most of the remaining promoters contain either the Inr element, or Inr plus the DPE (Smale and Kadonaga, 2003). Whereas both the TATA and Inr can direct correct transcriptional initiation independently (Carcamo et al., 1991; Weis and Reinberg, 1997), the DPE must act in conjunction with the Inr (Burke and Kadonaga, 1996). In a study of 301 unrelated plant promoters, only 57% contained TATA, a percentage similar to that generally found in other eukaryotes (Shahmuradov et al., 2003). The average spacing between the plant TATA and the start of transcription was found to be 26 bp, very similar to other eukaryotes. Despite a lack of TATA consensus, TATA-less promoters can function with TBP. In vitro experiments indicate that in TATA-less promoters, activity was correlated with the %A/T nucleotides at the –30 position, suggesting that mammalian TBP shows some degree of recognition of even badly ﬂawed TATA-like sequences (Zenzie-Gregory et al., 1993). However, activity in assays containing mutated TBP indicated that DNA contact by TBP may not be an absolute requirement for transcription (Zenzie-Gregory et al., 1993).

1.4

Transcription factor IID

The GTF TFIID is a large multiprotein complex composed of TBP and additional subunits (usually 12–15) called TAFs (for reviews see Burley and Roeder, 1996; Verrijzer and Tjian, 1996; Lee and Young, 1998; Roeder, 1998; Tora, 2002). TFIID seems to be present in all groups of eukaryotic organisms and is thought to play a key role in promoter recognition and transcriptional activation of gene expression. TAFs have been shown to bind activators in vitro (Verrijzer and Tjian, 1996) and to play a critical role in metazoan development. TAFs are the targets of activator proteins, serving as bridges between the activator and TBP in the recruitment of TFIID to the promoter (Verrijzer and Tjian, 1996). Activation of speciﬁc genes in animals can be reduced by mutations in certain TAFs including TAF1, TAF6, and TAF4 (Sauer et al., 1996); moreover, certain TAF mutations are lethal in both mammals and yeast, especially those involved in the cell cycle (Reese et al., 1994; Poon et al., 1995; Verrijzer and Tjian, 1996). Work from Buratowski’s group has shown that four histone-like TAFs (TAFs 6, 9,11, and 12) are generally required for most transcription (Michel et al., 1998; Komarnitsky et al., 1999) in yeast. However, some exceptions are noted: TAF9-depleted cells still retain the capacity for Ace1 induction by copper, and the activation of heat-shock (HS) genes occurs in the

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

9

absence of a TFIID complex (Moqtaderi et al., 1998). The essential nature of TAF11 is signiﬁcant, since this TAF is found only in TFIID. Approximately 84% of yeast genes are dependent on one or more TAFs (Shen et al., 2003). Selective recruitment of TAFs by the upstream activator sequences of TAF-dependent promoters has been demonstrated in yeast, using chromatin immunoprecipitation (ChIP) assays (Li et al., 2002). This suggests that many TAFs, while not globally required for transcription, may play specialized roles in the regulation of subsets of genes. In plants, little information regarding the role of TAFs in transcription is available, except the in vitro studies of Washburn et al.(1997). In those experiments, activated transcription directed by the Herpes simplex VP16 acidic activator was dependent on the presence of TBP plus the TAFs – result closely in line with expectations from mammalian and yeast studies (Albright and Tjian, 2000; Sanders et al., 2002).

1.5

Role of TFIID in development

The degree to which TAFs participate in global gene activation is not resolved, but the evidence points to a strong bias toward involvement in developmental processes of multicellular organisms. Although TAFs are clearly not involved in all transcription, it does appear that certain TAFs and their alternate isoforms are critical components of cell-type-speciﬁc pathways of differentiation, while others ﬁll more general requirements in the progression of the cell cycle. For example, the two largest TAFs (1 and 2) are required in mammals for the G1/S and G2/M transitions of the cell cycle, respectively (Wang et al., 1997; Martin et al., 1999). Out of the 12–13 remaining TAFs, almost half have been shown to be involved in cellular differentiation. TAF4 and TAF4b are required for embryogenesis in ﬂies and mammals, as well as participate in gamete production (Metzger et al., 1999; Bell et al., 2001; Freiman et al., 2001; Guermah et al., 2003; Hiller et al., 2004). TAF4 is also required for activation of the master regulators Dorsal and Twister in Drosophila (Zhou et al., 1998; Pham et al., 1999) and is critical to neuronal cell differentiation of the embryonic brain and spinal cord in mice (Metsis et al., 2001). Although the subunits of TFIID play major roles in cellular differentiation and cell cycle in animals, it is unclear to what extent they play a similar role in plants. However, deep involvement in the processes of cellular differentiation is likely, since all of the alternative forms of TAFs that have specialized toward differentiation in other organisms are also present in Arabidopsis (Lago et al., 2004). It will be interesting to see how this potential for specialization manifests itself in plants where reproductive tissues and organs are derived from postembryonic meristems instead of being formed during embryogenesis, as is the case in metazoans. Experimentally induced alterations in levels of Arabidopsis TBP or speciﬁc TAFs show a wide range of phenotypes affecting the organization of vegetative meristems, leaf development, formation of ﬂoral organs and leaves, fertility, pollen tube growth, and light-mediated induction of speciﬁc genes. High levels of TBP-2 expression at the transcription level are seen in apical shoot tissues; whereas, overexpression

10

REGULATION OF TRANSCRIPTION IN PLANTS

of Arabidopsis TBP-2 in transgenic plants resulted in shoot proliferation, with supernumerary meristems forming in disorganized leaf primordia (Li et al., 2001). There are several lines of evidence consistent with the involvement of plant TAFs in developmental processes. TAF10 is a histone-fold protein that is a component of two major transcriptional complexes: TFIID and SAGA (Grant et al., 1998; Green, 2000). In animals, TAF10 shows a very restricted pattern of expression and is present only in speciﬁc cells during embryogenesis (Georgieva et al., 2000; Mohan et al., 2003). Although few similar studies have been reported in plants, there is limited evidence suggesting that plant TAF10 may also be specialized to regulate transcription with tissue speciﬁcity. In Flaveria trinervia (a composite of the Aster family), low levels of transcripts occur throughout the plant (Tamada et al., 2003). However, there are locations where TAF10 mRNA is abundant or at elevated levels: in the vascular tissues of hypocotyls, in the central stele of roots, and in bundle sheath cells of leaves (Furumoto et al., 2005). Overexpression of the F. trinervia TAF10 (ftTAF10) in Arabidopsis resulted in several abnormal phenotypes. One had limited growth of an indeterminate inﬂorescence, and the other developed dark green deformed leaves and chimeric ﬂoral organs similar to terminal ﬂower mutants (Shannon and Meeks-Wagner, 1991). TAF6 contains a histone fold and is present in animals in two forms, TAF6 and TAF6-L (TAF6-like). TAF6 is an integral part of TFIID, and TAF6-L has been shown in humans to be a component of the histone acetyltransferase (HAT)-containing PCAF (p300/CBP-associated factor) complex. In animals TAF6 is implicated in a variety of developmental events in germline and somatic cells (Aoyagi and Wassarman, 2001). Arabidopsis has two TAF6 genes (6 and 6b) that are distantly related (35% identity) (Lago et al., 2004). In plants heterozygous for a T-DNA insertion in TAF6, the only observed affect was a drastic reduction in pollen tube growth rates (Lago et al., 2005). These results not only conﬁrm the relatively recent ﬁnding that de novo RNA synthesis occurs in pollen tubes (Becker et al., 2003), but indicate that TAF6 plays an important role in pollen tube function. TAF1 is unique among the subunits of TFIID due to its polyfunctional enzymatic capabilities. In addition to promoter recognition at the Inr, it has the potential to acetylate, phosphorylate, and facilitate ubiquitylation of chromatin or PIC components. There are two paralogs of TAF1 in Arabidopsis, TAF1 and TAF1b. These are also known as HAP1 and HAP2, respectively, based on their classiﬁcation as proteins possessing HAT activity (Pandey et al., 2002). TAF1 has been shown in other organisms to possess two additional activities: a protein kinase activity and a ubiquitin activating and conjugating activity (Pham and Sauer, 2000). These enzymatic activities potentially enable TAF1 to modify chromatin and other transcription factors. All three of these domains are conserved in the Arabidopsis genes (Lago et al., 2004). In humans, two bromodomains are present at the C-terminus that synergistically facilitate binding to acetylated histone H4 (Jacobson et al., 2000). In Arabidopsis, there is only a single bromodomain. It is not known whether an additional bromodomain is furnished by an auxiliary protein, as is the case in yeast where both bromodomains are located on a separate protein (Bdf1). Plant TAF1 is unique among eukaryotes in having a ubiquitin domain (UbD) embedded within the coding region. The function of the UbD is unknown, but it raises the possibility that

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

11

it serves for the attachment of proteasome subunits, perhaps as a way to facilitate turnover of transactivators at the promoter. Another feature of TAF1 is the presence of an N-terminal domain (TAND-1) that mimics the structure of the double-strand TATA sequence of the promoter (Liu et al., 1998; Mal et al., 2004). TAND-1 of yeast and Drosophila TAF1 interacts with the concave DNA-binding surface of TBP and inhibits TBP binding to the TATA of the promoter (Bagby et al., 2000). The binding of TAND-1 to TBP may be conserved at the structural level, but is not easily identiﬁed in terms of amino acid sequence in plant TAF1 (Lago et al., 2004). This domain seems to be present in Arabidopsis TAF1, but is not evident in TAF1b from examination of amino acid sequence. HAP2 (TAF1b) is expressed at extremely low levels in most plant tissues, but is easier to detect in shoots and ﬂower buds (Bertrand et al., 2005). Microarray analysis of RNA from fourteen-day Arabidopsis shoots of the haf2 knockout mutant indicated that transcript levels from 854 genes from various functional categories were affected. However, it was not possible to distinguish between direct and secondary effects in this experiment (Bertrand et al., 2005). In addition, disruption of Arabidopsis HAF2 expression by T-DNA insertion interfered with the expression of several light-regulated genes, including CAB2 and RBCS-1A. ChIP analysis of these two promoters revealed that TAF1b may be involved in the acetylation of histone H3 in both genes, but only H4 acetylation at the RBSC-1A promoter. The fact that these perturbations in light-responsive signaling were speciﬁc to TAF1b mutations, and not TAF1, suggests that at least some degree of specialization has occurred between these plant paralogs of TAF1. The histone fold is present in 9 out of 14 TAFs of TFIID. These have the potential to form ﬁve heterodimer pairs, which are thought to make structural contributions to TFIID (Gangloff et al., 2001). Four TAFs may form a nucleosome-like structure composed of two heterodimers: TAF6 (H4)–TAF9 (H3) and TAF4 (H2A)–TAF12 (H2B). However, stoichiometric considerations and the TAF immunolocalization experiments of Leurent et al. (2004) suggest that the structure more resembles the archaeal tetramer versus the eukaryotic octomeric structure. In addition, six other TAFs may form three other heterodimers (TAF3–TAF10/10b, TAF8–TAF10/10b, and TAF11–TAF13). Immunolabeling experiments with yeast TAFs, combined with EM, have shown TFIID to possess a trilobed structure (Figure 1.4) (Leurent et al., 2004). Two copies of each histone-fold heterodimer are present that allow asymmetric assignment to each of the three lobes. Two copies of TAF5 seem to form a structural backbone for lobes A and B, with TAFs 1 and 7 and TBP associated with lobe A. Yeast two-hybrid studies using the Arabidopsis TAFs yielded an interaction matrix consistent with the yeast structure (Lawit, 2003), suggesting that TFIID has experienced overall structural conservation among eukaryotes.

1.6

Mediator

The mediator is a large complex (∼2 MDa) composed of 20–25 proteins that are required in vivo for basal transcription at the level of initiation and reinitiation.

12

REGULATION OF TRANSCRIPTION IN PLANTS

Figure 1.4 Map of TFIID subunits. The topology and assignment of subunit locations is based on the immunolabeling experiments of Leurent et al. (2004). The two copies of TAF5 serve important structural roles, as well as the two copies of histone-fold TAF heterodimers (4/12, 6/9, 8/10, and 11/13). TAF3 is absent here to reﬂect the lack of TAF3 identiﬁcation in plants to date.

Its critical role in basal transcription, as well as its involvement in activation and repression qualify it as a GTF (Takagi and Kornberg, 2005). Mediator does not directly bind DNA of the promoter, but instead acts as a coactivator, serving as a bridge between transactivators and RNA pol II. One of its roles in gene activation is thought to involve interactions with the of the largest subunit of RNA pol II (Myers et al., 1998; Naar et al., 2002; Nair et al., 2005). Since the role of mediator in activated transcription and its structure in both yeast and metazoans have recently been extensively reviewed elsewhere (Bjorklund and Gustafsson, 2005; Chadick and Asturias, 2005; Conaway et al., 2005; Kim and Lis, 2005; Kornberg, 2005; Malik and Roeder, 2005), in this section we concentrate on what is known of mediator in plants. A number of biochemical, genetic, protein interaction, and electron microscopy (EM) studies have determined that mediator is composed of three modules designated as ‘tail’, ‘head’, and ‘middle’ (Chadick and Asturias, 2005). In addition, there is a fourth module known as ‘CDK8/Srb8-11’ that is present in some mediator preparations. We have used the amino acid sequences provided in Boube et al. (2002) to identify the corresponding homologs in Arabidopsis using BLAST and reciprocal BLAST searches. Here we present a compiled sequence analysis of the data representing various mediator modules and identify Arabidopsis mediator subunits, including putative Arabidopsis homologs not found in yeast (Bourbon et al., 2004). We have used the model for modular subunit distribution compiled in Chadick and Asturias (2005) to organize the data (Tables 1.1–1.5).

1.6.1

Tail module

The tail module of mediator has been characterized as an integrator of transcription factor signals in yeast, and evidence suggests that it can function as a separate coactivator complex (Zhang et al., 2004). In yeast it is composed of ﬁve subunits (MED2, 3, and 14–16), three of which have corresponding orthologs in metazoans (MED14–16). In plants, only MED14 and 15 have been tentatively identiﬁed, one of which is linked to a mutant phenotype (SWP).

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER Table 1.1

13

Mediator tail subunits from humans, Drosophila, and Arabidopsis Tail

Saccharomyces cerevisiae MED2 (Med2) MED3 (Med3) MED14 (Rgr1) MED15 (Gal11) MED16 (Sin4)

Arabidopsis thaliana

Drosophila melanogaster

Homo sapiens

At3g04740 (SWP1) (B) At1g15780

TRAP170 Arc105 TRAP95

TRAP170-DRIP/CRSP150 ARC105 TRAP95-DRIP92

Note: The uniﬁed nomenclature proposed by Bourbon et al. (2004) is listed in the S. cerivisiae column along with the yeast homolog in parentheses. Genes identiﬁed in Boube et al. (2002) are followed with ‘(B)’. Arabidopsis genes are according to the Arabidopsis Genome Initiative (AGI) annotators and are the TAIR locus designation (http://www.Arabidopsis.org/).

The identiﬁcation of MED15 (a yeast Gal11 ortholog) is based on a single block of amino acid conservation. Novatchkova and Eisenhaber (2004) identiﬁed a KIX domain in the N-terminus of Drosophila ARC105, yeast Gal11, plant Gal11-like (At1g15780.1), and plant CREB-binding protein/p300 (CBP/p300) and postulate it to be the deﬁning feature of Gal11-like proteins. KIX is a protein–protein interaction domain with afﬁnity for the KID domain of CREB, as well with a number of other transcriptional activators (Campbell and Lumb, 2002; Liu et al., 2003; Zor et al., 2004). MED14 is a subunit that has been implicated as a regulator of both positive and negative gene expressions in yeast (Covitz et al., 1994; Jiang et al., 1995; Lee et al., 1999). It is broadly required for Caenorhabditis elegans embryonic transcription, Table 1.2

Mediator middle subunits from humans, Drosophila, and Arabidopsis Middle

Saccharomyces cerevisiae MED1 (Med1) MED4 (Med4) MED5 (Nut1) MED7 (Med7) MED9 (Cse2/Med9) MED10 (Nut2/Med10) MED21 (Srb7) MED31 (Soh1)

Arabidopsis thaliana

Drosophila melanogaster

Homo sapiens

At5g02850 (B)

Trap220 Trap36

TRAP220-ARC/DRIP205 TRAP36-ARC/DRIP36

Med7

ARC/DRIP34-CRSP33

CG5134 Nut2

Med25 hNut2-hMed10

Trap19 Trap18

HSrb7 hSoh1

At5g03220 (B) At5g03500 At5g41910 (B) At1g26665.1/.2a At4g04780 (B) At5g19910 (B)

Note: The uniﬁed nomenclature proposed by Bourbon et al. (2004) is listed in the S. cerivisiae column along with the yeast homolog in parentheses. Genes identiﬁed in Boube et al. (2002) are followed with ‘(B)’. Alternate splice variants are designated by ‘a’. Arabidopsis genes are according to the AGI annotators and are the TAIR locus designation (http://www.Arabidopsis.org/).

Table 1.3 Mediator head subunits from humans, Drosophila, and Arabidopsis Head Saccharomyces cerevisiae

Arabidopsis thaliana

Drosophila melanogaster

Homo sapiens

MED6 MED8 MED11 MED17 (Srb4) MED18 (Srb5) MED19 (Rox3) MED20 (Srb2)

At3g21350 (B)

Med6 ARC32 Med21 Trap80 P28/CG14802 CG5546 Trfp

HMed6-ARC/DRIP33 ARC32 HSPC296 TRAP80-ARC/DRIP77 p28b LCMR1 hTrfp

Med24

Surf5

MED22 (Srb6)

At5g20170 (B) At2g22370 (B) At4g09070 (B) At2G28230 At1g07950 (B) At1g16430

Note: The uniﬁed nomenclature proposed by Bourbon et al. (2004) is listed in the S. cerivisiae column along with the yeast homolog in parentheses. Genes identiﬁed in Boube et al. (2002) are followed with ‘(B)’. Arabidopsis genes are according to the AGI annotators and are the TAIR locus designation (http://www.Arabidopsis.org/).

Table 1.4 Mediator CDK8 subunits from humans, Drosophila, and Arabidopsis CDK8 Saccharomyces cerevisiae

Arabidopsis thaliana

Drosophila melanogaster

Homo sapiens

CDK8 (Srb10) CycC (Srb11) MED12 (Srb8) MED13 (Srb9)

At5g63610 At5g48640 At4g00450 (B) At1g55325 (B)

Dk8 CycC Kto Skd/Pap/Bli

CDK8 CycC TRAP230 ARC/DRIP240 TRAP240 ARC/DRIP250

Note: The CDK8 module is dissociable and thought to be involved in repression of gene expression. The uniﬁed nomenclature proposed by Bourbon et al. (2004) is listed in the S. cerivisiae column along with the yeast homolog in parentheses. Genes identiﬁed in Boube et al. (2002) are followed with ‘(B)’. Arabidopsis genes are according to the AGI annotators and are the TAIR locus designation (http://www.Arabidopsis.org/).

Table 1.5 Unique mediator subunits from humans, Drosophila, and Arabidopsis Unique

Arabidopsis thaliana

Drosophila melanogaster

Homo sapiens

MED23 MED24 MED25 MED26

At1g23230.1

TRAP150β TRAP100 Arc92 Arc70

hSUR2/CRSP130 TRAP/CRSP/DRIP100 ARC92 CRSP70-ARC70

Trap37 Med23 Intersex Trap25

TRAP37-CRSP34 Fksg20 Hintersex TRAP25

MED27 MED28 MED29 MED30

At1g25540.1 (PFT1) At3g48060.1 At3g48050.1/.2a At3g09180.1

Note: These subunits are not present in yeast and, therefore, have been designated as ‘unique’ (Bourbon et al., 2004). Alternate splice variants are designated by ‘a’. Arabidopsis genes are according to the AGI annotators and are the TAIR locus designation (http://www.Arabidopsis.org/).

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

15

as well as phosphorylation of the CTD of RNA pol II (Shim et al., 2002). Arabidopsis MED14 has strong homology to MED14 (yeast Rgr1) in other organisms (Autran et al., 2002). Mutations in Arabidopsis MED14 (yeast Rgr1) have drastic developmental consequences. Analysis of a set of mutants with abnormal cell division patterns and cell number identiﬁed a recessive mutation named ‘STRUWWELPETER’ (SWP) (Autran et al., 2002). SWP plants have reduced cell numbers in all aerial organs and exhibit abnormal meristem function. SWP seems to deﬁne the duration of the cell proliferation phase of leaf primordia, but not affect cell division rates. Other abnormalities in the shoot indicated that it is a highly pleiotropic mutation; however, there were no apparent abnormalities in root growth or development despite SWP expression in the root (Autran et al., 2002). As may be expected, a recessive epigenetic mutation in two step II splicing factors that seems to speciﬁcally effect the expression of SWP has a similar phenotype to SWP (Clay and Nelson, 2005).

1.6.2

Middle complex

The middle and head complexes of mediator have been implicated by structural EM studies to make direct contact with RNA pol II (Chadick and Asturias, 2005). The middle module has been shown in yeast to have afﬁnity for the CTD of the largest subunit of RNA pol II (Kang et al., 2001), participating in both activation and repression (Han et al., 2001; Kang et al., 2001). The middle complex is composed of two submodules designated MED9 (MED9, 1 and 4 subunits) and MED10 (MED10, 7 and 21) (Boube et al., 2002). These two submodules are thought to act in opposite ways: the MED9 subcomplex is involved in repression, while the MED10 subcomplex activates transcription (Han et al., 2001; Kang et al., 2001). Arabidopsis orthologs to components of the middle complex have been identiﬁed for ﬁve out of the eight subunits present in other eukaryotes. For MED7 and 10, there is more uncertainty regarding their identiﬁcation as bona ﬁde subunits of the plant mediator. The Arabidopsis MED7 (Boube et al., 2002) is nearly identical along its entire length to the N-terminus of the other listed Arabidopsis protein, At5g030500. This putative alternate form of MED7 has an RNA-binding domain (RBD) in its C-terminus with similarity to RBDs found in plant nucleolins (Bogre et al., 1996). The two listed Arabidopsis MED10 (Nut2) candidates show comparable amino acid sequence similarity to MED10 present in other eukaryotes. The involvement of MED10 in GCN4-mediated transcription in yeast raises the possibility that the MED10 submodule may play a wider role in transcriptional activation (Han et al., 1999). Less is known concerning the roles of the other members of the MED10 submodule in speciﬁc gene regulation. The MED21 (Srb7) Arabidopsis homolog is larger than MED10 and is similar to metazoan SRB7 at its C-terminus. In addition, it contains a GRF zinc-ﬁnger domain at its N-terminus. This presumed zinc-binding domain is found in a variety of DNA-binding proteins and may be involved in nucleic acid binding. MED31 (Soh1), long recognized as a component of human and Drosophila mediator, was recently identiﬁed as a genuine mediator subunit in yeast (Linder and Gustafsson, 2004). Like many of the mediator subunits, only a relatively

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REGULATION OF TRANSCRIPTION IN PLANTS

small domain of the protein has been conserved across evolutionary distance: a 69-amino acid region that is rich in leucine and aromatic residues (Linder and Gustafsson, 2004). This conserved motif appears to be a protein interaction domain required for the association of MED31 with the rest of the mediator complex.

1.6.3

Head module

The head module (Srb4 module) plays a major role in binding RNA pol II. Early genetic studies strongly suggested the possibility of interactions between the CTD of RNA pol II and the Srb proteins, many of which reside in the head module (Thompson et al., 1993). In vitro studies later demonstrated direct binding of the Srb4, MED9, and MED10 modules to the CTD of pol II (Kang et al., 2001). EM imaging of highly puriﬁed yeast RNA pol II–mediator complexes suggests that multiple contacts between the head module and polymerase are likely (Asturias et al., 1999). It is unknown whether these contacts serve a strictly structural purpose, or if mediator may impart functionally signiﬁcant conformational change to the polymerase. Although attachment of mediator to RNA pol II is a major function of the head module, it also serves as a target for recruitment by the acidic activation domain of the yeast Gal4 transactivator (Koh et al., 1998). Based on experiments in yeast, the MED17 (Srb4) subunit appears to exert global effects on transcription. For example, the nearly absolute requirement of MED17 was demonstrated by the observation that a temperature-sensitive mutation (srb4ts) was as detrimental to overall transcription as a mutation in RNA pol II itself (Holstege et al., 1998). Two head module subunits, MED20 and MED22, may have multiple isoforms in plants. The MED20 (Srb2) Arabidopsis homolog (encoded by At4g09070) does not have signiﬁcant similarity to yeast MED20, but is clearly related to human and Drosophila homologs. In addition, we identiﬁed another MED20 gene in Arabidopsis, At2G28230, that does show signiﬁcant similarity to both human and Drosophila genes and is highly similar to At4g09070. The third putative MED20 gene, At2g28020.1, shows a high degree of similarity that is restricted to the C-termini of the other two Arabidopsis paralogs. Interestingly, some head module genes are not found in Arabidopsis (such as MED8 and MED19), or have been assigned to the mediator by others (Boube et al., 2002), but are not conﬁrmed by our analyses (i.e., MED11). The MED6 homolog in Arabidopsis shows strong similarity to the metazoan subunit. Mutants of MED6 in Drosophila exhibit severe developmental abnormalities, and the expression of many, but not all, developmentallyregulated genes are affected (Gim et al., 2001).

1.6.4

CDK8/Srb8-11 module

The fourth mediator module, CDK8/Srb8-11, appears to be reversibly bound and has been closely linked to transcriptional repression, both in yeast (Kuchin and Carlson, 1998; van de Peppel et al., 2005) and in metazoans (Mo et al., 2004; Yoda et al., 2005). This module, containing a kinase that phoshorylates the CTD of RNA pol II, may repress transcription by inhibiting the association between mediator and the

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

17

CTD. Mediator containing the Srb8-11 module from Shizosaccharomyces pombe can be isolated only in free form, not complexed with RNA pol II (Samuelsen et al., 2003). This is also the case in mammalian systems where the larger form of mediator, ARC-L, is unable to bind the CTD of RNA pol II, unlike CRSP, the smaller transcriptionally active form, which can (Naar et al., 2002). Genes encoding all subunits of the CDK8 module have been putatively identiﬁed in Arabidopsis and are listed below in Table 1.4.

1.6.5

Mediator subunits unique to metazoans and plants

A number of mediator subunits have been identiﬁed in metazoans that are not found in yeast (Bourbon et al., 2004) and, hence, could not be assigned to a speciﬁc module. We conducted reciprocal Psi blast searches (Altschul et al., 1997) of the A. thaliana database using human and Drosophila homologs to identify putative homologs of these subunits in Arabidopsis listed in the following table. It is interesting that several of these subunits have afﬁnity for transactivators. For example, MED23 interacts with a number of transcription factors including C/EBPβ where it mediates C/EBPβ interaction with both transcriptionally active and inactive mediator complexes (Mo et al., 2004). Note that MED23 is the new designation of the Sur2/CRSP130 subunit originally misidentiﬁed as the homolog of Gal11 (Boube et al., 2002). Mediator in metazoans seems to be present in two distinct forms: one involved in gene activation and one associated with repression. The repressor form of mediator (ARC-L) is larger in mass than the activation-type mediator exempliﬁed by CRSP, which was ﬁrst characterized as a coactivator complex required for Sp1 activation (Ryu et al., 1999). Repressor-type mediators contain the CDK8 module and lack MED26. In contrast, activation-type mediators (i.e., CRSP) lack the CDK8 module, but contain the MED26 subunit. Therefore, MED26 is thought to be essential for the activation function. MED26 in metazoans and in Arabidopsis (At3g48060 and At3g48050.1/2) contains an N-terminal domain (Domain I) that forms a four-helix cluster that is also found in transcription elongation factor SII (TFIIS) and in elongin A (Booth et al., 2000). Both Arabidopsis homologs contain an additional domain, BAH/ELM1/BAM (bromoadjacent homology or motif), that may be a protein– protein interaction domain and is present in a number of proteins involved in gene transcription and repression (Goodwin and Nicolas, 2001). The Arabidopsis MED26 homologs appear to represent a gene duplication, one of which (At3g48050.1/2) has a splice variant. MED25 is a member of the ARC mediator complex and has been identiﬁed as the target subunit of the VP16 transactivation domain (Mittler et al., 2003; Yang et al., 2004). In Arabidopsis, MED25 (At1g25540) encodes the nuclear protein PFT1, which is involved in the regulation of ﬂowering time downstream of phyB in a photoperiod-independent manner (Cerdan and Chory, 2003). PFT1 also modulates the expression of the ﬂoral integrator gene FT, consistent with its role as a mediator subunit. Metazoan MED25 interactions with the mediator complex are mediated through a von Willebrand type A domain (vWF-A), shown to be involved in protein– protein interactions (Hinshelwood et al., 1999; Mittler et al., 2003 ). Arabidopsis

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REGULATION OF TRANSCRIPTION IN PLANTS

PFT1 also has this interaction domain, as well as a glutamine-rich region similar to the one present in Drosophila MED25. Overall, plant mediator appears to share a subunit composition similar to that characteristic of metazoans. This is based on the ﬁnding that four out of the eight subunits present in metazoans, but not in yeast, have putative orthologs in Arabidopsis. It will be interesting to see if the ‘missing’ metazoan subunits are actually present in plants (as highly diverged forms), lack additional subunits altogether, or whether plants possess truly unique mediator subunits.

1.7

Transcription factor IIB

Transcription factor IIB is a key member of the PIC from archaea through higher eukaryotes. The highly conserved C-terminal half of TFIIB (TFIIB core) is composed of two imperfectly repeated domains (R1 and R2) that show similarity to cyclin. When in the PIC with TBP, TFIIB makes contact upstream of the TATA in the major groove of the BRE and downstream of TATA in the minor groove (Nikolov et al., 1995; Lagrange et al., 1998; Tsai and Sigler, 2000). The N-terminus of TFIIB contains two highly conserved domains of approximately 30 residues each: the zinc ribbon and B-ﬁnger. These N-terminal domains protrude into the cleft of RNA pol II that forms the active site, and the TFIIB core makes contact with the C-terminal stirrup of TBP in the region between the two cyclin folds. The zinc ribbon binds to the dock region of pol II (Rbp1 subunit) and overlaps the RNA exit channel, and the adjacent B-ﬁnger forms a loop structure that ﬁlls the space between the RNA exit channel and the catalytic site of the enzyme. The B-ﬁnger is positioned in close proximity to the 8-bp RNA–DNA hybrid within the transcription bubble and is thought to play a role in start-site selection (Bushnell et al., 2004; Chen and Hahn, 2004). The B-ﬁnger and TFIIB core domains are also in close contact with TFIIF on the surface of pol II and within the active site (Freire-Picos et al., 2005). These intimate associations between TBP, TFIIB, and RNA polymerase seem to be conserved from archaea to higher eukaryotes, including plants. There are two families of TFIIB type proteins: TFIIB which is associated with RNA pol II transcription, and those associated with RNA pol III transcription known as B-related factors (BRFs). There are at least three of BRF genes in Arabidopsis: At2g45100, At3g09360, and At2g01280. Although TFIIB has specialized to function with RNA polymerases II and III, a single type of TBP functions with all three eukaryotic RNA polymerases. Plants are unusual in that they have multiple TFIIBs compared to the single proteins in metazoans and yeast. For example, in Arabidopsis there are ﬁve general classes of TFIIB based on phylogenetic analysis of the R2 core domain (Lawit, 2003). There appears to be a group of closely related TFIIBs found in all plants that we designate as Type I. This group is presumed to represent the main TFIIB based on the observation that it is, by far, the most highly conserved among plants and, therefore, is most likely involved in expression of a largest percentage of the genes. Mutational changes in the Type I TFIIBs are expected to be very constrained due to the wide-ranging affects mutations would impose on all aspects of

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

19

growth and development. At present, Type I TFIIB genes include two from Arabidopsis (At3g10330 and At2g41630), two from poplar (B3 and B1), and one each from grape (TC19782), soybean (U 31097), alfalfa (TC86832), citrus (CB292941), rice (AF464908), and wheat (TC68795). Plants also have several other more highly diverged TFIIB genes, which we designate as Type II. There are four Type II TFIIB genes in rice (PO430F03.39, AC136492, AAN59779, and PO430F03.36) and two in Arabidopsis (At3g57370 and At3g29380). From the limited amount of DNA sequence data available in plants, it seems that the number of Type I genes may normally be one to two, while the number of Type II genes may be more variable between plant species (four in rice; two in Arabidopsis) (Lawit, 2003). Plants also contain a very unusual class of TFIIB known as pBrp (TFIIB5; Type III) that is associated with the plastid (Lagrange et al., 2003). Phylogenetic analysis of the R2 domain suggests that this protein is quite ancient, having a branch point near those of yeast TFIIB and archaeal TFB (Lagrange et al., 2003; Lawit, 2003). Studies in Arabidopsis revealed that pBrp is predominantly located on the outer surface of the plastid envelop (Lagrange et al., 2003). In addition, pBrp contains PEST-related sequences in the linker domain of the N-terminus and at the C-terminus beyond the TFIIB core region. The PEST motif targets proteins for rapid turnover by the proteasomes. Inhibition of proteasome function by chemical treatments, or by utilizing mutants in COP9, resulted in the accumulation of pBrp in the nucleus. Lagrange et al. (2003) have suggested from these results that pBrp is controlled by nucleocytoplasmic partitioning which is dependent on proteasome degradation by an unknown process. The close association with the plastid cyosolic face supports the possibility that pBrp may be uniquely involved in the expression of nuclear-encoded plastid genes. The existence of three types of TFIIB, and the existence of multiple paralogs within these types, strongly implies that TFIIB has undergone a much higher degree of specialization in plants compared to metazoans and yeast. It will be interesting to test this hypothesis in the future and determine the parameters of promoter recognition that may have been exploited in the process. For example, is there a pBrp-speciﬁc BRE, and are there other GTFs or transactivators that speciﬁcally function in association with pBrp? Along these lines, perhaps pBrp functions with a novel form of RNA pol II. This is not as speculative as it may seem in view of the degree of divergence between pBrp proteins and other TFIIBs present in the pBrp zinc ribbon and the low level of similarity with the canonical B-ﬁnger at the amino acid level (Lawit, 2003). This possibility is strengthened by the presence of a novel RNA pol II Rbp2 subunit in Arabidopsis (Nature, 2000).

1.8

Summary

Higher plants have much in common with metazoans and yeast with respect to gene and promoter structure and with respect to the composition of the basal transcriptional apparatus. The core promoter in plants contains the TATA and Inr elements, but appears to lack other motifs such as the DPE and BRE. In addition, the TATAproximal CAAT box and its cognate transactivator (NF-Y) ﬁrst characterized in

20

REGULATION OF TRANSCRIPTION IN PLANTS

mammals is also present in plants. It is expected that in plants, as in other eukaryotes, upstream elements are often distributed in module-like clusters and TATA-proximal modules exert a dominant inﬂuence on transcription. These common features of promoter structure are consistent with the assumption that the fundamental mechanisms of gene activation and repression have been conserved among the eukaryotes. A survey of completed plant genomes reveals that genes encoding subunits for the typical assemblage of GTFs (TFIIA, B, D, E, F, and H) are present. While most metazoans and the fungi usually possess a single gene encoding the GTFs and their respective subunits, plants are able to accommodate limited amounts of gene duplication and specialization. For example, the Arabidopsis genome contains two copies of TBP, and TAFs 1, 4, 6, 11, and 12. Of these, the additional copy of TAFs 6, 11, and 12 seems to be derived from the ancient genome duplication that doubled approximately 70% of the Arabidopsis genome (Nature, 2000; Lago et al., 2004). However, an even more ancient event is responsible for the duplication of TAFs 1 and 4, since these are present in two copies in monocots, metazoans, and yeast, and are not located in the regions of the genome that were duplicated in Arabidopsis (Lago et al., 2004). This ability of plants to tolerate, and possibly exploit, multiple alleles of GTFs is best illustrated with TFIIB, where widely divergent forms exist, and one (pBrp) is plastid associated (Lagrange et al., 2003). At present the biological signiﬁcance of having multiple genes encoding a GTF is unknown; however, the expectation is that several have specialized for cell-type or developmentally speciﬁc roles. Many of the redundant GTFs in plants are not universal in distribution. For example, TAFs 6, 11, and 12, which are duplicated in Arabidopsis, are present only as single alleles in rice (Lago et al., 2004). This raises several possibilities: that ancient duplications of the plant GTFs may not be maintained through evolution, or that the duplication of plant GTFs is an ongoing process that may lead to the development of novel patterns of expression. Even though the underlying mechanisms of promoter structure and gene regulation can be traced back to the pre-eukaryotic period and are shared by all eukaryotes, much remains to be discovered regarding plant-speciﬁc mechanisms by which GTFs regulate gene expression. The technical difﬁculties inherent to in vitro transcription with plant systems have been a barrier for biochemical characterization of the complex machinery of transcription. However, the rapid accumulation of whole genome sequence information for a growing number of organisms has greatly facilitated the identiﬁcation of genes encoding the major components of basal transcription in plants based on the conservation of functional domains among the eukaryotes. In some cases, orthologous genes corresponding to GTFs and their subunits can clearly be identiﬁed in plants; however, some subunits are more conserved in structure than in amino acid sequence. In these instances (some TAFs and mediator subunits), only small blocks (20–30 amino acids) of similarity in coding sequence can be recognized, and these domains are often also present in multiple proteins not associated with transcription. A future challenge is to immunopurify the multisubunit GTFs found in plants using epitope-tagged proteins introduced into transformed plants in order to conﬁrm predictions in subunit composition and, possibly, discover novel plant-speciﬁc subunits. A strategy employing targeted mutagenesis of speciﬁc GTF subunits may ultimately provide information that will enable us to better understand

GENERAL TRANSCRIPTION FACTORS AND THE CORE PROMOTER

21

how plants as multicellular organisms have exploited the ancient mechanisms of transcription in their unique exploration of a sessile, land-adapted lifestyle.

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B. Michel, P. Komarnitsky and S. Buratowski (1998) Histone-like TAFs are essential for transcription in vivo. Molecular Cell 2, 663–673. G. Mittler, T. Stuhler, L. Santolin, et al. (2003) A novel docking site on Mediator is critical for activation by VP16 in mammalian cells. The EMBO Journal 22, 6494–6504. X. Mo, E. Kowenz-Leutz, H. Xu and A. Leutz (2004) Ras induces mediator complex exchange on C/EBP beta. Molecular Cell 13, 241–250. W.S. Mohan, Jr., E. Scheer, O. Wendling, D. Metzger and L. Tora (2003) TAF10 (TAF(II)30) is necessary for TFIID stability and early embryogenesis in mice. Molecular and Cellular Biology 23, 4307–4318. Z. Moqtaderi, M. Keaveney and K. Struhl (1998) The histone H3-like TAF is broadly required for transcription in yeast. Molecular Cell 2, 675–682. L.C. Myers, C.M. Gustafsson, D.A. Bushnell, et al. (1998) The med proteins of yeast and their function through the RNA polymerase II carboxy-terminal domain. Genes and Development 12, 45–54. A.M. Naar, D.J. Taatjes, W. Zhai, E. Nogales and R. Tjian (2002) Human CRSP interacts with RNA polymerase II CTD and adopts a speciﬁc CTD-bound conformation. Genes and Development 16, 1339–1344. D. Nair, Y. Kim and L.C. Myers (2005) Mediator and TFIIH govern carboxyl-terminal domaindependent transcription in yeast extracts. The Journal of Biological Chemistry 280, 33739–33748. The Arabidopsis Initiative (2000) Analysis of the genome sequence of the ﬂowering plant Arabidopsis thaliana. Nature 408, 796–815. D.B. Nikolov and S.K. Burley (1997) RNA polymerase II transcription initiation: a structural view. Proceedings of the National Academy of Sciences of the United States of America 94, 15–22. D.B. Nikolov, H. Chen, E.D. Halay, et al. (1995) Crystal structure of a TFIIB–TBP–TATA-element ternary complex. Nature 377, 119–128. C. Nocente-McGrath, C.A. Brenner and S.G. Ernst (1989) Endo16, a lineage-speciﬁc protein of the sea urchin embryo, is ﬁrst expressed just prior to gastrulation. Developmental Biology 136, 264–272. M. Novatchkova and F. Eisenhaber (2004) Linking transcriptional mediators via the GACKIX domain super family. Current Biology 14, R54–R55. M. Ouhammouch, G.E. Langham, W. Hausner, et al. (2005) Promoter architecture and response to a positive regulator of archaeal transcription. Molecular Microbiology 56, 625–637. R. Pandey, A. Muller, C.A. Napoli, et al. (2002) Analysis of histone acetyltransferase and histone deacetylase families of Arabidopsis thaliana suggests functional diversiﬁcation of chromatin modiﬁcation among multicellular eukaryotes. Nucleic Acids Research 30, 5036–5055. A.D. Pham, S. Muller and F. Sauer (1999) Mesoderm-determining transcription in Drosophila is alleviated by mutations in TAF(II)60 and TAF(II)110. Mechanisms of Development 84, 3–16. A.D. Pham and F. Sauer (2000) Ubiquitin-activating/conjugating activity of TAFII250, a mediator of activation of gene expression in Drosophila. Science 289, 2357–2360. D. Poon, Y. Bai, A.M. Campbell, et al. (1995) Identiﬁcation and characterization of a TFIID-like multiprotein complex from Saccharomyces cerevisiae. Proceedings of the National Academy of Sciences of the United States of America 92, 8224–8228. A. Ransick, S. Ernst, R.J. Britten and E.H. Davidson (1993) Whole mount in situ hybridization shows Endo 16 to be a marker for the vegetal plate territory in sea urchin embryos. Mechanisms of Development 42, 117–124. J.C. Reese, L. Apone, S.S. Walker, L.A. Grifﬁn and M.R. Green (1994) Yeast TAFIIS in a multisubunit complex required for activated transcription. Nature 371, 523–527. R.G. Roeder (1998) Role of general and gene-speciﬁc cofactors in the regulation of eukaryotic transcription. In: Mechanisms of Transcription, Cold Spring Harbor Symposia on Quantitative Biology, p. 679. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY. S. Ryu, S. Zhou, A.G. Ladurner and R. Tjian (1999) The transcriptional cofactor complex CRSP is required for activity of the enhancer-binding protein Sp1. Nature 397, 446–450. C.O. Samuelsen, V. Baraznenok, O. Khorosjutina, et al. (2003) TRAP230/ARC240 and TRAP240/ARC250 mediator subunits are functionally conserved through evolution. Proceedings of the National Academy of Sciences of the United States of America 100, 6422–6427.

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S.L. Sanders, K.A. Garbett and P.A. Weil (2002) Molecular characterization of Saccharomyces cerevisiae TFIID. Molecular and Cellular Biology 22, 6000–6013. F. Sauer, D.A. Wassarman, G.M. Rubin and R. Tjian (1996) TAF(II)s mediate activation of transcription in the Drosophila embryo. Cell 87, 1271–1284. I.A. Shahmuradov, A.J. Gammerman, J.M. Hancock, P.M. Bramley and V.V. Solovyev (2003) PlantProm: a database of plant promoter sequences. Nucleic Acids Research 31, 114–117. I.A. Shahmuradov, V.V. Solovyev and A.J. Gammerman (2005) Plant promoter prediction with conﬁdence estimation. Nucleic Acids Research 33, 1069–1076. S. Shannon and D.R. Meeks-Wagner (1991) A mutation in the Arabidopsis TFL1 gene affects inﬂorescence meristem development. Plant Cell 3, 877–892. W.C. Shen, S.R. Bhaumik, H.C. Causton, et al. (2003) Systematic analysis of essential yeast TAFs in genome-wide transcription and preinitiation complex assembly. The EMBO Journal 22, 3395– 3402. E.Y. Shim, A.K. Walker and T.K. Blackwell (2002) Broad requirement for the mediator subunit RGR1 for transcription in the Caenorhabditis elegans embryo. The Journal of Biological Chemistry 277, 30413–30416. S. Sinha, S.N. Maity, J. Lu and B. de Crombrugghe (1995) Recombinant rat CBF-C, the third subunit of CBF/NFY, allows formation of a protein-DNA complex with CBF-A and CBF-B and with yeast HAP2 and HAP3. Proceedings of the National Academy of Sciences of the United States of America 92, 1624–1628. S.T. Smale and J.T. Kadonaga (2003) The RNA polymerase II core promoter. Annual Review of Biochemistry 72, 449–479. M. Soltysik-Espanola, D.C. Klinzing, K. Pfarr, R.D. Burke and S.G. Ernst (1994) Endo16, a large multidomain protein found on the surface and ECM of endodermal cells during sea urchin gastrulation, binds calcium. Developmental Biology 165, 73–85. Y. Takagi and R.D. Kornberg (2006) Mediator as a general transcription factor. The Journal of Biological Chemistry 268, 80–89. Y. Tamada, K. Nakamori, K. Matsuda, T. Furumoto and K. Izui (2003) Characterization of TAF10, a general transcription factor, in plants. In: 7th International Congress of Plant Molecular Biology, Barcelona, pp. S05–S22. A. Testa, G. Donati, P. Yan, et al. (2005) Chromatin immunoprecipitation (ChIP) on chip experiments uncover a widespread distribution of NF-Y binding CCAAT sites outside of core promoters. The Journal of Biological Chemistry 280, 13606–13615. C.M. Thompson, A.J. Koleske, D.M. Chao and R.A. Young (1993) A multisubunit complex associated with the RNA polymerase II CTD and TATA-binding protein in yeast. Cell 73, 1361–1375. L. Tora (2002) A uniﬁed nomenclature for TATA box binding protein (TBP)-associated factors (TAFs) involved in RNA polymerase II transcription. Genes and Development 16, 673–675. F.T. Tsai and P.B. Sigler (2000) Structural basis of preinitiation complex assembly on human pol II promoters. The EMBO Journal 19, 25–36. J. van de Peppel, N. Kettelarij, H. van Bakel, et al. (2005) Mediator expression proﬁling epistasis reveals a signal transduction pathway with antagonistic submodules and highly speciﬁc downstream targets. Molecular Cell 19, 511–522. C.P. Verrijzer and R. Tjian (1996) TAFs mediate transcriptional activation and promoter selectivity. Trends in Biochemical Sciences 21, 338–342. E.H. Wang, S. Zou and R. Tjian (1997) TAFII250-dependent transcription of cyclin A is directed by ATF activator proteins. Genes and Development 11, 2658–2669. K.B. Washburn, E.A. Davis and S. Ackerman (1997) Coactivators and TAFs of transcription activation in wheat. Plant Molecular Biology 35, 1037–1043. L. Weis and D. Reinberg (1997) Accurate positioning of RNA polymerase II on a natural TATAless promoter is independent of TATA-binding-protein-associated factors and initiator-binding proteins. Molecular and Cellular Biology 17, 2973–2984. F. Werner and R.O. Weinzierl (2002) A recombinant RNA polymerase II-like enzyme capable of promoter-speciﬁc transcription. Molecular Cell 10, 635–646.

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F. Yang, R. DeBeaumont, S. Zhou and A.M. Naar (2004) The activator-recruited cofactor/Mediator coactivator subunit ARC92 is a functionally important target of the VP16 transcriptional activator. PNAS 101, 2339–2344. A. Yoda, H. Kouike, H. Okano and H. Sawa (2005) Components of the transcriptional Mediator complex are required for asymmetric cell division in C. elegans. Development 132, 1885–1893. C.H. Yuh, H. Bolouri and E.H. Davidson (1998) Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene. Science 279, 1896–1902. B. Zenzie-Gregory, A. Khachi, I.P. Garraway and S.T. Smale (1993) Mechanism of initiator-mediated transcription: evidence for a functional interaction between the TATA-binding protein and DNA in the absence of a speciﬁc recognition sequence. Molecular and Cellular Biology 13, 3841–3849. F. Zhang, L. Sumibcay, A.G. Hinnebusch and M.J. Swanson (2004) A triad of subunits from the Gal11/Tail domain of Srb mediator is an in vivo target of transcriptional activator Gcn4p. Molecular and Cellular Biology 24, 6871–6886. J. Zhou, J. Zwicker, P. Szymanski, M. Levine and R. Tjian (1998) TAFII mutations disrupt dorsal activation in the Drosophila embryo. Proceedings of the National Academy of Sciences of the United States of America 95, 13483–13488. T. Zor, R.N. De Guzman, H.J. Dyson and P.E. Wright (2004) Solution structure of the KIX domain of cbp bound to the transactivation domain of c-Myb. Journal of Molecular Biology 337, 521–534.

2 Transcription factors of Arabidopsis and rice: a genomic perspective Jos´e Luis Riechmann

2.1

Introduction

The regulation of many physiological and developmental processes in plants (and in multicellular organisms in general) is largely built upon the cellular capacity for differential gene expression. That capacity is hardwired and encoded in the genome (Davidson, 2001), in the form of cis-regulatory sequences that determine where and when genes are expressed, and exerted by transcription factors and transcriptional coregulators that act on those sequences. Transcription factors are usually deﬁned (and are considered in this chapter) as proteins that show sequence-speciﬁc DNA binding and that are capable of activating or/and repressing transcription. They are modular proteins, with distinct and separable domains for DNA binding and activation/repression, and most of them can be grouped into families according to the amino acid sequence of their DNA-binding domain (Luscombe et al., 2000). In addition, they can bear motifs or domains for protein–protein interactions with other transcription factors, from the same or different families. Transcription factors are the most numerous of all the different classes of proteins involved in transcription. They are building blocks for the mechanisms for selectivity of gene activation, are the principal protein components of the combinatorial logic of transcription, and are often expressed in a tissue-speciﬁc, cell-type-speciﬁc, temporal-speciﬁc, or stimulus-dependent speciﬁc manner. In this chapter, transcription factors are considered in the context of the complete plant genome sequences that are available, i.e., in Arabidopsis and rice. A description of the complement of transcription factors in Arabidopsis and rice sheds light on issues such as gene redundancy, and the ensuing problems for the characterization of the transcription factor phenome, or the degree of functional conservation across species. Recent extensive reviews are available for aspects of transcription factor biology (such as their molecular mechanisms of action) that are not covered here (for example, Riechmann, 2002; Latchman, 2003; Wray et al., 2003). In addition, the genomic technologies developed in the last decade have enabled the analysis of transcription factor activity from the perspective of gene regulatory networks, which is beyond the scope of this chapter but has also been reviewed recently (Wellmer and Riechmann, 2005).

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE

2.2

29

Arabidopsis and rice genomes: the angiosperm complement of transcription factors

The availability of the genome sequences of Arabidopsis thaliana (Arabidopsis Genome Initiative, 2000) and rice (Oryza sativa) (Goff et al., 2002; Yu et al., 2002, 2005; International Rice Genome Sequencing Project, 2005) allows a global, or genomic, analysis of transcriptional regulation in plants. For such analyses, a comprehensive list of parts (in this case, of transcription factors and of the genes that they may regulate) can be generated through various bioinformatic analyses.

2.2.1

General considerations for genome-wide analyses

The identiﬁcation of transcription factor coding genes in a genome sequence is carried out through sequence similarity searches and pattern-ﬁnding methods. Thus, the results obtained reﬂect, and are limited by, the previous knowledge on this class of proteins. All of the major families of transcription factors in plants have probably been already identiﬁed. However, in the case of Arabidopsis, approximately 40–45% of its 26 207 protein-coding genes (annotation release 5, January 2004) do not have meaningful Gene Ontology (GO) categories assigned to them (i.e., they remain classiﬁed as ‘unknown’) (Haas et al., 2005). Similarly, biological functions have not been assigned for ∼50% of the genes in rice (International Rice Genome Sequencing Project, 2005; Yu et al., 2005). It is likely that some of these uncharacterized proteins are transcriptional regulators, and, in fact, novel transcription factors are still being discovered, which are often found to belong to (small) gene families (for example, Desveaux et al., 2000; Bouche et al., 2002; Sangwan and O’Brian, 2002; Yang and Poovaiah, 2002; Zourelidou et al., 2002; C¸ akir et al., 2003; Carrasco et al., 2003; Curaba et al., 2003; Desveaux et al., 2004; Meister et al., 2004; Mitsuda et al., 2004; Mouchel et al., 2004; Carles et al., 2005; Carrasco et al., 2005; Yin et al., 2005). Conversely, new experimental evidence may question (or eventually disprove) whether proteins once considered transcription factors actually play such a role (for example, the TUBBY-like proteins or TULP; Carroll et al., 2004). Therefore, the exact number and identity of transcription factor genes present in Arabidopsis and rice (as well as, for the same reasons, in any other of the sequenced eukaryotic genomes) will be uncertain for some time. Additional issues in genome-wide surveys include whether all the proteins identiﬁed by sequence similarity searches do indeed belong to the functional groups into which they are being cataloged, and the degree of completeness of the genome sequence under study. For example, only a subset of the proteins that bear a C2H2 zinc-ﬁnger motif are actually transcription factors, whereas others are involved in other processes, such as splicing (Riechmann et al., 2000; Englbrecht et al., 2004). In addition, gene sequences might diverge more than expected, which might hamper the identiﬁcation of homologous genes through sequence similarity searches (for

30

REGULATION OF TRANSCRIPTION IN PLANTS

a discussion of these issues, including examples in Arabidopsis, see Riechmann, 2002). For these and other reasons, different genome-wide searches for genes of the same family may result in slightly different gene sets (for an illustrative example about the bHLH proteins in Arabidopsis, see Bailey et al., 2003) (see also Table 2.1).

2.2.2

Arabidopsis transcription factors

The analysis of the Arabidopsis genome sequence indicates that it codes for at least 1589 transcription factors, which account for ∼6% of its estimated ∼26 200 protein-coding genes (Table 2.1) (Arabidopsis Genome Initiative, 2000; Riechmann et al., 2000). These 1589 transcription factor genes are classiﬁed into more than 40 different gene families and, in addition, there are a few single-copy or ‘orphan’ genes, such as LEAFY (LFY) and SPOROCYTELESS (SPL) (Table 2.1). Many of those gene families are large, with over, or close to, 100 members, and the largest of them, bHLH, AP2/ERF, and MYB-(R1)R2R3 factors, each represent ∼9% of the transcription factor complement, or 0.5% of the total number of genes in the genome (Table 2.1). A recently developed online database of Arabidopsis transcription factors (DATF) aims to present a comprehensive view of them by integrating multiple sources of information, in particular about gene families and gene sets (http://datf.cbi.pku.edu.cn/; Guo et al., 2005). Data in DATF are very similar to the results summarized in Table 2.1, with the differences being due to the use in Table 2.1 of slightly more stringent criteria for considering a gene or members of a gene family as bona ﬁde transcription factors. Salient features of the Arabidopsis complement of transcription factors (that also apply to other plant genomes) were highlighted in a comparative study that included the genomes of Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster, and that illustrated the large degree of diversity in transcriptional regulators that is present among the different eukaryotic kingdoms (Riechmann et al., 2000; Riechmann, 2002). Arabidopsis transcription factors that belong to families that are common to all eukaryotes do not share signiﬁcant similarity with those from the other kingdoms, except in the conserved DNA-binding domains that deﬁne the respective families (Riechmann et al., 2000). In addition, other sources of diversity include the presence of lineage-speciﬁc families, uneven ampliﬁcation of common families among eukaryotic lineages (and between plant lineages, i.e., monocots and dicots, see below), and protein domain shufﬂing. In general, transcription factor families have collectively higher expansion rates in plants than in animals: the majority of the families that are shared between plants and animals are larger in plants (Riechmann et al., 2000; Shiu et al., 2005). For example, two of the largest Arabidopsis families, MYB and MADS, are very small in fungi and animals. However, in animals and fungi there tends to be one or two speciﬁc transcription factor families that have been enormously and disproportionately ampliﬁed, more so than any of the families in plants: for example, the nuclear hormone receptors in C. elegans (∼38% of its transcription factors), the C2H2 zincﬁnger proteins in Drosophila (∼46%) and humans, or the C6 and C2H2 families in yeast (∼25% each) (Riechmann et al., 2000; Riechmann, 2002). In plants, there

31

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE Table 2.1

Arabidopsis transcription factorsa,b

Gene family

Number of genesc

Genetically characterized factorsd

e

AP2/ERF AP2 subfamily f ERF-EREBP subfamily RAV subfamily BHLH bHLH

19 122

6 123

(-b)HLH MYB superfamily MYB-(R1)R2R3

39 135

MYB-related C2H2 (Zn)

52 113

NAC

109

HB

91

MADSg Type II (MIKC)h

46

Type Ii

bZIP

WRKY (Zn)

?-64

77

72

ANT, AP2, PLT1, PLT2, WRI1 ABI4, AtERF7, CBF1, CBF2, CBF3, CBF4, ERF1, DRN/ESR1, SHN2, SHN3, WIN1/SHN1 — ALC, AMS, BEE1, BEE2, BEE3, BIM1, BIM2, BIM3, EGL3, FIT1, FAMA, GL3, HFR1, ICE1, NAI1, PIF1/PIL5, PIF3, PIF4, MYC2/JIN1, SPT, TT8 IND AS1, ATR1, BOS1, DUO1, FLP, GL1, HOS10, LAF1, MYB2, MYB4, MYB12, MYB23, MYB26, MYB30, MYB32, MYB33, MYB60, MYB61, MYB65, MYB88, MYB98, MYB103, PAP1, PAP2, TT2, WER CCA1, CPC, EPR1, ETC1, LHY, TRY EMF2, FIS2, JAG, KNU, RBE, RHL41, SE, SUP, TT1, VRN2 ATAF2, CUC1, CUC2, CUC3, NAC1, NAP, NST1, NST2, RD26, VND6, VND7 ANL2, ATHB-2, ATHB-8, ATHB-13, ATHB-15, ATML1, BEL1, CNA, GL2, HOS9/PFS2, KNAT1/BP, OCP3, PDF2, PHB, PHV, PNF, PNY/BLR/RPL, PRS, REV, STIP, STM, WUS AG, AGL15, AGL24, ANR1, AP1, AP3, CAL, FLC, FUL, MAF1, MAF2, PI, SEP1, SEP2, SEP3, SEP4, SHP1, SHP2, SOC1, STK, SVP, TT16

—

ABI5, ABF2, ABF3, ABF4, EEL, FD, HY5, HYH, PAN, TGA2, TGA5, TGA6 TTG2, RRS1, WRKY22, WRKY29, WRKY70

Gene family references Riechmann and Meyerowitz, 1998; Sakuma et al., 2002; Gutterson and Reuber, 2004; Yamasaki et al., 2004b; Nole-Wilson et al., 2005 Bailey et al., 2003; Buck and Atchley, 2003; Heim et al., 2003; Toledo-Ortiz et al., 2003

Stracke et al., 2001; Jiang et al., 2004

Takatsuji, 1999; Englbrecht et al., 2004 Ooka et al., 2003; Ernst et al., 2004; Olsen et al., 2005 Chan et al., 1998; Schrick et al., 2004

Riechmann and Meyerowitz, 1997; Ng and Yanofsky, 2001; Becker and Theissen, 2003; De Bodt et al., 2003a,b; Kofuji et al., 2003; Martinez-Castilla and Alvarez-Buylla, 2003; Parenicova et al., 2003; Lehti-Shiu et al., 2005

Sib´eril et al., 2001; Jakoby et al., 2002; Vincentz et al., 2003; Deppmann et al., 2004 Eulgem et al., 2000; Ulker and Somssich, 2004 (Continued )

32

REGULATION OF TRANSCRIPTION IN PLANTS

Table 2.1 Arabidopsis transcription factorsa,b (Continued )

Gene family

Number of genesc

GARP G2-like

41

Genetically characterized factorsd

13

APL, GLK1, GLK2, KAN1, KAN2, LUX, PHR1 ARR1, ARR2, ARR10, ARR11, ARR12

C2C2 (Zn) Dof

36

CDF1, COG1, DAG1, DAG2, OBP3

CO-like

32

CO, COL1, COL9

GATA

30

HAN

ARR-type B/pseudoARRtype B

YABBY CCAAT-binding factor HAP2-type HAP3-type HAP5-type Dr1 GRAS

10 11 13 2 32

— LEC1, L1L — — GAI, LAS, PAT1, RGA, RGL1, RGL2, SCR, SHR

Trihelix TCP

29 24

PTL PTF1

ARF

23

HSF

21

ARF2/HSS, ARF3/ETT, ARF4, ARF5/MP, ARF6, ARF7/NPH4, ARF8, ARF10, ARF16, ARF19 HSF1, HSF3

STK-like

17

—

C3H-type 1 (Zn) SBP (Zn)

17 17

PEI1 SPL3, SPL8

GRF/ENBP (C3H-type2; Zn)

16

AtGRF1–3, AtGRF5

Nin-like ABI3/VP1 ZF-HB (Zn) SRS (Zn) E2F/DP CPP (Zn) Alﬁn-like GBP-like/BPC

14 14 14 10 8 8 7 7

— ABI3, FUS3, LEC2 — SHI, STY1, STY2 E2Fa, E2Fb, DPa, DEL1 TSO1 — —

EIL

6

6

CRC, FIL, INO

EIN3, EIL1

Gene family references Riechmann et al., 2000 Rossini et al., 2001 Hosoda et al., 2002; Hwang et al., 2002; Lohrmann and Harter, 2002; Mason et al., 2004 Yanagisawa, 2002; Lijavetzky et al., 2003 Lagercrantz and Axelsson, 2000; Grifﬁths et al., 2003 Reyes et al., 2004; Shikata et al., 2004 Bowman, 2000 Lotan et al., 1998; Gusmaroli et al., 2001, 2002

Pysh et al., 1999; Richards et al., 2000; Bolle, 2004; Tian et al., 2004 Zhou, 1999; Ayadi et al., 2004 Cubas et al., 1999; Cubas, 2002; Kosugi and Ohashi, 2002 Guilfoyle and Hagen, 2001; Remington et al., 2004; Okushima et al., 2005 Nover et al., 2001; Kotak et al., 2004 Zourelidou et al., 2002; Curaba et al., 2003 Li and Thomas, 1998 Cardon et al., 1999; Yamasaki et al., 2004a Christiansen et al., 1996; van der Knaap et al., 2000; Kim et al., 2003 Schauser et al., 2005 Stone et al., 2001 Windh¨ovel et al., 2001 Fridborg et al., 2001 de Jager et al., 2001 Cvitanich et al., 2000 Bastola et al., 1998 Sangwan and O’Brian, 2002; Meister et al., 2004 Chao et al., 1997

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE Table 2.1

33

(Continued )

Gene family

Number of genesc

Genetically characterized factorsd

Gene family references

NtLIM1-like (Zn) BES CAMTA

6 6 6

— BES1, BZR1 —

BRX-like DBP-like S1Fa-like

5 5 3

BRX — —

Whirlye HRT-like (Zn) VOZ (Zn) ULT LFY SPL/NZZ SAP

3 2 2 2 1 1 1

AtWhy1 — — ULT1 LFY SPL/NZZ SAP

Kawaoka et al., 2000 Yin et al., 2005 Bouche et al., 2002; Yang and Poovaiah, 2002 Mouchel et al., 2004 Carrasco et al., 2005 Zhou et al., 1995 Desveaux et al., 2002, 2005 Krause et al., 2005 Raventos et al., 1998 Mitsuda et al., 2004 Carles et al., 2005 Weigel et al., 1992 Schiefthaler et al., 1999 Byzova et al., 1999

a

Transcription factors are usually deﬁned as proteins that show sequence-speciﬁc DNA binding and the capability to activate or repress transcription. However, the distinction between ‘transcription factors’ and other transcriptional regulators is not without problems (see, Riechmann et al., 2000; Riechmann, 2002). Most of the genes counted here fulﬁll those characteristics, but some do not (for example, some proteins of the bHLH family, indicated as the (-b)HLH subfamily, may not actually bind DNA); on the other hand, proteins that work together with some transcription factors, such as the IAA proteins that work with ARF proteins, have not been included in the table. b (Zn) indicates a zinc-coordinating motif. c The data shown in the table are an updated (October 2005) version of those in Riechmann (2002). Additional genome-wide analyses of several Arabidopsis transcription factor families have been published more recently. The results of such analyses have also been used to update the table, when appropriate, and if so, they are cited in the ‘Gene family references’ column. d Includes genes characterized by loss of function and/or, if informative results were obtained, by gain of function (as of October 2005). The correspondence between acronyms and gene names can be found at TAIR (http://www.arabidopsis.org). e The AP2/ERF family was initially referred to as AP2/EREBP, for AP2/ethylene-r esponsive element binding protein; the Whirly family was initially referred to as PBF-2-like, after the founding member, potato PBF-2. f The AP2 subfamily contains 19 members. Fourteen of them are proteins with two AP2 domains each (R1 and R2). The other ﬁve are proteins with only one clearly recognizable AP2 domain, but that domain is more related in sequence to either R1 or R2 than to the single AP2 domain of any of the ERF subfamily proteins. g The MADS-box family has been the subject of several genome-wide gene identiﬁcation and phylogenetic analyses. Whereas these studies (and the analysis reported in Riechmann et al., 2000) agree on the size and composition of the MIKC subfamily of MADS-box genes (Type II MADS-box genes, according to Alvarez-Buylla et al., 2000), they differ in the number of recognized Type I genes, as well as on their classiﬁcation in different phylogenetic subgroups. Only the broad subdivision of the MADS family into Type I and Type II genes is considered here (following the classiﬁcation of Martinez-Castilla and Alvarez-Buylla, 2003). h Type II (MIKC) includes MADS-box genes of the classic MIKC-type (also referred to as MIKCc ) and also genes of the MIKC∗ -type (see Becker and Theissen, 2003; Kofuji et al., 2003). i The identiﬁcation and classiﬁcation of Type I genes has differed among the various studies, in part because of poor conservation of typical key MADS-domain residues. For example, some genes exhibit a highly divergent N-terminal region of the MADS box (and also lack other conserved regions); those genes were considered MADS like by De Bodt et al., but were included in the MADS family by Parenicova et al. and Kofuji et al. Furthermore, it is unclear (but possible) whether some of the Type I genes might be pseudogenes, nonfunctional genes, the result of (retro)transposition events, or perhaps even represent a new class of transposable elements (De Bodt et al., 2003b; Parenicova et al., 2003). For these reasons, since it is still unclear how many of Type I MADSbox genes are in fact functional transcription factor genes, the number of members of the subfamily is indicated as ‘?-64’.

34

REGULATION OF TRANSCRIPTION IN PLANTS

is no family of transcription factors that represents by itself one third or more of the total number of transcription factors in the organism. Shufﬂing of some of the DNA-binding domains that are present in all eukaryotes has generated novel transcriptional regulators with plant-speciﬁc combinations of modules, as, for example, in the homeodomain, MADS, and ARID protein families (Riechmann et al., 2000; Riechmann, 2002). Furthermore, in Arabidopsis, approximately 45% of its transcription factors belong to families that are speciﬁc to the plant kingdom (when compared to animals and fungi, i.e., among the crown-group eukaryotes), whereas ∼53% correspond to families that are present in plants, fungi, and animals (the remaining minority belonging to families that are present in two of the three kingdoms) (Riechmann et al., 2000; Riechmann, 2002) (see Table 2.1). However, some of the ‘plant-speciﬁc’ families of transcription factors have also been recently identiﬁed in noncrown-group eukaryotes. In addition, new sequence and structural data are showing how the DNA-binding domains of some of the plant-speciﬁc transcription factor families are related to proteins present in other organisms, in which those domains may not form part of transcription factors but rather of other types of (DNA-binding) proteins. Thus, some proteins might have evolved as transcription factors after the plant lineage split from animals and fungi, but the structural frameworks for the DNA-binding domains were already present in ancestral organisms (Yamasaki et al., 2005a). A large plant-speciﬁc family of transcription factors is the AP2/ERF group, characterized by the presence of the AP2 DNA-binding domain. The AP2 domain itself, however, is not plant speciﬁc, since it has been found in endonucleases of different organisms (cyanobacteria, ciliates, and viruses) and in putative transcription factors from apicomplexans (such as the malarial parasite Plasmodium) (Magnani et al., 2004; Wuitschick et al., 2004; Balaji et al., 2005). Similarly, the B3 DNA-binding domain, which is present in several plantspeciﬁc families of transcription factors (ARF, ABI3/VP1, and RAV) (Riechmann, 2002), is structurally related to the EcoRII DNA-binding domain (Yamasaki et al., 2004b). The WRKY DNA-binding domain, also initially considered plant speciﬁc, does not show strong structural similarity to other known domains (Yamasaki et al., 2005a), but it has been found in a primitive eukaryote (the unicellular protist Giardia lamblia) and in the slime mold Dictyostelium discoideum (as well as in the green alga Chlamydomonas reinhardtii) (Ulker and Somssich, 2004; Wu et al., 2005; Zhang and Wang, 2005); the RWP-RK domain, the putative DNA-binding region characteristic of the plant NIN-like proteins, is also found in D. discoideum and in C. reinhardtii (Schauser et al., 2005). In summary, some of the domains that deﬁne families of transcription factors initially considered speciﬁc to plants predate the plant–fungus/animal divide. On the other hand, the structures of the DNA-binding domains of the SBP, NAC, and EIL proteins (all apparently plant speciﬁc) represent novel folds (Ernst et al., 2004; Yamasaki et al., 2004a, 2005b). Because of their regulatory nature, it is often thought that transcription factors are generally expressed at low levels relative to other genes. However, various types of genomic data contradict such assumption, and indicate that, at least in plants, transcription factor genes are not substantially different from the rest of the genes in the genome in terms of overall expression and when considered as a whole. Analyses of Arabidopsis expressed sequence tags (ESTs) (Riechmann, 2002), of the RIKEN

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE

35

full-length (RAFL) cDNA clone collection (Seki et al., 2002), or of various macroand microarray gene expression datasets (Chen et al., 2002; Jiao et al., 2003; de Folter et al., 2004; Wellmer et al., 2004; Schmid et al., 2005), all indicate that the average expression of transcription factors is similar to the average expression for all genes. However, for transcription factors that are expressed in discrete, often small, spatial and temporal domains, detection of their expression may require real-time polymerase chain reaction (PCR) experiments (Czechowski et al., 2004). Quantitative real-time PCR is generally more sensitive than microarrays, and can thus alleviate the problem caused by isolating heterogenous tissue samples in which the abundance of the transcript(s) of interest is reduced (it is often difﬁcult, if at all possible, to speciﬁcally isolate the cells/tissues in which a given transcription factor may be expressed – rather, those cells/tissues are usually isolated together with cells/tissues in which it is not; Schnable et al., 2004; Wellmer and Riechmann, 2005).

2.2.3

Rice transcription factors: a comparison to Arabidopsis

The rice genome has been sequenced using the whole-genome shotgun method (in draft and ﬁnished form, and for two different rice subspecies, indica and japonica) (Goff et al., 2002; Yu et al., 2002, 2005), and also with a map-based strategy (subsp. japonica) (International Rice Genome Sequencing Project, 2005). Initial global analyses of the sequence illustrate the general similarities and differences with Arabidopsis, in transcription factor gene content (Xiong et al., 2005). In addition, many families and subfamilies of transcription factors have been the subject of detailed analyses in rice; these include the WRKY (Wu et al., 2005; Xie et al., 2005; Zhang and Wang, 2005), NAC (Ooka et al., 2003), MADS (MIKC-type, Nam et al., 2004), MYB (Jia et al., 2004; Jiang et al., 2004), bHLH (Buck and Atchley, 2003), AP2/ERF (ERF subfamily, Gutterson and Reuber, 2004), Dof (Lijavetzky et al., 2003), GRAS (Tian et al., 2004), HB (START-HB subfamily, Schrick et al., 2004), GATA (Reyes et al., 2004), GRF (Choi et al., 2004), CO-like (Grifﬁths et al., 2003), and NIN-like families (Schauser et al., 2005). Overall, the transcription factor gene complements of Arabidopsis and rice are similar in terms of the total number of genes and the relative sizes of the different gene families, as expected, since the evolutionary divergence between the monocot and dicot lineages is a relatively recent event (∼150–200 million years ago). A recent study identiﬁed ∼1600 transcription factor coding genes in the rice genome sequence (Xiong et al., 2005). Applying the criteria used in Table 2.1 (which yielded 1589 Arabidopsis transcription factors), and also accounting for the differences in the quality of sequence annotation, it is possible to estimate the rice genome codes for ∼1800 transcription factors (representing 4.8–4.4% of the estimated 37 500– 40 000 nontransposable-element-related protein-coding sequences in the genome; Bennetzen et al., 2004; International Rice Genome Sequencing Project, 2005; Yu et al., 2005). The relative sizes of the families in the two organisms are generally maintained, with minor variations; for example, NAC and WRKY families are proportionally larger in rice, whereas the MADS family appears to be larger in Arabidopsis (Figure 2.1). However, both genomes have a complicated history of

Figure 2.1 Content and distribution of transcription factor genes in Arabidopsis and rice. The data represented in this ﬁgure are from Xiong et al. (2005). Arabidopsis and rice data were obtained in that study using the same analyses and criteria, which allows for a more consistent comparison between the two organisms than if results from two separate studies were used. Because of this, however, the Arabidopsis data in this ﬁgure do not match perfectly with those in Table 2.1, although the general conclusions that can be drawn from the Arabidopsis versus rice comparison remain valid. Differences between the study by Xiong et al. and Table 2.1 are minor differences in gene number (for example, 105 NAC family genes identiﬁed by Xiong et al., versus 109 in Table 2.1), recently identiﬁed families that were not included in the study by Xiong et al. (such as CAMTA, VOZ, BES, and BRX-like), and differences in family deﬁnition (for example, for the C2H2 proteins; only the EPF subfamily was considered by Xiong et al.). In addition, some families are not included in the ﬁgure (Trihelix, C3H-type1) due to larger discrepancies between the results of Xiong et al. and previous analyses. Single-copy genes are not included in the ﬁgure. The data for the Dof and GATA families are from Lijavetzky et al. (2003) and Reyes et al. (2004), respectively, and from Table 2.1.

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE

37

large- and gene-scale duplications, and it appears that many lineage-speciﬁc events have contributed to generating the respective current gene sets. Phylogenetic analyses of individual gene families with both Arabidopsis and rice sequences (or with Arabidopsis and maize; for example, Rabinowicz et al., 1999; Munster et al., 2002) show the presence of many common subgroups or clades, indicating that gene duplications and ampliﬁcation of the gene families had already taken place in the most recent common ancestor (MRCA) of monocots and dicots. In fact, through such analyses it has been estimated that the common ancestor of rice and Arabidopsis had a set of at least ∼400 ancestral transcription factor genes (Xiong et al., 2005). Many cases of 1:1 orthologous relationships can be identiﬁed between Arabidopsis and rice genes (usually corresponding to well-conserved functions). However, there are also many instances of 1:n, n:1, and n:n relationships (originated by duplications that took place after the two lineages had separated and/or by lineage-speciﬁc geneloss events), as well as species-speciﬁc genes for which no putative orthologs can be identiﬁed in the other organism (Figure 2.2). Orthologous groups of the 1:n and n:1 types may correspond to functions that have diversiﬁed in one species but not in the other, whereas those of the n:n type correspond to functions that might have diversiﬁed in both, and genes that are classiﬁed as lineage speciﬁc in these analyses may correspond to species-speciﬁc or highly specialized functions. The MADS-box family provides examples of all these scenarios. Many cases of orthology can be identiﬁed between Arabidopsis MADS-box genes and those from rice or maize, and even from gymnosperms (Becker and Theissen, 2003; Nam et al., 2004). Putative orthologous MADS-box genes have regularly maintained conserved functions, even after substantial sequence divergence. On the other hand, there are a few MADS-box genes that are not members of clades shared by Arabidopsis and rice, for example, the Arabidopsis ﬂowering time genes FLC and MAF1-5 (Ratcliffe et al., 2003), which form a monophyletic group, Arabidopsis AGL15, and rice OsMADS32 (Nam et al., 2004). Rice and Arabidopsis have 37 and 39 MADS-box genes of the MIKCc (or Type II) class, respectively (Figure 2.2; Nam et al., 2004), and at least 32 genes have been already identiﬁed in maize (Munster et al., 2002). The number of ancestral genes in the MRCA of monocots and dicots has been estimated as 12–20, and many MADS-box gene duplication and diversiﬁcation events occurred earlier than that, after the separation of the moss and fern lineages from the lineage that originated the ﬂowering plants (Munster et al., 2002; Becker and Theissen, 2003; Nam et al., 2003, 2004; Zahn et al., 2005). Diversity of MADS-box genes in Arabidopsis is thus rather ancient, and it appears that it is fairly representative for other ﬂowering plants (Becker and Theissen, 2003). Other families of transcription factors had similar evolutionary histories, although the proportion of species- or lineage-speciﬁc genes, and the degree of ampliﬁcation after a given lineage divergence step, varies by gene family (see Figure 2.2 and associated references). In addition, gene clades that are shared by monocots and dicots might evolve at different rates. For example, within the WRKY family, subgroup III is largely ampliﬁed in monocots and appears to be evolutionarily more active than in Arabidopsis (Wu et al., 2005; Zhang and Wang, 2005). Interestingly, it appears that WRKY genes are overrepresented in ﬂowering plants in comparison with fern, moss, or pine; because WRKY genes are important regulators for biotic

38

REGULATION OF TRANSCRIPTION IN PLANTS

Figure 2.2 Summary of orthologous relationships between Arabidopsis and rice genes for selected transcription factor gene families. A hypothetical phylogenetic tree is depicted to illustrate the different types of relationships that are considered: 1 : 1, 1 : n and n : 1 (duplications in rice or Arabidopsis), n : n (duplications in both), and speciﬁc to one of the two plants. Because the complete map-based sequence of the rice genome was not available when the phylogenetic studies were performed, various sources of rice sequences were used to identify gene family members (whole-genome shotgun assemblies from the indica and/or japonica subspecies, sequences from the International Rice Genome Sequencing Project (IRGSP), and cDNA sequences and ESTs). Families and phylogenetic analyses that were used to create this ﬁgure are as follows: WRKY (Wu et al., 2005), MADS (MIKC-type proteins only) (Nam et al., 2004), GRAS (Tian et al., 2004), Dof (Lijavetzky et al., 2003), GATA (Reyes et al., 2004), and CO-like (Grifﬁths et al., 2003). The percentage of genes classiﬁed as ‘speciﬁc’ for each of the families and plants is indicated.

and abiotic stress responses, and ﬂowering plants are dominant over nonﬂowering plants in their distribution, it has been hypothesized that WRKY genes might be important for such adaptability (Zhang and Wang, 2005).

2.2.4

Gene duplications, functional redundancy, and the transcription factor phenome

The Arabidopsis and rice genomes contain many tandem gene duplications, as well as many large duplicated chromosomal segments – the result of ancient whole

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE

39

genome duplication event(s) that occurred during their evolution (Simillion et al., 2002; Blanc et al., 2003; Bowers et al., 2003; Cannon et al., 2004; Yu et al., 2005). Many of these duplications have been followed by the loss of duplicated genes, by rearrangements, or by divergent evolution – but still up to 40–50% of the Arabidopsis genes comprise pairs of highly related sequences (Arabidopsis Genome Initiative, 2000; Blanc et al., 2000). The process of gene loss following duplication appears nonrandom, since genes from some functional categories (including, but not limited to, transcription factors) have been preferentially retained in Arabidopsis (Blanc and Wolfe, 2004). Closely related genes account for ∼45% of the total number of members in the major families of transcription factors (Riechmann et al., 2000). Importantly, pairs or groups of closely related transcription factor genes in Arabidopsis are most often located in different chromosomes (∼65% on average), or in the same chromosome but at very large distances (∼22%; the remaining 13% corresponding to tandem repeats) (Riechmann et al., 2000). This distribution makes it feasible to generate the respective double or triple mutants, which are often required for the analysis of highly related genes that may have overlapping or partially redundant functions. Approximately 230 Arabidopsis transcription factors have been genetically characterized (∼15% of the transcription factor gene complement; Table 2.1). Whereas in the early years of Arabidopsis research, characterization was achieved through the traditional genetic approach (whereby genes are ﬁrst deﬁned by a mutant phenotype and then isolated), reverse genetics methods are currently widely used (Zhang, 2003; Østergaard and Yanofsky, 2004) and have facilitated targeted analyses of closely related genes (see below). Still, for the majority of these transcriptional regulators, functional characterization is usually limited to the description of phenotypic differences between mutant and wild-type plants, and determination of their expression pattern, and there is limited knowledge on the genes that they regulate and on the mechanisms that they use to achieve that regulation. However, gene expression microarrays and other genomic approaches are starting to shed light on the dynamic relationships between the transcriptional regulators, the transcriptome, and the genome (Wellmer and Riechmann, 2005). Of particular relevance to transcription factors, DNA microarrays have been used to compare the transcriptome of transcription factor mutant versus wild-type plants (for example, Mele et al., 2003; Schmid et al., 2003; Wellmer et al., 2004) and to follow gene expression changes after the speciﬁc induction or activation of the transcription factor under study, as a way to identify genes potentially regulated by such transcription factor or that form part of the network that it controls or participates in. In these experiments, synthetic systems in which the transcription factor is fused to the rat glucocorticoid receptor (GR), and thus exogenously activated with dexamethasone, are generally used. Arabidopsis regulators that have already been studied using GR fusions include LFY, AGAMOUS (AG), and NPR1 (Ito et al., 2004; Wagner et al., 2004; William et al., 2004; Gomez-Mena et al., 2005; Wang et al., 2005b). In addition, the global gene expression proﬁling of physiological or developmental processes (Chen et al., 2002; Nemhauser et al., 2004; Hannah et al., 2005) can lead to the identiﬁcation of transcription factors that may be involved in their regulation, but that had not been uncovered by genetic analyses (for example, Bergmann et al., 2004).

40

REGULATION OF TRANSCRIPTION IN PLANTS

Probably the two main difﬁculties for generating a comprehensive phenome of a plant’s transcriptional regulator set are the ﬁnite number of assays in which the mutants can usually be screened and the existence of functional redundancy among different genes (Riechmann and Ratcliffe, 2000; Riechmann, 2002). Many examples of functional redundancy or overlap among highly related Arabidopsis transcription factors have been uncovered in recent years, already encompassing ∼36% of the total number of transcription factors functionally characterized and including the majority of gene families (Table 2.2). In many of these cases, single mutants exhibit either subtle or no phenotypic alterations, whereas the double (or triple) mutants show much more drastic phenotypic changes. Furthermore, in addition to redundancy resulting from the incomplete functional divergence between paralogs, it can also arise from functional convergence of more distantly related gene family members. Although the extent of this type of redundancy in Arabidopsis is unknown, there is evidence that it exists. For example, AINTEGUMENTA acts redundantly with APETALA2 to repress AG expression in cells of the second whorl of developing Arabidopsis ﬂowers (the two proteins belong to the AP2 subfamily, but to different clades within it) (Krizek et al., 2000).

2.3

Plant promoters

Transcription factors regulate gene expression in a combinatorial manner, through different cis-elements that coordinately regulate the expression of the corresponding gene. Cis-acting elements are usually organized in a modular fashion: the regulatory region of a gene can be partitioned into discrete sub-elements, each containing one or several binding sites for transcription factors and performing a certain regulatory function. These modules can interact synergistically, i.e., combinations of modules can direct gene expression in a manner not observed with the modules in isolation (for reviews see Riechmann, 2002; Wray et al., 2003). Regulatory sequences of plant genes usually span relatively short DNA intervals (as compared to animals, metazoans in particular), often less than 1 or 2 kb. This is illustrated by the compact organization of the Arabidopsis and rice genomes, in which gene density is high. In Arabidopsis, there is one gene per 4.5 kb of DNA: the gene length (from annotated transcriptional start to stop) is approximately 2.2 kb, and ∼2.3 kb corresponds to intergenic regions. Considering the whole genome, transposons account for ∼20% of the intergenic DNA, resulting in an average of 1.9 kb of DNA for the 5 and 3 regions of a particular gene (Arabidopsis Genome Initiative, 2000). In rice, gene density is lower (one nontransposable-element-related protein-coding gene per ∼10 kb), but the average gene length is similar to that in Arabidopsis (International Rice Genome Sequencing Project, 2005; Yu et al., 2005). Other plants have much larger genomes than those of Arabidopsis or rice (∼2500 Mbp in the case of maize, for example), but with a similar organization of genes. In maize, genic regions occupy less than 10–20% of the genome, usually in the form of compact gene-rich islands, with much of the remaining genomic DNA corresponding to repetitive sequences made up of retrotransposons and other elements (Palmer et al., 2003; Whitelaw et al., 2003; Messing et al., 2004).

41

TRANSCRIPTION FACTORS OF ARABIDOPSIS AND RICE Table 2.2

Functional redundancy among related Arabidopsis transcription factors Redundant or overlapping function

Gene family

Genes

AP2/ERF

PLT1, PLT2

AP2/ERF AP2/ERF bHLH bHLH bHLH

CBF1, CBF2, CBF3 WIN1/SHN1, SHN2, SHN3 BEE1, BEE2, BEE3 BIM1, BIM2, BIM3 GL3, EGL3, TT8

MYB-R2R3 MYB-R2R3

FLP, MYB88 GL1, MYB23

MYB-R2R3 MYB-related

MYB33, MYB65 ETC1, TRY, CPC

MYB-related

LHY, CCA1

Circadian rhythmicity

NAC

CUC1, CUC2, CUC3

NAC

NST1, NST2

HB

PNF, PNY

HB

PDF2, ATML1

HB

PHB, PHV, REV, CNA

HB MADS

KNAT1/BP, STM AP1, CAL, FUL

Shoot apical meristem formation; organ separation Secondary wall thickening and anther dehiscence Response to ﬂoral inductive signals Shoot epidermal cell differentiation Radial patterning (PHB, PHV, REV); meristem regulation (PHB, PHV, CNA) Stem cell function Floral meristem identity

MADS

AG, SHP1, SHP2, STK

MADS

SEP1, SEP2, SEP3, SEP4

BZIP WRKY GARP

TGA2, TGA5, TGA6 WRKY22, WRKY29 GLK1, GLK2

Root meristem: stem cell niche patterning and maintenance Freezing tolerance Regulation of wax biosynthesis Brassinosteroid signaling Brassinosteroid signaling Trichome and root hair development, anthocyanin production (GL3, EGL3); seed coat mucilage regulation (TT8, EGL3) Stomatal patterning Trichome initiation at leaf edges Anther development Trichome and root hair cell patterning

Fruit dehiscence (SHP1, SHP2); Carpel identity (AG, SHP1, SHP2); Ovule identity (AG, SHP1, SHP2, STK) Floral organ identity

Systemic acquired resistance Innate immunity Chloroplast development

References Aida et al. (2004)

Gilmour et al. (2004) Aharoni et al. (2004), Broun et al. (2004) Friedrichsen et al. (2002) Yin et al. (2005) Bernhardt et al. (2003), Zhang et al. (2003a)

Lai et al. (2005) Kirik et al. (2005) Millar and Gubler (2005) Schellmann et al. (2002), Esch et al. (2004), Kirik et al. (2004) Alabadi et al. (2002), Mizoguchi et al. (2002) Aida et al. (1997), Takada et al. (2001), Vroemen et al. (2003) Mitsuda et al. (2005) Smith et al. (2004) Abe et al. (2003) Emery et al. (2003), Prigge et al. (2005) Byrne et al. (2002) Bowman et al. (1993), Kempin et al. (1995), Ferr´andiz et al. (2000) Liljegren et al. (2000), Pinyopich et al. (2003)

Pelaz et al. (2000), Honma and Goto (2001), Pelaz et al. (2001), Ditta et al. (2004) Zhang et al. (2003b) Asai et al. (2002) Fitter et al. (2002) (Continued )

42

REGULATION OF TRANSCRIPTION IN PLANTS

Table 2.2 Functional redundancy among related Arabidopsis transcription factors (Continued )

Gene family

Genes

GARP GARP

KAN1, KAN2 ARR1, ARR2, ARR10, ARR11, ARR12 FIL, YAB3 GAI, RGA, RGL1, RGL2

YABBY GRAS

ARF

ARF5/MP, ARF7/NPH4, ARF19

ARF

ARF6, ARF8

ARF ARF SRS BES

ARF3/ETT, ARF4 ARF10, ARF16 STY1, STY2 BES1, BZR1

Redundant or overlapping function

References

Lateral organ polarity Cytokinin signal transduction

Eshed et al. (2001) Mason et al. (2005)

Lateral organ development Gibberellin signaling

Kumaran et al. (2002) Dill and Sun, (2001), King et al. (2001), Lee et al. (2002), Wen and Chang (2002), Tyler et al. (2004) Hardtke et al. (2004), Okushima et al. (2005), Weijers et al. (2005), Wilmoth et al. (2005)

Embryo axial patterning, vascular development (ARF5, ARF7); lateral root formation, leaf cell expansion, gravitropism (ARF7, ARF19) Jasmonic acid production and ﬂower maturation Organ asymmetry Root cap formation Gynoecium development Brassinosteroid signaling

Nagpal et al. (2005) Pekker et al. (2005) Wang et al. (2005a) Kuusk et al. (2002) Yin et al. (2005)

As a result of this genomic organization, regulatory sequences in Arabidopsis, and in plants in general, are easier to identify and delimit experimentally than in animals (see Riechmann, 2002). Compact Arabidopsis and rice 5 promoter sequences often recapitulate faithfully the expression of the native gene when assayed in transgenic plants by reporter gene fusions, that is, in a chromatin context. However, this is not always the case, because regulatory elements can also be localized downstream of the transcription start site. For example, the expression of the Arabidopsis MADS-box gene AG has been shown to depend on its large, second intron, which contains binding sites for at least two AG regulators, LFY and WUSCHEL (WUS) (Sieburth and Meyerowitz, 1997; Bomblies et al., 1999; Busch et al., 1999; Deyholos and Sieburth, 2000; Lohmann et al., 2001). Other Arabidopsis genes that depend on intronic sequences for the regulation of their expression are FLC and SEEDSTICK (both MADS-box genes; Sheldon et al., 2002; Kooiker et al., 2005), as well as PETAL LOSS (a trihelix transcription factor; Brewer et al., 2004). In other cases, regulation is mediated by elements in the 5 or 3 untranslated regions (Larkin et al., 1993; Chen et al., 1998; Yu et al., 2001), in sequences farther downstream (Ito et al., 2004), or, more rarely, even in coding sequences (Ito et al., 2003). Interestingly, two recent reports in maize have described or suggested that sequences located far upstream (50–100 kb) of the transcription start site of a gene can inﬂuence its expression, perhaps after being separated from the transcribed sequences by the insertion of retroelements – these are the ﬁrst exceptions to the general rule that gene regulatory regions in plants are relatively short (Stam et al., 2002; Clark et al., 2004).

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3 Chromatin-associated architectural HMGA and HMGB proteins assist transcription factor function Klaus D. Grasser and Dorte Launholt

3.1

Introduction

Within the cell nucleus, the genomic DNA of eukaryotic organisms is packaged into a highly complex and dynamic nucleoprotein structure known as chromatin. The best studied level of chromatin organisation is the wrapping of the DNA around histone octamers, resulting in the formation of nucleosome particles, which consist of two copies each of the core histones (H2A/B, H3 and H4) and ∼146 bp of DNA. Assisted by linker histones, the nucleosomal arrays fold into higher order chromatin ﬁbres comprising the chromosomes. The compaction of the DNA provided by chromatin represses the transcription of genes by restricting the access of DNA-binding regulatory factors to their DNA target sites, and by inhibiting the progression of RNA polymerases. Since both initiation and elongation of RNA polymerase II transcription are inhibited in the chromatin context in vitro, the dynamic assembly and disassembly of the genomic DNA into chromatin represents an important level of gene regulation. Numerous non-histone proteins regulate the transient changes in chromatin structure that prime the nuclear DNA for gene expression. Thus, post-translational modiﬁcation of histones (acetylation, methylation, etc.) (see Chapter 4) and ATP-dependent chromatin-remodelling complexes (see Chapter 5) are involved in altering the chromatin structure stimulating activatordependent transcription. The high mobility group (HMG) proteins are (after the histones) the second most abundant family of chromosomal proteins. Their presence in all tissues of eukaryotes favours the possibility that the HMG proteins are required for proper cellular function. Due to their abundance, HMG proteins serve a global structural function in the nucleus, and they act as architectural factors, facilitating various DNA-dependent processes such as transcription and recombination. More than 30 years ago, HMG proteins were identiﬁed as contaminants in histone H1 preparations. Originally they were deﬁned based on their extractability from chromatin by 0.35 M NaCl, their solubility in 2% trichloroacetic acid or 5% perchloric acid and their high content of charged amino acid residues (Goodwin et al., 1973). Because of their characteristic primary structures, mammalian HMG proteins have been subdivided into three distinct families (Bustin and Reeves, 1996; Bianchi and Agresti, 2005),

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whose nomenclature has been revised (Bustin, 2001): r HMGA proteins (formerly HMGI/Y) containing AT-hook DNA-binding motifs r HMGB proteins (formerly HMG1/2) containing HMG-box domain(s) r HMGN proteins (formerly HMG14/17) containing a nucleosome-binding domain In plants, proteins belonging to the HMGA and HMGB families have been identiﬁed and characterised over the past years (Spiker, 1988; Grasser, 1995), whereas HMGN proteins so far have been found exclusively in vertebrates. The pioneering work on plant HMG proteins by Spiker and co-workers has identiﬁed and characterised the HMG proteins from wheat germ, revealing structural differences between the plant and animal HMG proteins (Spiker, 1984, 1988; Spiker and Everett, 1987). Isolation and characterisation of HMG proteins (and of the cDNAs encoding these proteins) from various mono- and dicotyledonous species essentially conﬁrmed the initial ﬁndings obtained for the wheat germ proteins (Grasser, 1995).

3.2 3.2.1

HMGA proteins Structure and expression

HMGA proteins have been identiﬁed in higher eukaryotes including mammals, insects and plants. Plant HMGA proteins (∼20 kDa) display an overall structure that is different from that of their counterparts in other organisms (Klosterman and Hadwiger, 2002; Grasser, 2003). Thus, plant HMGA proteins contain four copies of the AT-hook DNA-binding motif, while mammalian and insect HMGA have three AT-hooks (Figure 3.1). The AT-hook motif is a short, positively charged sequence containing the invariant GRP core (Figure 3.2), which is usually ﬂanked by proline, arginine and lysine residues (Bustin and Reeves, 1996). The short acidic region found at the C-terminus of mammalian and insect HMGA proteins does not occur in plant HMGA. However, the most obvious structural difference is the plantspeciﬁc presence of an N-terminal domain of ∼65 amino acid residues, which shares sequence similarity with the globular domain of H1 linker histones (Figure 3.2). The evolutionary relation of plant HMGA proteins and linker histones is also evident from the presence of a single intron in the plant HMGA genes, which is localised within the H1-like domain. The position of this intron is conserved between HMGA genes and the genes coding for linker histones (Krech et al., 1999). HMGA proteins from various plant species share 40–80% amino acid sequence identity (Gupta et al., 1997b; Yamamoto and Minamikawa, 1997b). In the absence of DNA, the nuclear magnetic resonance spectrum of the AT-hook region of human HMGA indicates random coil, but upon DNA binding, the part of the protein that contacts the DNA becomes ordered and adopts a well-deﬁned conformation. Thereby, the RGR motif

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Figure 3.1 Schematic representation of HMGA proteins from various eukaryotes. The AT-hook regions representing the DNA-binding motifs of all HMGA proteins are indicated by black boxes, while the domain similar to the globular domain of linker histone H1 speciﬁc for plant HMGA is indicated by a light-grey box and the C-terminal acidic region speciﬁc for mammalian and insect HMGA is indicated by a dark-grey box.

Figure 3.2 Alignment of the amino acid sequences of plant HMGA proteins. The alignment contains the sequences of the HMGA proteins deduced from cDNAs of Glycine max (X58246, X58244), Canavalia gladiata (D83070, D83071), Pisum sativum (X89568), Arabidopsis thaliana (X99116), Oryza sativa (L24390), Triticum aestivum (AF502250) and Zea mays (AJ131371, AF291748). The region sharing sequence similarity with the globular domain of linker histone H1 and the GRP center of the AT-hook motifs are highlighted in black.

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of the AT-hooks presents a narrow concave surface that perfectly ﬁts into the minor groove of A/T-rich tracts (Huth et al., 1997). The HMGA proteins of mammals and insects are subject to various posttranslational modiﬁcations (Reeves and Beckerbauer, 2001). They are phosphorylated by several protein kinases including CDC2, MAP kinase, CK2 and PKC, and the phosphorylations modulate the nucleosome- and DNA interactions of the HMGA proteins (Bustin, 1999; Banks et al., 2000; Schwanbeck et al., 2001). Accordingly, the phosphorylations are likely to regulate functional properties of HMGA proteins in vivo. Moreover, it has been reported that the HMGA proteins can be modiﬁed by multiple acetylations and methylations (Edberg et al., 2004; Sgarra et al., 2004, 2006; Edberg et al., 2005; Miranda et al., 2005; Zou and Wang, 2005). Thus, (mammalian) HMGA proteins are highly modiﬁed by post-synthetic modiﬁcations, and some of the modiﬁcations are tissue speciﬁc or dependent on the developmental state (Edberg et al., 2004, 2005; Sgarra et al., 2004). Analogous to the histone code, the existence of a ‘modiﬁcation code’ for HMGA was suggested that may be expressed differentially, for instance, in normal and malignant cells (Edberg et al., 2004). Comparatively little is currently known about post-synthetic modiﬁcations of plant HMGA proteins. In a study examining HMGA from maize endosperm tissue, it was found that HMGA is phosphorylated by the CDC2 kinase (Zhao and Graﬁ, 2000), suggesting that post-translational modiﬁcations contribute also to the regulation of plant HMGA proteins. The expression of mammalian HMGA genes is upregulated in undifferentiated, rapidly proliferating cells or during embryonic development, whereas they are expressed at low levels in fully differentiated or non-dividing cells (Reeves and Beckerbauer, 2001). Some plant species including Arabidopsis and pea have one type of HMGA protein (Gupta et al., 1997a,b), while other species including Canavalia gladiata and soybean encode two different HMGA proteins (Laux et al., 1991; Yamamoto and Minamikawa, 1997b) (cf. Figure 3.2). The plant HMGA genes appear to be expressed ubiquitously (Laux et al., 1991; Gupta et al., 1997a,b, 1998; Yamamoto and Minamikawa, 1997a,b; Zhang et al., 2003b), but the HMGA expression levels vary between different tissues, possibly correlated to the proliferative state of the cells (Gupta et al., 1997b; Zhang et al., 2003b). The level of maize HMGA is elevated during endoreduplication in developing endosperm tissue, suggesting that HMGA is involved in the formation of a more open chromatin conﬁguration facilitating transcription and/or replication (Zhao and Graﬁ, 2000). In pea, HMGA was found to be expressed at decreased levels upon pathogen infection. Moreover, HMGA can reduce gene expression driven by a defence gene promoter, suggesting that HMGA is involved in the regulation of plant defence gene expression (Klosterman et al., 2003).

3.2.2

DNA and chromatin interactions

Mediated by the AT-hooks, HMGA proteins bind preferentially to the minor groove of A/T-rich stretches of double-stranded DNA (Reeves and Beckerbauer, 2001). Both electrostatic and non-electrostatic components contribute to the DNA binding of HMGA (Huth et al., 1997; Dragan et al., 2003). Depending on the DNA substrate,

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binding of mammalian HMGA proteins can bend, straighten, unwind and loop the DNA molecules in vitro (Reeves and Beckerbauer, 2001). The interaction of plant HMGA proteins of various sources with DNA has been examined in several studies using electrophoretic mobility shift assays and DNA footprinting (Pedersen et al., 1991; Nieto-Sotelo et al., 1994; Webster et al., 1997; Yamamoto and Minamikawa, 1997a; Gupta et al., 1997b; Zhang et al., 2003a). In these experiments, the HMGA proteins interact with varying afﬁnities with different A/T-motifs in double-stranded DNA. Random oligonucleotide selection experiments with pea HMGA have revealed that the protein binds to A/T-stretches of ﬁve or more base pairs (Webster et al., 1997). Using surface plasmon resonance it has been discovered that HMGA has an approximately sevenfold higher afﬁnity for A/T-rich double-stranded DNA than the structurally unrelated HMGB proteins (Webster et al., 2000). Experiments with truncated HMGA proteins have demonstrated that the individual H1-like domain does not interact with DNA, and that at least two AT-hook motifs are required for efﬁcient DNA binding (Nieto-Sotelo et al., 1994; Zhang et al., 2003a). A detailed DNA-binding analysis has shown that the four AT-hooks of the wheat HMGA protein do not contribute equally to the interaction with a PetE promoter fragment, since the N-terminal AT-hooks play a major role in DNA binding. The regions ﬂanking the AT-hook motifs (cf. Figure 3.2) can modulate the DNA binding that is primarily dictated by the AT-hooks, and therefore account for the distinct DNA binding of the individual AT-hook regions (Zhang et al., 2003a). These differences seen in DNAbinding experiments are in line with structural studies of various AT-hook regions demonstrating that the regions ﬂanking the core of the AT-hooks contact the DNA to different extents (Huth et al., 1997). Mammalian HMGA proteins also interact preferentially with four-way junction DNA, contacting both the branch point, as well as sites on the arms of the DNA substrate. The mode of binding is distinct from that of HMGB proteins and histone H1, although all three protein families share the speciﬁc binding to four-way junction DNA, and compete for binding to four-way junctions (Hill et al., 1999). Using electrophoretic mobility shift assays and surface plasmon resonance the speciﬁc binding of wheat HMGA to four-way junction has been demonstrated (Zhang et al., 2003a). The interaction of wheat HMGA with four-way junction DNA was compared with that of HMGB proteins and histone H1 for the same substrate, revealing that the relative binding afﬁnity of three types of proteins is in the order of HMGA > H1 > HMGB (Zhang et al., 2003b). The interaction of HMGA with native chromatin has been studied in intact maize nuclei. HMGA could be released from the highly nuclease-sensitive chromatin by limited digestion with micrococcal nuclease, indicating that HMGA primarily associates with the non-compacted, transcriptionally active chromatin. Moreover, HMGA could be selectively released from chromatin by spermidine and distamycin A (Lichota and Grasser, 2001). Distamycin A intercalates into A/T-rich DNA, and can compete for HMGA binding in naked DNA (Webster et al., 1997), suggesting that HMGA binds A/T-tracts both in naked DNA and in nucleosomal templates. Mammalian HMGA proteins interact with nucleosome core particles (containing ∼146 bp of DNA, lacking internucleosomal linker DNA) binding in close proximity to histones H2A/B and H3 (Reeves and Nissen, 1993). Plant HMGA can speciﬁcally

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59

bind to isolated mononucleosome particles in vitro, both core particles (Arwood and Spiker, 1990), as well as nucleosomes containing ∼165 bp of DNA (including linker DNA) (Lichota and Grasser, 2001). HMGA interacts with isolated nucleosomes by a mode that differs from that of the HMGB proteins (Lichota and Grasser, 2001).

3.3 3.3.1

HMGB proteins Structure and expression

HMGB proteins have been identiﬁed from various higher plants and they have in common an overall structure that differs from that of HMGB proteins of other sources (Grasser, 1995). In plant HMGB proteins (∼13–27 kDa) the central HMGbox DNA-binding domain is ﬂanked by a basic N-terminal domain and a highly acidic C-terminal domain (Figure 3.3). The HMG-box domain of ∼75 amino acid residues has a conserved L-shaped fold with an angle of ∼80◦ between the arms, consisting mainly of three α-helices (Travers, 2000; Thomas and Travers, 2001). The basic N-terminal and the acidic C-terminal domains are variable in size and amino acid sequence (Figure 3.4), accounting for the differences in molecular mass of the members of plant HMGB protein family (Grasser, 2003). In Arabidopsis, for instance, the N-terminal domain of the HMGB5 protein is composed of 29 amino acid residues, whereas the N-terminal domain of HMGB6 comprises 111 amino acid residues (Grasser et al., 2004). Using intramolecular crosslinking and spectrometric techniques, it has been demonstrated that the terminal domains of plant HMGB proteins can interact, which modulates various functional properties of the proteins (Thomsen et al., 2004). Higher plants express several structurally variable HMGB proteins. Five HMGB proteins have been identiﬁed from the monocot plant maize (Stemmer et al., 1999) and six related proteins have been characterised from the dicot plant Arabidopsis (Stemmer et al., 1997; Grasser et al., 2004). A recent study of two additional Arabidopsis HMGB-type proteins has revealed that despite striking sequence

Figure 3.3 Schematic representation of the structure of HMGB proteins from various eukaryotes. HMG-box domains are indicated by dark-grey boxes, while the C-terminal acidic domains found in the plant, insect and vertebrate proteins, but not in the yeast NHP6a/b proteins, are indicated by black boxes. HMG boxes of the ‘single HMG-box proteins’ have a higher degree of similarity to the second HMG box (B-domain) than to the ﬁrst HMG box (A-domain) of vertebrate HMGB.

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Figure 3.4 Alignment of the amino acid sequences of HMGB proteins from Arabidopsis thaliana, Oryza sativa and Zea mays (cf. Table 3.1; for sequence details see Plant Chromatin Database, http://www.chromdb.org/). We have considered only sequences that share the typical overall structure of plant HMGB proteins, containing a central HMG-box domain that is ﬂanked by a basic N-terminal and an acidic C-terminal domain. The potential primary and secondary intercalating residues within the HMG-box domain are indicated in bold, and the relative position of introns within the amino acid sequences are indicated by triangles.

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similarity to the previously characterised HMGB proteins, one of the analysed proteins has properties that are very different from those of typical HMGB proteins. According to analyses of green ﬂuorescent protein (GFP) fusions, this protein (encoded by the AGI locus At5g23405) is mainly localised in the cytoplasm (rather than the nucleus) and it does not bind to DNA (Grasser et al., 2006). Therefore, HMGB proteins that have been predicted solely based on their amino acid sequences should be evaluated experimentally. Currently, comprehensive information about the members of the plant HMGB protein family (from systematic experimental studies and/or genome projects) is available only for few species. We have summarised the characteristics of the HMGB-type proteins encoded by the maize, rice and Arabidopsis genomes in Table 3.1. The amino acid sequences of the same group of proteins were used to construct an amino acid sequence similarity tree that reveals the relationship between the protein sequences (Figure 3.5). There is a close relationship between the monocot HMGB sequences. Thus, there are rice proteins resembling all the HMGB proteins that have been characterised from maize, but instead of the pairs of maize HMGB2/3 and HMGB4/107 proteins (∼90% amino acid sequence identity for each Table 3.1

HMGB proteins of Arabidopsis, rice and maize

Proteina

Length Mass

Acc. no.

Locus

AtHMGB1 AtHMGB2 AtHMGB3 AtHMGB4 AtHMGB5 AtHMGB6 AtHMGB14∗ AtHMGB12∗ ZmHMGB1 ZmHMGB2 ZmHMGB3 ZmHMGB4 ZmHMGB5 ZmHMGB106∗ ZmHMGB107∗ OsHMGB1 OsHMGB710∗ OsHMGB707∗ OsHMGB706∗ OsHMGB705∗ OsHMGB711∗

178 aa 144 aa 141 aa 138 aa 125 aa 241 aa 151 aa 149 aa 157 aa 139 aa 138 aa 126 aa 123 aa 212 aa 127 aa 157 aa 146 aa 131 aa 145 aa 202 aa 133 aa

Y14071 Y14072 Y14073 Y14074 Y14075 AY086023 AY084626 AY052244 X58282 Y08297 Y08298 Y08807 AJ006708 AF527617 AF527616 AY262827 AP005742 XM 473515 AP004858 XM 479646 XM 473515

At3g51880 At1g20693 At1g20696 At2g17560 At4g35570 At5g23420 At2g34450 At5g23405

20265 15982 15681 15364 14203 26964 17481 16997 17146 15316 15007 14104 13637 23534 14215 17100 16349 13873 15765 22328 15566

Structurespeciﬁc DNANuclear DNA-bindingb bendingc localisationd +1 +1 +1 +1 +1 +2 +7 −7 +3 +3 +3 +3

Os06g51220 +4 Os09g37910 Os04g47690 Os02g44930 Os08g01100 Os01g47600

+u +u

+2 −7 −7 +3,5 +3,5 +3,5 +3,5

+u +u +2 +7 −7 +6 +6 +6 +6 +6

+4

Published name of protein or ∗ name used in Plant Chromatin Database (http://www.chromdb.org/). Experimental evidence for structure-speciﬁc DNA binding to four-way junction DNA, minicircles or supercoiled DNA. c Experimental evidence for DNA bending (circularisation, ﬂuorescence resonance energy transfer (FRET)). d Experimental evidence for nuclear localisation (GFP fusions, cell fractionation). b,c,d References of the functional HMGB protein studies: 1 Stemmer et al., 1997; 2 Grasser et al., 2004; 3 Ritt et al., 1998b; 4 Wu et al., 2003a,b; 5 Wisniewski et al., 1999a; 6 Grasser et al., 1991; 7 Grasser et al., 2006; u our unpublished results.

a

b

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Figure 3.5 Amino acid sequence similarity tree of HMGB-type proteins from Arabidopsis thaliana (At), Oryza sativa (Os) and Zea mays (Zm). The amino acid sequences (Plant Chromatin Database, http://www.chromdb.org/) were aligned by multiple sequence alignment that was used to construct the tree, using the ClustalW software. The upper part contains all the sequences related to the previously characterised HMGB proteins (‘traditional HMGBs’), while the lower part contains the HMGB-type sequences (‘novel HMGBs’) related to Arabidopsis HMGB6 (Grasser et al., 2004).

pair) there is only a single rice protein each. The Arabidopsis HMGB proteins (in particular the HMGB4 and HMGB5 proteins) form a rather separate group. The group of ‘novel HMGB proteins’ speciﬁed by AtHMGB6 (Grasser et al., 2004) also forms a distinct set of sequences, grouping at the bottom of the tree (Figure 3.5). In general, the HMGB proteins of monocots and dicots (currently just based on Arabidopsis sequences) display to some extent different structural features (with the exception of the Arabidopsis HMGB2/3 proteins, which share similarities with maize and rice HMGB1). It requires further studies to clarify whether the structural differences seen between the maize/rice and Arabidopsis HMGB proteins are reﬂected by functional differences. Based on the available studies, currently there is no indication of signiﬁcant functional differences between monocot and dicot HMGB proteins (Grasser, 2003).

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63

HMGB proteins of mammals are subject to various post-translational modiﬁcations including acetylation, methylation, ADP ribosylation and glycosylation (van Holde, 1989). Mammalian HMGB1 can be acetylated at multiple sites (Bonaldi et al., 2003), and acetylation of a lysine residue in the N-terminal region of mammalian HMGB1 can enhance its binding to DNA structures (Ugrinova et al., 2001). HMGB proteins of the insect Chironomus tentans are phosphorylated by protein kinases PKC and CK2, altering the DNA-binding properties of the proteins (Wisniewski et al., 1994, 1999b). Post-translational modiﬁcation of plant HMGB proteins initially was recognised, since the proteins puriﬁed from plant tissues (according to mass spectrometric measurements) displayed masses that were signiﬁcantly larger than the calculated masses of the proteins (Webster et al., 1997; Stemmer et al., 1999). Further analysis of some maize HMGB proteins revealed that masses of the native proteins could be reduced essentially to the calculated masses by dephosphorylation with alkaline phosphatase (Stemmer et al., 2002b, 2003). Hence, plant HMGB proteins are phosphoproteins in vivo that occur in differentially phosphorylated variants (Stemmer et al., 2003). Mapping of the phosphorylation sites identiﬁed serine residues within the acidic C-terminal domains of the analysed proteins, and the same residues could be phosphorylated in vitro by protein kinase CK2α (Stemmer et al., 2002b). Therefore, protein kinase CK2 is involved in the phosphorylation of HMGB proteins of plants (and insects, see above). CK2 is a conserved eukaryotic Ser/Thr kinase that occurs in various isoforms in the plant cell nucleus and cytosol (Riera et al., 2001). CK2 is suspected to play a global role in transcription-related chromatin remodelling (Barz et al., 2003) and is involved in cell growth and proliferation, as well as in stress response and cell survival (Litchﬁeld, 2003; Meggio and Pinna, 2003). Phosphorylation of plant HMGB proteins by CK2 increases protein stability against thermal denaturation (Stemmer et al., 2002b). In line with this ﬁnding, the phosphorylation enhances intramolecular interactions between the basic N-terminal and the acidic C-terminal domains of maize HMGB1 (Thomsen et al., 2004). Based on Northern and Western blot analyses, the HMGB genes appear to be expressed ubiquitously in plants (O’Neill and Zheng, 1998; Yamamoto and Minamikawa, 1998; Stemmer et al., 1999; Wu et al., 2003a). The various HMGB proteins that simultaneously occur in the same tissue appear to be of very different abundance. Accordingly, the ﬁve maize HMGB proteins are present in markedly different amounts (HMGB1 and HMGB2/3 are ∼20 times more abundant than HMGB4 and HMGB5), and the relative amounts of the proteins differ between the analysed tissues (Stemmer et al., 1999). The situation might be similar in Arabidopsis, as according to the very different number of expressed sequence tag hits in the database (http://www.arabidopsis.org/), the various HMGB genes are expressed at different levels. In the short-day plant Pharbitis nil, the expression of an HMGB gene is regulated by an endogenous circadian rhythm, whereas another HMGB gene is not under the control of photoperiod or an endogenous rhythm, suggesting that some HMGB proteins may be involved in the circadian-regulated gene expression (O’Neill and Zheng, 1998).

64

3.3.2

REGULATION OF TRANSCRIPTION IN PLANTS

DNA and chromatin interactions

In general, the DNA-binding properties of HMGB proteins are characterised by non-sequence-speciﬁc interaction with linear double-stranded DNA. However, the proteins speciﬁcally recognise various DNA structures, including four-way junctions, DNA minicircles and cis-platinated DNA. Another important feature of the HMGB proteins in their function as architectural factors is their ability upon DNA binding to bend linear DNA by over 90◦ (Travers, 2000; Thomas and Travers, 2001; Agresti and Bianchi, 2003; Grasser, 2003). Structural studies of protein–DNA complexes have revealed a number of details regarding the DNA interaction of nonsequence-speciﬁc HMG-box domains (Murphy et al., 1999; Ohndorf et al., 1999; Masse et al., 2002). The concave face of the L-shaped HMG-box domain primarily contacts the minor groove of the DNA, and a hydrophobic wedge is inserted deep into the minor groove. Two residues partially intercalate between base pairs introducing a kink, which contributes signiﬁcantly to the overall bend (Travers, 2000; Thomas and Travers, 2001). The potential primary intercalating residue of the plant HMGB proteins is a well-conserved phenylalanine residue while in the majority of the proteins the secondary intercalating residue is valine (cf. Figure 3.4). The intercalating residues of HMG-box domains play a critical role in DNA binding and modulating DNA structure by bending and supercoiling (He et al., 2000; Stros and Musel´ıkov´a, 2000; Klass et al., 2003). In various studies it has been demonstrated that plant HMGB proteins bind to certain DNA structures such as DNA minicircles, four-way junctions and supercoiled DNA with higher afﬁnity than that for the corresponding linear DNA (Grasser et al., 1994, 2004; Stemmer et al., 1997; Ritt et al., 1998b; Webster et al., 2001; Wu et al., 2003b; Zhang et al., 2003b). As studied by electrophoretic mobility shift assays, DNA footprinting and surface plasmon resonance, plant HMGB proteins bind to a variety of (A/T-rich) promoter regions (Pedersen et al., 1991; Grasser et al., 1994; Webster et al., 1997, 2000; Wu et al., 2003b). Random oligonucleotide binding site selection experiments have revealed that a pea HMGB protein in principle binds non-sequence-speciﬁcally to DNA, but it displays a preference for structurally ﬂexible sites in linear DNA containing deformable dinucleotide steps (Webster et al., 1997). In line with that, plant HMGB proteins upon DNA binding can severely bend the DNA (Table 3.1), as demonstrated by ﬂuorescent resonance energy transfer (Wisniewski et al., 1999a) and circularisation experiments (Grasser et al., 1994; Ritt et al., 1998b; Webster et al., 2001; Wu et al., 2003b). DNA fragments shorter than ∼150 bp (due to the inﬂexibility of the DNA) cannot be ligated intramolecularly. However, in the presence of a DNA-bending protein, intramolecular ring closure catalysed by DNA ligase can occur. In circularisation assays of this type, in the presence of DNA ligase the HMGB proteins can mediate covalent intramolecular ring closure of short DNA fragments. Maize HMGB1, for instance, could facilitate the formation of DNA minicircles as small as 70 bp, demonstrating its ability to bend the DNA remarkably (Grasser et al., 1994). HMGB proteins from various sources have been shown to bend DNA severely, and the bending activity is an important

ARCHITECTURAL HMG PROTEINS

65

feature of the HMGB proteins in their function as architectural factors (Ritt et al., 1998b; Webster et al., 2001; Wu et al., 2003b). The basic N-terminal domain of maize and rice HMGB1 signiﬁcantly stimulates the binding to linear DNA, whereas the acidic C-terminal domain has the opposite effect. However, the domains ﬂanking the central HMG-box DNA-binding domain have only little inﬂuence on the binding to DNA minicircles, since the interaction with minicircles is an inherent property of the HMG-box domain. Full-length HMGB1 displays DNA-binding properties similar to those of the individual HMGbox domain, suggesting that the terminal domains functionally neutralise each other (Ritt et al., 1998a; Wu et al., 2003b). This ﬁnding is in line with the interaction of the basic N-terminal and the acidic C-terminal domains in maize HMGB1, which is facilitated by CK2-mediated phosphorylation of residues within the acidic tail of the protein (Thomsen et al., 2004). Moreover, the phosphorylation negatively inﬂuences binding to linear DNA, while the phosphorylation does not affect the afﬁnity for DNA minicircles (Stemmer et al., 2002b). The phosphorylation-induced interaction of the basic N-terminal and the acidic C-terminal domains limits the positive effect of the basic domain on interactions with linear DNA, while the basic region is dispensable for binding DNA minicircles (Ritt et al., 1998a; Wu et al., 2003b). The basic N-terminal domain can support binding to linear DNA by directly interacting with the DNA (Ritt et al., 1998a; Thomsen et al., 2004). Similar to the yeast HMGB protein, NHP6A (Yen et al., 1998; Masse et al., 2002), the HMG-box domain may bind to the minor groove, whereas the basic N-terminal domain wraps over the DNA backbone from the minor groove into the major groove of the DNA, thereby stabilising the protein–DNA interaction. The chromatin association of maize HMGB proteins was examined by releasing the proteins from isolated nuclei, using various reagents. The different HMGB proteins were similarly extracted from chromatin by NaCl, but there were clear differences in the extractability using ethidium bromide and spermine. Ethidium bromide released preferentially HMGB2/3 and HMGB4, whereas spermine released exclusively HMGB1 (Lichota and Grasser, 2001). Differential extraction of HMGB proteins was also observed from wheat and rice chromatin (Arwood et al., 1991; Van den Boeck et al., 1994). The chromatin association was also studied by limited digestion of the chromatin with micrococcal nuclease. HMGB2/3 appears to be associated primarily with the highly nuclease-sensitive chromatin, whereas HMGB1 and especially HMGB4 and HMGB5 were released only after more extensive digestion of the chromatin (Lichota and Grasser, 2001). In summary, these results indicate that the various plant HMGB proteins are differentially associated with chromatin. In addition to DNA binding, speciﬁc interactions with histones (and their variants) and other chromosomal proteins are likely to be important determinants of the differential chromatin association of plant HMGB proteins. In line with these results, the HMGB proteins of the dipteran insect Chironomus, termed cHMG1a and cHMG1b, are distinctly distributed in chromosomes (Ghidelli et al., 1997). The cHMG1a protein is uniformly distributed along the chromosome, whereas the cHMG1b protein is speciﬁcally localised in chromosomal puffs of interphase giant chromosomes,

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REGULATION OF TRANSCRIPTION IN PLANTS

indicating a role in transcription. The in vitro interaction of HMGB proteins with nucleosomes has been examined by electrophoretic mobility shift assays, revealing that maize HMGB proteins can bind speciﬁcally to isolated mononucleosomes containing DNA of ∼165 bp (Lichota and Grasser, 2001). Since wheat HMGB proteins form rather non-speciﬁc complexes with nucleosome core particles (containing ∼146 bp of DNA) (Arwood and Spiker, 1990), the interaction with linker DNA may be a critical feature for the nucleosome binding of plant HMGB proteins. Analysis of the nucleosome interactions of full-length and truncated HMGB1 proteins demonstrated that only the full-length protein can bind to nucleosomes speciﬁcally, as both deletion of the basic N-terminal domain and deletion of the acidic C-terminal domain abolish speciﬁc nucleosome interactions (Lichota and Grasser, 2001). Most likely, proper nucleosome interaction of the plant HMGB proteins requires simultaneous interactions of the HMG-box domain and the acidic tail with DNA and core histone(s), respectively.

3.4

Dynamic interaction of histone H1 and HMG proteins with chromatin

Mammalian nuclei contain a relatively constant amount of linker histone H1 of almost one molecule of H1 per nucleosome (∼107 molecules), which indicates that the majority of nucleosomes are bound by H1 (van Holde, 1989; Bustin et al., 2005). On the other hand it has been estimated that nuclei contain ∼106 molecules of HMGB and ∼104 molecules of HMGA proteins, and their cellular amounts can differ, depending on the developmental state (van Holde, 1989; Bustin, 1999). H1 and HMGB proteins share several DNA-binding features (see also above) and there also are similarities in their chromatin interactions (Zlatanova and van Holde, 1998; Jerzmanowski et al., 2000). This has led to the proposal that the accessibility of nucleosomal DNA for regulatory proteins can be controlled by displacing H1 by other proteins, and HMG proteins are obvious candidates for this function (Zlatanova et al., 2000). In line with this possibility, H1 and HMGB proteins differentially affect the accessibility of the nucleosomal DNA (Ragab and Travers, 2003). The relatively high expression level of Xenopus and Drosophila HMGB proteins during certain stages of development (when the H1 levels are comparatively low) suggested that HMGB and linker histones share a structural role in organizing chromatin (Ner and Travers, 1994; Nightingale et al., 1996). The inverse regulation of the expression of HMGB proteins and linker histones, however, is a feature that is observed only in few cases and therefore does not explain in general the interaction of HMGB proteins and linker histones. Recent studies have revealed that the bulk of core histones is immobile on DNA in the cell nucleus, but the majority of other DNA-interacting proteins are mobile. Using photobleaching techniques such as ﬂuorescence recovery after photobleaching (FRAP), it has been demonstrated that various nuclear proteins display very different mobility in mammalian cell nuclei (Misteli, 2001; Hager et al., 2002). In contrast to earlier assumptions, H1 is a mobile molecule that interacts with the

ARCHITECTURAL HMG PROTEINS

67

nucleosome only transiently, before it dissociates to bind to another site, and the mobility is modulated by post-translational modiﬁcations of H1 (Lever et al., 2000; Misteli et al., 2000; Horn et al., 2002). Previous experiments have revealed that HMGB1 does not stably associate with chromatin in the cell nucleus (Falciola et al., 1997). In line with that, recent FRAP experiments have shown that HMGB and HMGA proteins are highly mobile proteins with a residence time on chromatinbinding sites in the order of seconds, but still the main fraction of the proteins is bound to chromatin at steady state (Catez et al., 2004; Phair et al., 2004). The proteins ﬁnd their binding sites by three-dimensional scanning of the nucleus, transiently binding to target sites and then rapidly moving on to the next site (Phair et al., 2004). Intriguingly, in this scenario HMGA and HMGB proteins compete with histone H1 for binding sites, weakening H1 binding to chromatin, whereas the HMGs of different families do not compete with each other (Catez et al., 2004). These ﬁndings are consistent with earlier studies demonstrating that HMGA could cause transcriptional activation by displacing inhibitory proteins such as linker histone H1 from A/T-rich scaffold attachment regions (SARs, also termed matrix attachment regions, MARs) (Zhao et al., 1993). Maize HMGA could also relieve in vitro the inhibitory effect exerted by H1 on transcription driven by an A/T-rich zein gene promoter, suggesting that transcription may be controlled to some extent by the interplay of HMGA and H1 (Zhao and Graﬁ, 2000). A/T-rich sequences can act in general as quantitative, non-tissue-speciﬁc enhancers of plant gene expression, and binding of HMGA to these sequences may play a critical role (Sandhu et al., 1998). By reducing the binding of H1, HMG proteins may induce a less compact chromatin structure facilitating the access of regulatory factors to their nucleosomal target sites. The chromatin structure and accessibility of the genomic DNA packaged into nucleosomes are constantly modulated by a dynamic and competitive interaction network of chromosomal proteins (Catez et al., 2004; Phair et al., 2004).

3.5

HMGA and HMGB proteins as architectural assistant factors

Various analyses studying altered expression levels of HMGA and HMGB genes have demonstrated that the chromosomal HMG proteins have important cellular roles. Knockout of the mouse HMGA1 gene revealed that HMGA1 is required for normal sperm development (Liu et al., 2003), and that disrupting the HMGA1 gene results in a decreased expression of the insulin receptor, largely impairing insulin signalling (Foti et al., 2005). Inactivation of the HMGA2 gene causes the mouse pygmy phenotype, and a deﬁciency in fat tissue, probably due to affected fat-cell proliferation (Zhou et al., 1995; Anand and Chada, 2000). The lack of HMGB1 causes pleiotropic defects in mice and they die soon after birth, but cell lines can grow normally without HMGB1 (Calogero et al., 1999). Mice lacking HMGB2 (which is ∼80% identical to HMGB1) are viable, but male mice have reduced fertility, as HMGB2 seems to play a role in germ cell differentiation (Ronfani et al., 2001). Reduction of the amount of the HMGB-type proteins HMGD/Z in Drosophila causes only minor morphological defects. HMGD/Z was found to interact genetically with the Brahma

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REGULATION OF TRANSCRIPTION IN PLANTS

chromatin-remodelling complex (Ragab et al., 2006). Functional interaction with chromatin-remodelling complexes also has been observed for mammalian HMGB1, stimulating nucleosome sliding (Bonaldi et al., 2002). Ectopic expression of maize HMGB1 in tobacco seedlings resulted in reduced length of the primary root, whereas the shoot of the seedlings had wild-type appearance. This ‘short-root’ phenotype of the transgenic lines correlated with a decreased size of the cells in the cell division zone of the root. In these plants, the cell division rate rather than the cell elongation appears to be affected (Lichota et al., 2004). In yeast, knockout of one of the two NHP6A/B genes (encoding HMGB proteins) did not result in a phenotype distinct from the wild type, but the inactivation of both genes led to growth aberrations such as temperature-sensitive growth and various morphological defects (Costigan et al., 1994). Analyses of the gene expression in the strain lacking both NHP6A and NHP6B revealed that the induction of transcription and the expression levels of a variety of genes are altered relative to the control strain (Paull et al., 1996; Moreira and Holmberg, 2000). The expression of the majority of genes is not affected, but certain genes are upregulated, whereas other genes are downregulated in the doublemutant strain, presumably depending on whether the architectural factors assist the formation of stimulatory or repressive complexes. A well-established function of the HMGA and HMGB proteins is their architectural function in the proper three-dimensional assembly of nucleoprotein complexes regulating transcription (Reeves and Beckerbauer, 2001; Agresti and Bianchi, 2003; Grasser, 2003). The formation of these complexes is primarily under the control of DNA-binding factors, which recognise speciﬁcally cis-acting DNA target sequences. In eukaryotes, usually various regulators bound to different DNA sequence elements interact to form higher order nucleoprotein structures in which multiple protein–protein and protein–DNA contacts increase the speciﬁcity and stability of the regulatory complexes (combinatorial control). Dependent on the developmental stage and tissue type, or in response to environmental signals, speciﬁc sets of genes within the eukaryotic genomes are activated or repressed. This is achieved by assembling regulatory complexes containing various transcription factors bound to their cognate promoter/enhancer elements (Tjian and Maniatis, 1994; Singh, 1998; Merika and Thanos, 2001). Accordingly, activation or repression of a gene requires that all components of the ﬁnal complex are simultaneously available. The correct assembly of such DNA-bound (multiprotein) complexes often is assisted by architectural factors such as HMGA and HMGB proteins that can modulate DNA structure and/or contribute to the protein interactions within the complex. A proteomic approach identiﬁed novel protein interaction partners of HMGA including proteins related to chromatin remodelling and mRNA processing, which indicates that HMGA may serve (in addition to its role in transcript initiation) other functions in gene expression (Sgarra et al., 2005). The human virus-inducible IFN-β gene can serve as a model illustrating the role of HMGA in the regulation of gene expression (Merika and Thanos, 2001). The assembly of the multiprotein complex at the enhancer region of the IFN-β gene consisting of several transcription factors is assisted by DNA interactions of HMGA, which unbend an unfavourable intrinsic DNA curvature. Moreover, the

ARCHITECTURAL HMG PROTEINS

69

ﬁnal complex is stabilised by a complex network of mutual protein–protein interactions between activators and HMGA, resulting in a remarkable stable nucleoprotein structure (Yie et al., 1999). Dynamic control of IFN-β gene expression requires the regulated assembly and disassembly of the nucleoprotein structure, which is accomplished by differential acetylation of HMGA. Acetylation of HMGA at Lys65 by the acetyltransferase CBP destabilises the complex, whereas acetylation at Lys71 by PCAF/GCN5 potentiates transcription by stabilising the enhanceosome. Thus, the regulated acetylation of HMGA coordinates the transcriptional switch by causing either enhanceosome stabilisation or destabilisation (Munshi et al., 2001). Activation of the IFN-β gene is also accompanied by chromatin rearrangements in the promoter region allowing transcription initiation (Lomvardas and Thanos, 2002). There are several examples of an involvement of mammalian HMGA proteins in the formation of productive complexes initiating gene transcription (Reeves and Beckerbauer, 2001; Bianchi and Agresti, 2005). The role of HMGA in the regulation of transcription is to facilitate the DNA binding of transcription factors by inducing allosteric effects on DNA and/or by direct protein–protein interactions with the sequence-speciﬁc factors (Figure 3.6). Depending on the biological context and the developmental stage, HMGA proteins can regulate gene expression positively or negatively (Reeves and Beckerbauer, 2001; Bianchi and Agresti, 2005). In

Figure 3.6 Architectural function of HMGA and HMGB proteins in the formation of nucleoprotein structures (adapted from Grasser, 2003). Both HMGA and HMGB proved to be versatile and functionally ﬂexible proteins presumably involved in a variety of DNA-dependent processes including transcriptional initiation. Due to their abundance and mobility, HMG proteins bind the DNA randomly, eventually resulting in the formation of productive complexes. (A) Sequence-speciﬁc transcription factors may bind their target sites creating a transient DNA bend, which represents a high-afﬁnity binding site for HMG proteins. The DNA bending activity of the recruited HMG protein can stabilise the ﬁnal complex (without requirement of protein–protein interactions between the HMG protein and the transcription factor). (B) Alternatively, HMG proteins are speciﬁcally recruited by protein–protein interactions with sequence-speciﬁc regulators. Free or DNA-bound regulators can recruit the architectural HMGA or HMGB proteins. There may be different orders and mechanisms for HMG protein recruitment, and HMGs can interact only transiently to establish the complex, or they can be stable components of the assembly.

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electrophoretic mobility shift assays, the rice HMGA protein (termed PF1) could enhance (approximately tenfold) the binding of the transcriptional activator GT-2 to the phyA gene promoter. Since no direct physical contacts could be detected between HMGA and GT-2, the stimulation of GT-2 DNA binding was attributed to a preconditioning of the DNA target site by HMGA (Martinez-Garcia and Quail, 1999). In collaboration with transcription factors, the HMGB proteins contribute to the regulation of transcription initiation. The HMGB proteins can inﬂuence the formation of productive regulatory complexes at promoter or enhancer regions in two ways (Figure 3.6): (i) by direct protein interaction with transcription factor(s) facilitating their binding to DNA target sites, and/or (ii) by folding DNA target site (without protein interaction with transcription factors) into a suitable conformation stimulating the formation of the regulatory complex (Agresti and Bianchi, 2003; Grasser, 2003). The latter mechanism has been studied in detail using bacterial sitespeciﬁc recombination reactions as model systems, since HMGB proteins (without directly interacting with the recombinases) stimulate the assembly of productive synaptic complexes in these recombination reactions (Grosschedl, 1995). The correct three-dimensional assembly of the recombination complexes is facilitated by the DNA-bending activity of HMGB proteins. DNA bending is the primary determinant of the stimulatory effect, since HMGB proteins could substitute for other, even structurally unrelated bending proteins such as bacterial HU or IHF in promoting the recombination reactions (Grosschedl, 1995). Maize HMGB proteins can facilitate the site-speciﬁc β-recombination reaction in vitro and in vivo. Depending on the distance of the recombinase-binding sites on the DNA, the various maize HMGB proteins display different efﬁciency in stimulating β-recombination, indicating that the members of the HMGB family have different abilities to support the assembly of nucleoprotein structures (Stemmer et al., 2002a). Analogous to site-speciﬁc recombination, HMGB can be recruited to promoter regions without physical interactions with the transcription factors. In the case of the Epstein–Barr virus BHLF-1 promoter, ZEBRA transcription factors bind and bend the target DNA weakly, and this bent DNA represents a high-afﬁnity binding site for HMGB1. Thereby, HMGB1 is recruited to the promoter and stabilises the ﬁnal complex (Ellwood et al., 2000). At the BHLF-1 enhancer, HMGB1 displays a different mode of action. HMGB1 binds the target DNA only transiently to establish binding of two molecules of the viral activator Rta by a chaperone mechanism, and the DNA-bending activity of HMGB1 is the primary determinant of the stimulatory effect (Mitsouras et al., 2002). HMGB-induced DNA bending plays an important role also in the functional interaction of HMGB1 and p53. HMGB1 stimulates the binding of p53 to linear DNA, but not to pre-bent DNA (McKinney and Prives, 2002). In many instances, the HMGB proteins interact directly with transcription factors, stimulating the binding of the transcription factors to their speciﬁc DNA sites. HMGB proteins have been found to associate with a variety of transcription factors including members of the Rel, HOX, octamer and SREBP families as well as TFIID/TFIIA and steroid hormone receptors (Shykind et al., 1995; Zwilling et al., 1995; Zappavigna et al., 1996; Boonyaratanakornkit et al., 1998; Decoville et al., 2000; Najima et al., 2005). The protein–protein interactions with transcription factors explain how the

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non-sequence-speciﬁc HMGB proteins in these cases are recruited to their sites of action (Bustin, 1999; Thomas and Travers, 2001; Agresti and Bianchi, 2003; Grasser, 2003). Despite the interaction with certain transcription factors, the HMGB proteins are not always detectable in the ﬁnal ternary complex with DNA. Therefore, depending on the promoter/enhancer geometry and on the transcription factors involved, HMGB proteins may leave the assembly after initiating the formation of the transcription factor–DNA complex. In line with the dynamic movement of HMG proteins and other factors (see above) in the cell nucleus, a study of the interaction of HMGB1 and the glucocorticoid receptor (GR) revealed intriguing novel perspectives. HMGB1 and GR were found to interact only in the chromatin context, but not in the nucleoplasm, and the two partners decrease each other’s mobility favouring the formation of a productive complex at GR-binding sites (Agresti et al., 2005). In transient co-transformation experiments, maize HMGB1 can stimulate reporter gene expression in protoplasts (Grasser et al., 1993), and there are also a few examples of functional interactions of HMGB proteins and plant transcription factors. Thus, a wheat HMGB protein (termed HMGb, which is related to maize and rice HMGB1) can stimulate the binding of the bZIP transcription factor EmBP-1 to its DNA target site, whereas other tested HMGB proteins are not effective (Schultz et al., 1996). Maize HMGB1 interacts with the zinc-ﬁnger transcription factors Dof1 and Dof2 (through their Dof DNA-binding domain) and facilitates Dof DNA binding (Yanagisawa, 1997). The HMG-box domain of HMGB1 mediates the interaction and the individual domain is sufﬁcient for stimulating Dof2 DNA binding. Although all maize HMGB proteins can cooperate with Dof2, they do so with different efﬁcacy (Krohn et al., 2002). HMGB5 is clearly most effective and can stimulate the binding of maize Dof2 to its target site >30 fold in naked DNA. Maize HMGB5 also assists Dof2 DNA binding, when the Dof2 target site is assembled into nucleosome particles (Cavalar et al., 2003). Moreover, phosphorylation of HMGB1 and HMGB2/3 by protein kinase CK2 (see above) abolishes the functional interaction with Dof2 (Krohn et al., 2002). The widespread expression, the abundance and relative evolutionary conservation of the HMGA and HMGB proteins in (higher) eukaryotes indicate that they serve important cellular functions. This view is supported by studies of organisms with increased or decreased HMGA and HMGB levels displaying developmental defects and altered gene expression. Analyses of the role of HMGA and HMGB proteins in the formation of higher order nucleoprotein structures indicate that the HMGA and HMGB proteins as architectural factors assist speciﬁc transcriptional regulators, and contribute to proper control of transcript initiation. Upon stimulation through signal transduction pathways, the HMGA and HMGB proteins cooperate with sequencespeciﬁc transcription factors to form regulatory complexes, in which the synergy of multiple protein–DNA and protein–protein interactions provides the precision for the proper control of gene transcription in complex eukaryotic genomes. In contrast to the models involving an ordered stepwise assembly of regulatory complexes, future studies have to take into consideration recent ﬁndings demonstrating that HMG proteins and many other chromatin proteins are highly dynamic molecules in the cell nucleus (Bianchi and Agresti, 2005; Bustin et al., 2005; Gorski and Misteli, 2005).

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Acknowledgements Research in our laboratory has been supported primarily by grants from the Danish Research Council, and Dorte Launholt is recipient of a DBRA stipend.

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4 Histone modiﬁcations and transcription in plants Yii Leng Chua and John C. Gray

The N-terminal tails of histones H3 and H4 are modiﬁed post-translationally by acetylation and methylation. Acetylation of histones is reversible and dynamic, whereas histone methylation patterns persist through cell divisions, functioning as epigenetic memory. Plant histone acetyltransferases (HATs) and histone deacetylases (HDACs) regulate transcription of a wide range of genes, including genes that respond to environmental signals, and those that regulate development. Plants also have unique bromodomain (BRD) genes that control biological processes speciﬁc to plant physiology, such as seed germination and leaf morphogenesis. HATs, HDACs and BRD proteins modify growth patterns in response to a changing environment, and play important roles in adaptation, given the sessile nature of plants. HDACs play a central role in transcriptional control, because deacetylation of histones generally precedes histone methylation during gene silencing. Histone methylation by histone methyltransferases (HMTases) regulates spatial patterns of gene expression to specify organogenesis, genomic imprinting and ﬂowering time, and confer cell identity. We review the functions of various plant proteins that modify acetylation and methylation patterns of histones, and discuss the interplay between histone acetylation and methylation in transcriptional control in plants.

4.1

Introduction

Interphase chromatin is organised into nucleosomes (Figure 4.1A), which are composed of a linker histone, a histone octamer and 146 bp of DNA wound round the octamer in a 1.65 turn (reviewed by McGhee and Felsenfeld, 1980). The histone octamer contains two molecules each of the core histones H2A, H2B, H3 and H4, and is linked to the next nucleosome by linker DNA of variable length (Figure 4.1A) (Kornberg, 1974). The core histones possess a histone-fold domain and a basic Nterminal tail (Wolffe and Hayes, 1999). The histone-fold domain folds into three α-helices and interacts with the nucleosomal DNA (Figure 4.1B). Extending out of the nucleosome are the basic N-terminal tails of histones H2A, H2B, H3 and H4, and the basic C-termini of histone H2A (Luger et al., 1997). The N-terminal tails are modiﬁed by acetylation, methylation, phosphorylation, adenosine diphosphate (ADP)-ribosylation, ubiquitination and addition of small ubiquitin modiﬁer (SUMO). These post-translational covalent modiﬁcations regulate various cellular processes, such as transcription, DNA replication, chromatin assembly, doublestranded DNA break repair and cell division (Brownell and Allis, 1996; Strahl and Allis, 2000).

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Figure 4.1 Nucleosomes: (A) Schematic diagram of DNA organised into nucleosomes. DNA is wrapped around the histone octamer. The N-terminal tails of histones extend out of the nucleosomes. (Adapted from Luger, 2002.) (B) Schematic diagram of a nucleosome. Histones H3 (dark grey), H4 (black), H2A (light grey) and H2B (white) each fold into three α-helices. Positions of lysine residues in the N-termini of H3 and H4 are indicated by numbers. (Adapted from Luger, 2003.)

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Although the nucleosome structure was elucidated using avian and mammalian chromatin, the structure was later discovered to be highly conserved amongst yeasts, insects, plants and mammals (Bavykin et al., 1985). This suggests that the nucleosome is an extremely ancient macromolecule, which was formed before plants and animals diverged during evolution. Mutations that alter the nucleosome structure are likely to be lethal. Not only is the tertiary structure conserved, but the amino acid sequences of histones H3 and H4 are similar between different organisms (deLange et al., 1968; Patthy and Smith, 1973). For example, pea and calf thymus H4 differ at only two amino acids (Patthy and Smith, 1973). In particular, the amino acid sequences of the N-terminal tails of histones H3 and H4 are extremely conserved, and post-translational covalent modiﬁcations occur at the same lysine residues in different organisms (Figures 4.2A and 4.2B). Although the amino acid sequence of histone H2A is less conserved, the locations of lysine residues in the N-terminus that are subjected to post-translational modiﬁcations, are similar in different species (Figure 4.2C). In contrast, the N-terminal sequences of plant and animal histones

Figure 4.2 N-terminal sequences of histones: alignment of N-terminal sequences of human, Drosophila, yeast and Arabidopsis (A) histone H3, (B) histone H4 and (C) histone H2A. Lysine residues subjected to acetylation are numbered and labelled Ac.

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H2B are different, suggesting that post-translational modiﬁcations of histones H2B and their biological functions are likely to be different between plants and animals. Nucleosomes are often positioned on speciﬁc sequences along a gene (Simpson et al., 1993). Nucleosome positioning is deﬁned as the presence of a nucleosome on the same DNA sequence in all cells (Simpson et al., 1993). The nucleosomal DNA that wraps round the histone octamer in an 80 base-pair circle is distorted, containing sharp kinks in the double helix (Richmond et al., 1984; Luger et al., 1997). Thus, DNA sequences that encourage nucleosome positioning are often A/T-rich, with a propensity to curve (Richmond et al., 1984; Kornberg and Lorch, 1999). Promoter and enhancer regions are A/T-rich, and nucleosomes are often positioned on these regulatory sequences (Laybourn and Kadonaga, 1991; Workman and Kingston, 1998). The presence of nucleosomes on promoters and enhancers is generally inhibitory to transcription, because nucleosomal DNA is not available for binding to transcription activators and assembly of the RNA polymerase machinery. Inhibition is most effective when the recognition sequences are present at the pseudodyad (centre) than at the edge of the nucleosomes (Xu et al., 1998). In plants, nucleosomes are selectively positioned on the promoter of the β-phaseolin gene when the gene is inactive (Li et al., 1998, 1999). Nucleosomes also inhibit the interaction of the wheat transcription factor EmBP-1 with its recognition site in vitro (Niu et al., 1996). Interphase chromatin is also organised into euchromatin and heterochromatin. By deﬁnition, euchromatin is the chromatin that stains poorly with DNA-staining dyes, whereas heterochromatin stains deeply (Pardue and Hennig, 1990). Euchromatin consists of regions of the genome that are transcriptionally competent and possess an open chromatin structure. An open chromatin structure is currently thought to consist of DNA with widely spaced nucleosomes containing acetylated histones, and is organised into loops of 200–2000 kb, with the bases of the loops attached to a nuclear scaffold (Heslop-Harrison, 2003). In contrast, heterochromatin is highly condensed, is replicated late in S-phase and is inaccessible to transcription (Maison and Almouzni, 2004). The organisation of nucleosomal DNA into heterochromatin is poorly understood (Wolffe, 1995). Heterochromatic regions are also referred to as chromocentres. In Arabidopsis, there are nine chromocentres, consisting of centromeric regions of the ﬁve chromosomes, and four regions of ribosomal RNA (rRNA) genes (Heslop-Harrison, 2003). Gene-silencing consequent of heterochromatin formation is observed in X-chromosome inactivation in mammals (Jeppesen and Turner, 1993), position-effect variegation in Drosophila (Reuter and Spierer, 1992) and telomeric silencing in yeast and mammals (Perrod and Gasser, 2003). In plants, heterochromatin formation is involved in silencing of transposons (Lippman and Martienssen, 2004), and repression of rRNA genes in nucleolar dominance (Lawrence et al., 2004). The most well-studied post-translational modiﬁcations in plants are acetylation and methylation of the N-terminal tails of histones H3 and H4. These modiﬁcations regulate transcription by facilitating mobilisation of nucleosomes from promoters, recruiting transcription factors, or by regulating formation of euchromatin or heterochromatin. In contrast, very little is known about the functions of ADPribosylation, ubiquitination and SUMOylation of histones in plants. Phosphorylation

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of histones regulates DNA replication and cell division in plants (Houben et al., 2005), and is beyond the scope of this chapter. This review focuses on histone acetylation and methylation, and their roles in regulation of transcription. We ﬁrst give an overview of the functions of plant chromosomal proteins that regulate acetylation and methylation of histones, and the transcription factors that recognise these posttranslational modiﬁcations. We then discuss how histone acetylation and methylation may act in conjunction to regulate transcription in plants.

4.2

Histone acetylation and transcriptional activation

Acetylation of histones involves the transfer of acetyl (—COCH3 ) groups from acetyl-coenzyme A to the ε-amino groups of lysine residues K4, K9, K14, K18 or K23 of histone H3, or lysine residues K5, K8, K12 K16 or K20 of histone H4 by histone acetyltransferases (HATs) (Figure 4.2) (Lin et al., 1999; Rojas et al., 1999). Addition of the acetyl group results in loss of positive charge at the lysine side chain (Figure 4.3), abolishing interactions between the positively charged histone tails and the negatively charged DNA (McGhee and Felsenfeld, 1980; Cary et al., 1982). Acetylation of histone tails is generally correlated with activated transcription in yeasts, animals and plants. One of the earliest experiments indicating transcriptional activation by acetylation of histones in plants is the study of nucleolar dominance, a phenomenon where one parental set of rRNA genes is silenced in an interspeciﬁc hybrid (Chen and Pikaard, 1997). Brassica napus is a hybrid between Brassica

Figure 4.3 Acetylation of a lysine residue. Acetylation involves addition of —COCH3 to the ε-amino group of a lysine residue.

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oleracea and Brassica rapa. In B. napus, rRNA genes that are inherited from B. oleracea are silenced. Treatment of B. napus with trichostatin A or sodium butyrate, which are potent inhibitors of histone deacetylases (HDACs), increased histone acetylation levels and activated expression of B. oleracea rRNA genes (Chen and Pikaard, 1997). This suggests that rRNA genes are silenced by HDACs in nucleolar dominance (Chen and Pikaard, 1997). Subsequently, chromatin immunoprecipitation experiments showed that acetylated histones H3 and H4 were present on the promoter and enhancer regions of the actively transcribed plastocyanin gene (PetE) in green pea shoots, whereas these regions were associated with non-acetylated histones in etiolated shoots and roots, which had low PetE transcription (Chua et al., 2001). Interestingly, histone H3 acetylation levels at regions upstream of the enhancer, and at the coding region, remained unchanged during activation of PetE transcription (Chua et al., 2001). This indicates that acetylation of histones is targeted to speciﬁc nucleosomes present on important regulatory sequences during transcriptional activation (Chua et al., 2001). In transgenic tobacco plants containing the β-glucuronidase (GUS) reporter gene fused to the PetE promoter, treatment with trichostatin A and sodium butyrate increased histone acetylation levels at the promoter of the transgene and activated expression, indicating that acetylation of histones has a direct positive effect on transcription in plants (Chua et al., 2003). Unlike histone methylation, which activates or represses transcription depending on the lysine residue that is modiﬁed, transcriptional activation is generally correlated with acetylation of various lysine residues, such as K5, K8, K12 and K16 of histone H4, and K9 and K14 of histone H3 (Braunstein et al., 1996; Osano and Ono, 2003). Early biochemical studies suggested that acetylation of histones may increase transcription by altering the physical structure of chromatin to facilitate entry of transcription factors (Lee et al., 1993). Structural changes in chromatin may occur in the following ways: (1) acetylation of lysine residues neutralises the positive charges of histones, weakens histone–DNA contacts and facilitates the displacement of nucleosomes by transcription factors (McGhee and Felsenfeld, 1980; Cary et al., 1982; Puig et al., 1998); (2) acetylation also weakens nucleosome interconnections, inhibits formation of condensed chromatin and, hence, increases the accessibility of DNA recognition sequences to transcription factors (Luger et al., 1997; Mutskov et al., 1998; Tse et al., 1998); (3) histone acetylation changes the conformation of nucleosomal arrays by affecting the DNA path around nucleosomes, and releasing negative supercoils present in chromatin, thereby facilitating interactions of protein factors with chromatin (Norton et al., 1989; Bauer et al., 1994). In addition to altering chromatin structure, acetylation of histones may have a signalling function. The histone-code hypothesis proposes that post-translational modiﬁcations of histones provide heritable epigenetic information that speciﬁes alternative states of chromatin to regulate cellular processes such as transcription and replication (Strahl and Allis, 2000). Acetylated histones may specify an activated transcriptional state by signalling to transcriptional activators or co-activators (Strahl and Allis, 2000). In support of this hypothesis is the observation that various transcriptional activators and co-activators contain the bromodomain (BRD) motif,

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which interacts with acetylated histone tails, and are directed to actively transcribed genes (see Section 4.2.2). It is plausible that acetylation of histones has both a structural effect and a signalling function. Nonetheless, it is interesting that acetylation has evolved to be the post-translational modiﬁcation that marks activated transcription, because it would be thermodynamically less favourable for deacetylation to specify an open chromatin structure and an activated transcriptional state, due to the physical properties of histone tails and DNA. Acetylation of histone tails is associated with activated transcription, with the exception of a small group of genes in yeasts and mammals (Montecino et al., 1999; Deckert and Struhl, 2001; Sheldon et al., 2001; Ricci et al., 2002). Continuous high histone acetylation levels at these genes has a negative effect on transcription, because deacetylation is required to convert these genes back to their original chromatin structures following transcription (Kurdistani and Grunstein, 2003). The original chromatin structures are necessary for binding of sequence-speciﬁc transcription factors for the next round of transcription initiation (Kurdistani and Grunstein, 2003). Thus, for some genes, activated transcription is regulated by a dynamic cycle of histone acetylation and deacetylation (Kurdistani and Grunstein, 2003). Acetylation of histones is also correlated with DNA replication and cell-cycle progression in plants (Jasencakova et al., 2000; Wako et al., 2002). DNA replication is associated with an increase in histone H4 acetylation levels over large domains of euchromatin and heterochromatin (Jasencakova et al., 2000, 2001). In contrast, changes in histone acetylation levels associated with transcription are targeted to speciﬁc nucleosomes on promoters, enhancers and/or coding regions of plant genes (Chua et al., 2001, 2004). In addition, whereas acetylation of various lysine residues in histones H3 and H4 is generally correlated with increased transcription, replication and mitosis are associated with changes in acetylation at lysine residues K5, K8, K12 or K16 of histone H4 (Jasencakova et al., 2000, 2001; Wako et al., 2002). The acetylation levels of histone H3 remain largely invariant during DNA replication and cell-cycle progression (Jasencakova et al., 2000, 2001).

4.2.1

Plant histone acetyltransferases

HATs are classiﬁed on the basis of sequence homology into four families (Sterner and Berger, 2000): the GNAT/MYST superfamily consisting of the General Control Non-repressed protein 5-related AcetylTransferases (GNATs), and the ‘MOZ, Ybf2, Sas2 and Tip60’-related HATs (MYSTs); the p300/CBP family consisting of the p300/cAMP-response element-binding (CREB) protein-related HATs; the TAFII 250 family; and the SRC3 family consisting of ‘SRC1 and ACTR’related HATs. Arabidopsis, rice and maize have genes encoding homologues of GNAT/MYST-, p300/CBP- and TAFII 250-type HATs, but not SRC3-type HATs, which are involved in nuclear hormone signalling in animal cells, suggesting that this pathway is likely to be non-existent in plants (Loidl, 2004). There are many genes encoding HATs in plants: 16 in Arabidopsis and 8 in rice (Plant Chromatin Database, http://www.chromdb.org/).

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Analysis of HAT mutants in Arabidopsis indicates that acetylation of histones plays a central role in transcriptional activation of many genes, such as cold-response, light-induced and pathogen-induced genes, and regulates various aspects of plant development, including ﬂoral organogenesis, leaf morphogenesis, root development and ﬂowering time (Bertrand et al., 2003; Vlachonasios et al., 2003). Microarray analysis of chromatin-immunoprecipitated DNA by antibodies that recognise acetylated histone H4 tails indicates that histone acetylation is targeted to promoters of diverse sets of genes involved in photosynthesis, pathogen response, stress response and tissue-speciﬁc gene expression (Chua et al., 2004). Thus, acetylation of histones is a general mechanism that regulates transcription of a wide range of genes in plants.

4.2.1.1

GNAT/MYST family

The GNAT family is characterised by the acetyltrnsf 1 motif (Pfam accession: PF00583), an 80 amino acid residue consensus that binds to acetyl-coenzyme A. Plant GNAT-type HATs also possess BRDs that interact with acetylated histones, and also contain the radical S-adenosylmethionine (SAM) motif (Pfam accession: PF04055), which binds to an iron ion, and generates radical species by cleavage of SAM. There are three genes encoding GNAT-type HATs in Arabidopsis (HAG1, HAG2 and HAG3), and in rice (HAG702, HAG703 and HAG704) (Plant Chromatin Database). Yeast and Drosophila GNAT-type HAT GCN5 (General Control Non-repressed protein 5) proteins function as part of a multiprotein complex to regulate gene expression by acetylation of histones; they associate with Alteration/Deﬁciency in Activation (ADA) co-activators to form the Spt/Ada/GCN5 Acetyltransferase (SAGA) and ADA HAT complexes (Grant et al., 1997; Kusch et al., 2003). Plant GCN5 homologues are also part of multiprotein HAT complexes. For example, Arabidopsis HAG1 interacts with Arabidopsis homologues of ADA co-activators, ADA2a and ADA2b, to control expression of cold-regulated genes that contain CRT/DRE (C-repeat/dehydration-responsive) regulatory sequences (Stockinger et al., 2001). Recruitment of HAG1 to cold-regulated genes is likely to be mediated by CBF1, a transcription factor that binds to CRT/DRE (Stockinger et al., 2001). The maize ZmGCN5 also interacts with the maize homologue of ADA co-activator ZmADA2, and associates with the bZIP transcription factor OPAQUE2 to regulate gene expression (Bhat et al., 2003, 2004). Although puriﬁed recombinant HAG1 or ZmGCN5 acetylate free histones in vitro (Bhat et al., 2003), the associated ADA factors are likely to be required for acetylating histone tails in a chromatin template and for regulating substrate speciﬁcity (Balasubramanian et al., 2002). T-DNA insertional mutations in Arabidopsis HAG1 or ARADA2b reduced activation of cold-regulated genes by cold treatment (Vlachonasios et al., 2003). The observation that the expression of cold-regulated genes is not totally abolished in the mutants suggests that HAG1 controls activation but not initiation of transcription. In addition, HAG1 also regulates various aspects of plant development; HAG1 mutants have reduced root growth, smaller rosettes, curled leaves, smaller and fewer siliques, and homeotic transformation of petals into stamens, and sepals into needlelike structures (Bertrand et al., 2003; Vlachonasios et al., 2003). The ﬂoral homeotic

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transformations are due to activation of WUSCHEL (WUS) and AGAMOUS (AG) in the outer whorls of the ﬂower, suggesting that HAG1 regulates ﬂoral organogenesis through the WUS/AG pathway (Bertrand et al., 2003). The plant MYST family of HATs contains the MOZ SAS domain (Pfam accession: PF01853) and zinc ﬁngers. In yeast and mammals, MYST-type HATs regulate a wide range of cellular processes, including gene expression, chromatin assembly and double-stranded DNA break repair (Osada et al., 2001; Bird et al., 2002; Gomez et al., 2005). Two genes encoding MYST-type HATs (HAM1, HAM2) have been predicted for Arabidopsis, and one (HAM701) for rice (Plant Chromatin Database). The functions of these genes have not yet been investigated.

4.2.1.2

TAF I I 250 family

The TAFII 250 family of HATs associates with the TATA-box binding protein (TBP), which is a component of the basal transcription complex (Ruppert et al., 1993). TAFII 250 possesses a HAT catalytic domain of 260 amino acid residues, and activates transcription through acetylation of histones (Mizzen et al., 1996). There are two Arabidopsis TAFII 250 genes (HAF1 and HAF2), and one rice gene (HAF701) (Plant Chromatin Database). Plant HAF proteins also possess BRDs. Arabidopsis HAF2 regulates expression of photosynthesis genes. T-DNA insertion mutations in HAF2 led to reduced chlorophyll levels, and downregulation of light-responsive genes, such as LHCB1 and RBCS1A (Bertrand et al., 2005). Moreover, histone H3 acetylation levels at the promoters of LHCB1 and RBCS1A are decreased in HAF2, as demonstrated by chromatin immunoprecipitation experiments, indicating that HAF2 regulates transcription by acetylation of histones (Bertrand et al., 2005). These results are consistent with the observation that acetylation of histones is a key mechanism that activates expression of the photosynthesis gene PetE in light (Chua et al., 2001). Interestingly, mutations in HAF1 do not have phenotypes similar to HAF2, suggesting that the downstream genes regulated by the two HAF transcription factors are different (Bertrand et al., 2005). Analysis of Arabidopsis det1 (de-etiolated1) also suggests that HATs play important roles in regulating expression of light-induced genes (Benvenuto et al., 2002; Schroeder et al., 2002). Seedlings grown in the dark are characterised by long hypocotyls, closed and yellow cotyledons, and have low expression of photosynthesis genes, whereas light-grown seedlings have short hypocotyls, and green and expanded cotyledons. When grown in the dark, det1 has activated expression of photosynthesis genes and morphologies similar to light-grown seedlings, suggesting DET1 is involved in repression of light-induced genes. DET1 is a nuclear protein that binds to non-acetylated tails of histone H2B in dark-grown plants (Benvenuto et al., 2002). Following illumination, DET1 associates with UV-DDB1 (UV-Damaged DNA-Binding Protein 1), which consequently recruits HATs, leading to acetylation of histones and activated expression of light-induced genes (Schroeder et al., 2002).

4.2.1.3

P300/CBP family

The p300/CBP family of HATs possesses the CBP-type HAT domain, which contains the plant homeodomain (PHD) motif and a putative acetyl-coenzyme A-binding

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motif (Yuan and Giordano, 2002). Arabidopsis has ﬁve genes encoding p300/CBPtype HATs: HAC1, HAC2, HAC4, HAC5 and HAC12 (Plant Chromatin Database). Arabidopsis HAC1 (also known as PCAT2) acetylated histones in vitro, and activated gene expression when it was targeted to promoters of reporter genes in human cell lines (Bordoli et al., 2001). Mutants of HAT genes in this family have not been characterised, and the downstream genes regulated by p300/CBP-type HATs have not been investigated. Although acetylation of histones is a general mechanism that upregulates expression of many plant genes, speciﬁcity in gene regulation is likely to be mediated by different types of HATs. Different families of HATs regulate different aspects of plant physiology; for example, the Arabidopsis GNAT-type HAT HAG1 regulates cold-response genes, whereas the TAFII 250 protein HAF2 controls expression of light-response genes (Vlachonasios et al., 2003; Bertrand et al., 2005). In addition, different members of the same family appear to have distinct functions, indicating that they are recruited to different groups of downstream genes (Bertrand et al., 2005). Moreover, plant HATs function in multiprotein complexes. Thus, each HAT can associate with different sequence-speciﬁc transcription factors to regulate groups of genes independently and in a coordinated manner. In yeast and mammals, HATs also regulate transcription by acetylating transcription factors such as p53 and high mobility group (HMG) proteins in addition to histones (Bode and Dong, 2004; Edberg et al., 2004). Future work may indicate whether plant HATs also control transcription by modifying transcription factors.

4.2.2

Bromodomain proteins

Acetylated histones H3 and H4 regulate transcription through interaction with the BRD (Pfam accession: PF00439), a 110 amino acid residue motif that binds acetyllysine side chains, and is present in various yeast, mammalian and plant transcription factors (Jeanmougin et al., 1997). The BRD of the human p300/CBP-associated factor (PCAF) was ﬁrst demonstrated to interact with acetylated lysines in histone H3 peptides in vitro, by nuclear magnetic resonance spectroscopy (Dhalluin et al., 1999). Subsequently, the BRD was shown to bind selectively to acetylated histones in vivo by ﬂuorescence resonance energy transfer assays (Kanno et al., 2004). The BRD folds into a four-helical bundle with two loops at each end, forming a hydrophobic pocket that selectively ﬁts the non-charged side chain of an acetylated lysine residue, and not the positively charged side chain of an unmodiﬁed lysine residue (Owen et al., 2000). The BRD functions as a targeting module for various transcription factors. BRDs activate transcription by anchoring HATs to promoters of actively transcribed genes. The BRD motif is present in various plant HATs, including Arabidopsis HAG1, HAF1 and HAF2, maize HAF101 and HAG101 and rice HAF701 and HAG702. HATs are initially recruited to genes by sequence-speciﬁc transcription factors that recognise promoter sequences (Hassan et al., 2001, 2002). Following acetylation of histone tails, HATs are then tethered to acetylated histones through their BRDs, and remain associated with the promoter in the absence of sequence-speciﬁc

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transcription factors (Hassan et al., 2001, 2002). Stable promoter occupancy by HATs maintains high histone acetylation status, and activated transcription. BRDs are also present in chromatin-remodelling proteins such as CHROMATIN REMODELLING COMPLEX SUBUNIT R (CHR) 2 in Arabidopsis, and CHR707 in rice. CHR is the ATPase component of the Sucrose Non-Fermenting 2 (SNF2) family of proteins, which disrupt histone–DNA contacts and mobilise nucleosomes. Chromatin-remodelling proteins may thus be recruited to actively transcribed genes through BRDs. Bromodomains also bind to acetyl-lysine side chains in other proteins such as p53, C-Myb and MyoD, and may regulate transcription through interactions with transcription factors (Yang, 2004).

4.2.2.1

Bromodomain extra-terminal proteins

In yeast and mammals, the Bromodomain Extra-Terminal (BET) family of proteins possesses BRDs and an ET domain, and regulates cell proliferation and growth (Chua and Roeder, 1995; Houzelstein et al., 2002). There are 12 Arabidopsis and 10 rice genes encoding BET-like proteins (Plant Chromatin Database). These genes are designated GENERAL TRANSCRIPTION FACTOR GROUP E (GTE). Unlike yeast and mammalian BET proteins, which have two BRDs, plant GTE proteins contain one BRD. Moreover, many plant GTE genes encode only the N-terminus of the ET domain, the NET domain, and not the serine-rich C-terminus, which is known as the SEED domain (Florence and Faller, 2001). The functions of the ET domain have not been elucidated, but the motif has been proposed to be involved in protein–protein interactions (Lygerou et al., 1994). Arabidopsis GTE1 and GTE6 regulate different aspect of plant development, possibly because they are targeted to different downstream genes. GTE1 is involved in regulation of seed germination by light and abscisic acid (ABA) (Duque and Chua, 2003). Inactivation of GTE1 by a T-DNA insertion resulted in repression of a broad class of genes, including genes encoding proteins involved in cell wall formation, plastid transcription and translation, and lipid metabolism, suggesting that GTE1 functions as a general transcriptional activator (Duque and Chua, 2003). GTE6 controls leaf patterning during juvenile-to-adult transition in Arabidopsis (Chua et al., 2005). In many plant species, the transition from the juvenile to the mature phase is characterised by changes in leaf structure (Kerstetter and Poethig, 1998). In Arabidopsis, juvenile leaves possess round laminae, whereas mature leaves have elliptical laminae (Lawson and Poethig, 1995; Theodoris et al., 2003). GTE6 regulates the development of elliptical leaf shapes in mature plants by activating transcription of the myb-domain gene ASYMMETRIC LEAVES1 (AS1). GTE6 associates with the promoter and the ﬁrst exon of the gene, and activates transcription through acetylation of histones (Chua et al., 2005). AS1 in turn controls proximodistal patterning of leaves by repressing transcription of the KNOX genes KNAT1 and KNAT2 (Byrne et al., 2002; Theodoris et al., 2003). Although GTE1 and GTE6 have no HAT domains, they may activate transcription through acetylation of histones by interacting with HATs (Hassan et al., 2001). Alternatively, they may activate transcription by binding to acetylated histone tails and shielding them from the actions of HDACs (Ladurner et al., 2003). Interestingly,

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a tomato BET protein, VIRP1, binds to potato spindle tuber viroid RNA in the nuclei of infected leaves (Martinez de Alba et al., 2003). Because VIRP1 binds to RNA and is localised to the nucleus, it may be involved in RNA-mediated DNA methylation and gene silencing, or transportation of RNA to the nucleus (Martinez de Alba et al., 2003).

4.2.2.2

Plant bromodomain proteins

There are six Arabidopsis genes that encode proteins possessing a single BRD in conjunction with other functional motifs such as the ATPase AAA domain (BRD8), the Myb-like DNA-binding domain (BRD3, 4, 6 and 9) and WD-40 repeats (BRD11 and 12). Arabidopsis BRD1, 2, 5, 7, 10 and 13 encode proteins containing only one BRD. The functions of these plant BRD proteins have not been elucidated, and they may regulate transcription or cellular processes such as replication, cell cycle and protein degradation by associating with acetyl-lysine side chains in histones and other proteins.

4.2.3

Plant histone deacetylases

Opposing the activities of HATs are the histone deacetylases (HDACs), which remove acetyl groups from acetylated lysine residues (Taunton et al., 1996; Rundlett et al., 1998). HATs and HDACs act in conjunction to regulate global histone acetylation levels, and local histone acetylation at regulatory sequences of genes (Kurdistani and Grunstein, 2003). A total number of 18 HDACs has been predicted from the genome sequences of Arabidopsis and rice (Pandey et al., 2002). Plant HDACs are classiﬁed on the basis of sequence similarity into three families: the Reduced Potassium Deﬁciency 3/Histone Deacetylase 1 (RPD3/HDA1) family, the Histone Deacetylase 2 (HD2) family and the Silent Information Regulator 2 (SIR2) family.

4.2.3.1

RPD3/HDA1 family

The RPD3/HDA1 family of HDACs is characterised by the histone deacetylase domain, which spans over 300 amino acid residues (Pfam accession: PF00850). There are 12 genes encoding RPD3/HDA1-type HDACs in Arabidopsis, and 14 in rice (Plant Chromatin Database). Plant RPD3/HDA1-type HDACs function as part of multiprotein complexes, and are targeted to speciﬁc genes by co-repressors. For example, maize ZmRPD3I associates with ZmRBR1, the maize homologue of Retinoblastoma-Related (RBR), and with ZmRbAp1, a maize MSI/RbAp corepressor protein, to downregulate transcription (Rossi et al., 2003). Amongst the 12 genes encoding Arabidopsis RPD3/HDA1-type HDACs, HDA19 (also known as AtRPD3A or OOK) and HDA6 (also known as ATRPD3B) have been well investigated. HDA19 repressed transcription when it was directed to promoters of reporter genes in transient expression assays (Wu et al., 2000a). Chromatin immunoprecipitation experiments indicated that activated genes in HDA19 null mutants possessed increased histone acetylation levels, suggesting that HDA19 repressed gene expression by deacetylation of histones (Tian et al., 2005). Downregulation of HDA19 by antisense constructs and T-DNA insertions in Arabidopsis

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increased global histone acetylation levels, and had pleiotropic effects on plant development; plants had serrated and elongated leaves, ﬂoral homeotic transformations, reduced fertility and were late ﬂowering (Wu et al., 2000a; Tian and Chen, 2001; Tian et al., 2003). In HDA19 null mutants, almost 360 ﬂower-speciﬁc genes such as SUPERMAN were activated in leaves, and 80 leaf-speciﬁc genes were expressed in ﬂowers, indicating that HDA19 regulated tissue-speciﬁc gene expression (Tian et al., 2005). In rice, over-expression of OsHDAC1 results in increased growth rate, altered leaf structure and elongated roots, suggesting that RPD2/HDA-type HDACs also regulate growth and plant development in monocots (Jang et al., 2003). Arabidopsis HDA19 also plays a central role in pathogen and stress responses (Song et al., 2005; Zhou et al., 2005). HDA19 is activated following wounding, pathogen invasion and treatment with jasmonic acid or ethylene (Zhou et al., 2005). Plants over-expressing HDA19 were more resistant to pathogen invasion, and possessed increased expression of ETHYLENE RESPONSE FACTOR1 (ERF1) and PATHOGENESIS-RELATED (PR) genes encoding basic chitinase and b-1,3glucanase (Zhou et al., 2005). HDA19 also regulates gene expression in response to ABA, which accumulates in plants during drought, cold and salt stress (Song et al., 2005). HDA19 associates with the co-repressor AtSin3, and with an APETALA2/EREBP-type transcription factor AtERF7, to repress transcription of ABA-regulated genes that contain ethylene-response elements (Song et al., 2005). Apart from deacetylating histones, HDA19 may also regulate gene expression by interacting with transcription activators. In B. napus, cold treatment upregulates the expression of BnKCP1, which encodes a transcription activator containing a putative kinase-inducible domain (Gao et al., 2003). BnKCP1 associates with HDA19 to regulate expression of reporter genes (Gao et al., 2003). HDA19 also interacts with another transcription activator SCARECROW-like to control plant development (Gao et al., 2004). It is likely that HDA19 represses transcription through another mechanism, i.e. by sequestering transcriptional activators. Alternatively, activators may be expressed in a cell-speciﬁc manner to prevent or relieve repression of gene expression by HDA19 in certain tissues (Gao et al., 2004). Arabidopsis HDA6 is also a repressor of transcription. However, downregulation of HDA6 did not result in global changes in histone acetylation levels, but only increased histone H4 acetylation levels at certain regions of the genome, suggesting that HDA6 is not a general transcriptional repressor like HDA19 (Probst et al., 2004). Mutations in HDA6 resulted in reactivation of silenced transgenes and transposons, indicating that HDA6 is involved in maintaining gene silencing (Murfett et al., 2001; Aufsatz et al., 2002). HDA6 functions in conjunction with DNA methyltransferases, DDM1 and MET1, in RNAi-mediated gene silencing of transposons (Lippman et al., 2003). Thus, mutations in HDA6 also lead to decreased or modiﬁed DNA methylation patterns at rRNA repeats and transposons (Aufsatz et al., 2002; Lippman et al., 2003). The phenotypes of HDA6 mutants are different from HDA19; HDA6 mutants are late ﬂowering and do not possess altered morphology or growth patterns. Thus, the downstream target genes of HDA19 and HDA6 are likely to be different.

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4.2.3.2

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HD2 family

The HD2 family of HDACs is unique to plants, and is absent from mammals or fungi (Lusser et al., 1997; Pandey et al., 2002). Arabidopsis has four HD2-type HDAC genes, namely HDT1, HDT2, HDT3 and HDT4, and rice has two, HDT701 and HDT702. HD2-type HDACs are characterised by a nucleoplasmin motif (Pfam accession: PF03066). Nucleoplasmins are chromatin de-condensation proteins that regulate histone–DNA interactions (Earnshaw et al., 1980). HDT1, HDT2 and HDT701 also possess C2H2-type zinc ﬁngers (Pfam accession: PF00096) for interactions with DNA. HD2 was ﬁrst described as a nucleolar acid phosphoprotein with histone deacetylation activity in maize (Lusser et al., 1997). In Arabidopsis, HDT1, HDT2 and HDT3 localise to the nucleus, and repress gene expression when they are targeted to promoters of reporter genes (Wu et al., 2003; Zhou et al., 2004). Downregulation of HDT1 by an antisense construct, or expression of HDT1-GFP fusions, leads to aborted seeds in Arabidopsis (Wu et al., 2000b; Zhou et al., 2004). Expression of LATE EMBRYOGENESIS-ABUNDANT PROTEIN (LEA), SEED MATURATION PROTEIN and ABSCISIC ACID-RESPONSIVE ELEMENTS-BINDING FACTOR3 was misregulated in HDT1 mutants, indicating that HDT1 is a master regulatory gene that controls embryogenesis and/or endosperm development (Zhou et al., 2004). Arabidopsis HDT1 also regulates silencing of rRNA genes in nucleolar dominance (Lawrence et al., 2004). In Arabidopsis suecica, which is a hybrid between Arabidopsis thaliana and Arabidopsis arenosa, rRNA genes that are inherited from A. thaliana are silent, whereas rRNA genes derived from A. arenosa are expressed. Downregulation of HDT1 by RNAi leads to loss of DNA methylation, increased levels of trimethylated K4 in histone H3 and reduced levels of dimethylated K9 in histone H3 at A. thaliana rRNA genes, leading to gene expression and loss of nucleolar dominance (Lawrence et al., 2004). Trimethylated K4 in histone H3 is a hallmark of euchromatin, whereas dimethylated K9 in histone H3 is associated with transcriptionally repressed heterochromatin (Lawrence et al., 2004). HDT1 thus plays a central role in maintaining rRNA genes in a repressive chromatin structure by deacetylating amino acid residue K9 of histone H3, which consequently becomes available for methylation (Lawrence et al., 2004). Downregulation of HDT3 or HDT4 by RNAi does not affect nucleolar dominance in Arabidopsis, suggesting that nucleolar dominance is regulated speciﬁcally by HDT1, and not by the other members of the HD2 family (Lawrence et al., 2004).

4.2.3.3

SIR2 family

The SIR2 family consists of NADH-dependent HDACs, which are characterised by a SIR2-type HDAC domain (Pfam accession: PF02146). There are two genes encoding SIR2-type HDACs in Arabidopsis (HDA12 and HDA14), and two genes in rice (HDA701 and HDA702). Inhibition of SIR2-type HDACs in Arabidopsis by compounds containing the hydroxynaphthaldehyde moiety led to altered leaf structures and perturbation of body axis (Grozinger et al., 2001). In addition, the inhibitors prevented the formation of the vascular system in seedlings (Grozinger et al., 2001).

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SIR2-type HDACs regulate growth and development in plants (Grozinger et al., 2001).

4.2.4

Histone acetylation/deacetylation and environmental adaptation

Acetylation of histones is an important mechanism that regulates the expression of genes that respond to external stimuli such as cold, light and pathogens. Due to the reversible nature of histone acetylation, genes can be rapidly activated in the presence of an external stimulus by acetylation of histones, and then subsequently repressed by histone deacetylation when the stimulus ceases. Transcription by RNA polymerase II is a complex process; the TBP binds weakly to promoter sequences, and requires sequence-speciﬁc transcription factors along with a host of general transcription factors to be assembled into a functional RNA polymerase II machinery (Kadonaga, 1998). Following acetylation of histones, HATs and BRD-containing activators are directed to promoters, surpassing the requirement for ordered recruitment of sequence-speciﬁc transcription factors (Agalioti et al., 2000; Hassan et al., 2002). Moreover, because histone acetylation is a common mechanism that activates transcription, HATs and BRD-containing activators can be shared amongst different genes. In this way, the cell does not have to increase the amounts of sequence-speciﬁc transcription factors for each individual activated gene. Histone acetylation is thus an efﬁcient mechanism that maintains high transcription rates of many activated genes concurrently. Once the external stimulus ceases, deacetylation of histones occurs, and transcription is decreased, as HATs and co-activators are no longer recruited. Histone acetylation/deacetylation is a ﬂexible regulatory mechanism, which allows plants to respond rapidly to a changing environment. Plants are sessile organisms and adapt to a changing environment by modifying their growth patterns. In Arabidopsis, maize and rice, HATs, HDACs and BRD proteins modify plant development such as rate of growth, leaf morphogenesis, root growth, ﬂowering and seed development (see Sections 4.2.1–4.2.3). In addition, HATs and HDACs regulate the expression of many developmental genes in response to plant hormones, which are produced during abiotic and biotic stress. HATs and HDACs thus play central roles in adaptation to the environment, because they modify many aspects of plant development in response to external stimuli.

4.3

Histone methylation

Histones H3 and H4 are also modiﬁed by methylation, which involves the addition of methyl (—CH3 ) groups to the ε-amino groups of lysine residues by HMTases. Unlike acetylation, where only one acetyl group is added, the ε-amino group of lysine residues can be mono-, di- or trimethylated (Figure 4.4). Methylation of amino acid residues K4, K36 and K79 of histone H3 is generally associated with transcriptional activation, whereas methylation of amino acid residues K9 and K27 of histone H3 and K20 of histone H4 is correlated with heterochromatin formation and gene silencing (Bannister and Kouzarides, 2005; Lee et al., 2005). Because

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Figure 4.4 Methylation of a lysine residue. Chemical structure of lysine, monomethyl-lysine, dimethyl-lysine and trimethyl-lysine residues.

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methylation does not result in charge neutralisation of lysines, and the addition of a small methyl group is not likely to alter the physical structure of chromatin, histone methylation regulates transcription by recruiting transcription factors (Strahl and Allis, 2000). Moreover, mono-, di- and trimethylation have different effects on gene regulation, possibly because modiﬁed lysine residues are recognised by different groups of proteins. For example, in Chlamydomonas, dimethylated K4 in histone H3 is correlated with transcription in euchromatin, whereas monomethylated K4 in histone H3 is associated with non-transcribed genes (van Dijk et al., 2005). In plants, methylation of H3K9 plays an important role in silencing the expression of the ﬂowering repressor gene FLC (FLOWERING LOCUSC) during vernalisation, leading to early ﬂowering (Bastow et al., 2004; Sung and Amasino, 2004). This topic is discussed in detail in Chapter 9.

4.3.1

Plant SET-domain proteins

HMTases are characterised by the SET domain (Pfam accession: PF00856), which is a motif of approximately 130 amino acid residues that catalyses methylation of lysine residues using the cofactors S-adenosylmethionine or S-adenosylhomocysteine (Min et al., 2002; Marmorstein, 2003). The SET domain was ﬁrst described in three Drosophila chromatin-remodelling proteins: Su(var)3-9 (Suppressor of variegation 3-9), E(z) (enhancer of zeste) and Trithorax (Tschiersch et al., 1994). In solution, the SET domain of the yeast transcription factor Clr4 forms three clusters of β-sheets arranged in a triangle, forming a pocket for binding the cofactor and the N-terminal tail of histone H3 (Min et al., 2002; Marmorstein, 2003). SET-domain proteins exhibit different substrate speciﬁcity. For example, human SET7/9 methylates amino acid residue K4 of histone H3, whereas Neurospora DIM-5 methylates amino acid residue K9 of histone H3 (Wilson et al., 2002; Zhang et al., 2002). The substrate speciﬁcities of SET-domain proteins are likely to be regulated by sequences surrounding the domain (Min et al., 2002; Marmorstein, 2003). Not all SET-domain proteins function as HMTases; for example, the pea SET-domain protein Rubisco large subunit methyltransferase methylates amino acid residue K14 of the large subunit of Rubisco in chloroplasts (Trievel et al., 2002). Animal HMTases are divided into four families: E(Z), Trithorax, ASH1 (ABSENT OR SMALL HOMEOTIC DISCS1) and Su(var)3-9, based on sequence similarities. Depending on the substrate speciﬁcity, HMTases may function as transcription activators or repressors. There are 14 genes encoding SET-domain proteins in Drosophila, 17 in mouse and 4 in yeast (Springer et al., 2003). In Arabidopsis, there are a total of 41 genes that encode SET-domain proteins. Rice has 33 genes encoding SET-domain proteins, and 35 genes have been identiﬁed in maize so far (Plant Chromatin Database). Thus, plants have many more genes encoding SET-domain proteins than animals. Many plant SET-domain proteins possess PHD (plant homeodomain, Pfam accession: PF00628) (Aasland et al., 1995), PWWP (Pfam accession: PF00855) (Stec et al., 2000) and YDG (Pfam accession: PF02182) domains. The functions of these domains are unknown, although they may be involved in protein–protein interactions (Aasland et al., 1995; Stec et al., 2000). DNA-binding

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motifs such as zinc ﬁngers and AT-hooks are also common in plant SET-domain proteins (Springer et al., 2003). In addition, plant SET-domain proteins possess the pre-SET motif (Pfam accession: PF05033), which is a cysteine-rich domain that is essential for the enzymatic functions of the SET domain (Rea et al., 2000; Marmorstein, 2003).

4.3.1.1

E(Z)- and Trithorax-type HMTases

In Drosophila, E(z)-type HMTases belong to the Polycomb-group (PcG) proteins, which are involved in repression of homeotic genes for speciﬁcation of segmentation during embryogenesis (Francis and Kingston, 2001). In PcG mutants, spatial patterns of homeotic gene expression are established correctly, but are misregulated later in late embryogenesis, suggesting that PcG proteins maintain repression of inactivated genes through cell divisions (Francis and Kingston, 2001). In Drosophila and mammals, E(z)-type HMTases methylate amino acid residue K9 and/or K27 of histone H3, but not K4 of histone H3 (Czermin et al., 2002; Kuzmichev et al., 2002). Methylated amino acid residues K9 and K27 of histone H3 are hallmarks of heterochromatin, and are involved in transcriptional repression, because they are recognised by repressors possessing chromodomains (Nielsen et al., 2002). The chromodomain (chromatin organisation modiﬁer, Pfam accession: PF00385) is a 60 amino acid residue module binding methylated lysine side chains, and is present in various transcriptional repressors such as the yeast, mammalian and Drosophila Heterochromatin Protein 1 (HP1), and the Drosophila Polycomb protein (Czermin et al., 2002; Maison and Almouzni, 2004). In Arabidopsis, there are three E(z)-type HMTases: SDG1 (also known as CLF for CURLY LEAF), SDG5 (also known as MEA for MEDEA or FIS1 for FERTILISATION INDEPENDENT SEED1) and SDG10. Three E(z)-type HMTases, SDG124, SDG125 and SDG126, are also predicted in rice (Springer et al., 2003). Although HMTase activities have not been demonstrated for CLF and MEA, these proteins mediate transcriptional silencing (Goodrich et al., 1997; Grossniklaus et al., 1998). CLF represses transcription of the ﬂoral homeotic gene AGAMOUS (AG) in vegetative tissues. AG is a MADS-box gene that is expressed in whorls 3 and 4 of the ﬂower, and speciﬁes identity of stamens and the carpel (Bowman et al., 1989). Loss-of-function mutation in CLF resulted in expression of AG in whorls 1 and 2 of ﬂowers, and in leaves (Goodrich et al., 1997). CLF mutants possess curly leaves and exhibit homeotic transformation of sepals and petals into stamens and carpels. Like animal PcG proteins, CLF does not specify the spatial pattern of AG expression, but is required to repress its expression in cells where AG was initially silenced (Goodrich et al., 1997). MEA is an imprinted gene encoding a E(z)-type HMTase (Grossniklaus et al., 1998). Genomic imprinting is the phenomenon where a particular allele that is silenced depends on whether it is derived maternally or paternally (Moore, 2001). Because a plant may receive pollen from many sources, it is evolutionarily advantageous for the pollen-donating plant if the seed containing its embryo has welldeveloped endosperm. However, it is unfavourable for the mother plant to invest more energy than necessary in the development of a particular seed. The maternal

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genome in the embryo or the endosperm silences paternal growth-promoting genes, whereas the paternal genome would inactivate maternal growth-suppressing genes (Mora-Garcia and Goodrich, 2000). MEA is maternally expressed, and represses the paternally expressed MADS-box gene PHERES1 (Kohler et al., 2005). Loss-offunction mutations in MEA result in aborted seeds, due to over-proliferation of the embryo (Grossniklaus et al., 1998; Kohler et al., 2005). Another class of plant SET-domain proteins, the Trithorax-Group (TrxG)-type HMTases, is antagonistic in function to PcG, i.e. TrxG positively regulates expression of homeotic genes for pattern speciﬁcation in Drosophila (Francis and Kingston, 2001). TrxG genes are not involved in the initial activation of gene expression in progenitor cells, but are necessary for maintaining transcriptional activity in subsequent cell lineages following cell division (Francis and Kingston, 2001). TrxG-type HMTases such as the human MIXED LINEAGE LEUKAEMIA and the yeast SET1 methylate histone H3 at amino acid residue K4, which is a post-translational modiﬁcation characteristic of euchromatin (Lachner and Jenuwein, 2002; Milne et al., 2002). There are ﬁve genes encoding TRITHORAX-type HMTases in Arabidopsis (SDG2, SDG14, SDG25, SDG27 and SDG30) and in rice (SDG106, SDG115, SDG116, SDG127 and SDG129) (Springer et al., 2003). Arabidopsis SDG27 (also known as ATX1 for ARABIDOPSIS TRITHORAX1) methylates histone H3 at K4 in vitro, and activates expression of several ﬂoral homeotic genes, such as AP1, AP2 and AG (Alvarez-Venegas et al., 2003). Like Drosophila TrxG proteins, ATX1 positively regulates gene expression, but does not initiate transcription in cells (AlvarezVenegas et al., 2003). In addition to homeotic transformation of ﬂoral organs, ATX1 mutants have small rosette leaves and are late ﬂowering, suggesting that ATX1 also regulates genes that control vegetative development and ﬂowering time (AlvarezVenegas et al., 2003). During embryogenesis in Drosophila, PcG and TrxG genes function in conjunction to maintain initially established pattern of gene expression (Hugh and Brock, 2005). PcG and TrxG genes are important in propagating cell fate, and therefore confer cell identity during formation of organs. Because methylation of amino acid residue K9 of histone H3 by PcG-type HMTases is associated with heterochromatin formation, and methylation of amino acid residue K4 of histone H3 by TrxG-type HMTases is correlated with open accessible chromatin structures, it is currently considered that PcG and TrxG confer cell memory by re-establishing the same chromatin structures at their target genes in daughter cells following cell division (Francis and Kingston, 2001; Hugh and Brock, 2005). In plants, the TrxG-type HMTase SDG27 activates AG, whereas the PcG-type HMTase CLF represses AG to deﬁne its expression boundaries to specify ﬂoral organ identity. Hence, although plants and animals have very different homeotic genes (Meyerowitz, 2002), they have evolved to utilise PcG- and TrxG-type HMTases to regulate spatial patterns of gene expression to specify formation of organs (Kohler and Grossniklaus, 2002).

4.3.1.2

Su(var)3-9-type HMTases

A total of 15 genes encoding SET-domain proteins have been predicted to belong to the Su(var)3-9 family of HMTases in Arabidopsis (Springer et al., 2003).

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These genes are designated SUVH1 to SUVH15. Unlike Drosophila and mammalian Su(var)3-9-type HMTases, Arabidopsis homologues do not possess chromodomain or ankyrin repeats. Ankyrin repeats are tandemly arranged modules of 33 amino acid residues involved in protein–protein interactions (Kalus et al., 1997). In animals, Su(var)3-9-type HMTases speciﬁcally methylate amino acid residue K9 of histone H3, which in turn recruits transcriptional repressors possessing chromodomains, such as HP1. HP1 is involved in organising chromatin into heterochromatin (Maison and Almouzni, 2004). Su(var)3-9-type HMTases play important roles in gene silencing and are the main regulators of heterochromatic domains in animal cells (Maison and Almouzni, 2004). In Arabidopsis, SUVH2 localises to pericentric heterochromatic regions in the interphase nucleus (Naumann et al., 2005). Loss-of-function mutations in SUVH2 led to reduction in levels of mono- and dimethylated K9 in histone H3, monoand dimethylated K27 in histone H3, and monomethylated K20 in histone H4, which are the hallmarks of heterochromatin in Arabidopsis (Naumann et al., 2005). Over-expression of SUVH2 resulted in increased amounts of heterochromatin and enhanced transcriptional gene silencing (Naumann et al., 2005). Thus, Arabidopsis SUVH2 has similar functions to its animal homologues in establishing heterochromatin regions in the nucleus. Plants over-expressing SUVH2 are smaller and possess curly leaves, suggesting that SUVH2 regulates genes involved in growth and development (Naumann et al., 2005). Over-expression of another Arabidopsis Su(var)39-type HMTase gene, SUVH1, has no effect on heterochromatin formation, and no obvious morphological phenotypes (Naumann et al., 2005). Thus, SUVH1 and SUVH2 have different functions, suggesting that different members of the Su(var)39-family of HMTases have distinct biological roles. The tobacco Su(var)3-9-type HMTase, NtSET1, methylates amino acid residues K9 and K27 of histone H3 in vitro (Yu et al., 2004). Transgenic tobacco plants that over-express NtSET1 have stunted vegetative growth, due to inhibition of cell division and expansion (Shen and Meyer, 2004). NtSET1 interacts with Like Heterochromatin Protein1 (LHP1), which is the Arabidopsis homologue of HP1, and both proteins co-localise to heterochromatin in the nuclei of tobacco cells. Thus, NtSET1 may mediate heterochromatin formation through HP1 in tobacco (Yu et al., 2004). In addition, NtSET1 regulates chromosome segregation during cell division (Shen and Meyer, 2004). The tobacco NtSET1 is likely to be a homologue of the Arabidopsis SUVH2. Arabidopsis SUVH4 (also known as KYP for KRYPTONITE) was isolated in a genetic screen for suppression of silencing of the SUPERMAN gene, and again in a screen for reactivation of the silenced PAI gene (Jackson et al., 2002; Malagnac et al., 2002). SUVH4 can mono- or dimethylate but does not trimethylate amino acid residue K9 of histone H3 in vitro (Jackson et al., 2004). Loss-of-function mutations led to decreased levels of dimethylated K9 in histone H3, and reduced CpNpG DNA methylation at retro-transposons, repetitive genomic sequences and transgenes, suggesting that DNA methylation is coupled to methylation of amino acid residue K9 of histone H3 (Jackson et al., 2002; Naumann et al., 2005). DNA methylation is likely to be linked to histone methylation through CHROMOMETHYLASE3 (CMT3),

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which is a DNA methyltransferase that possesses a chromodomain, and is involved in maintenance of methylated cytosines at methylated genes (Bartee et al., 2001; Lindroth et al., 2001). SUVH4 and CMT3 may function in conjunction with ARGONAUTE1 (AGO1) in RNAi-mediated silencing of transposons (Lippman et al., 2003). In contrast to SUVH2, SUVH4 null mutants do not have signiﬁcant decrease in levels of methylated K27 in histone H3 and methylated K20 in histone H4 at chromocentres, suggesting that SUVH4 is not likely to be involved in organisation of heterochromatin (Naumann et al., 2005). Thus, there appear to be at least two mechanisms of gene silencing by dimethylated K9 in histone H3 in plants, i.e. via interaction with chromodomain-containing repressors to mediate formation of heterochromatin, or through interaction with chromomethylases to maintain DNA methylation patterns.

4.3.1.3

ASH1-type and plant-speciﬁc HMTases

Arabidopsis has ﬁve genes (SDG4, SDG7, SDG8, SDG26 and SDG24) and rice has two genes (SDG102 and SDG110) that encode proteins with sequence similarity and with similar arrangements of protein domains to Drosophila and mammalian ASH1-type HMTases (Baumbusch et al., 2001; Springer et al., 2003). Arabidopsis SDG15 and SDG34 contain a PHD domain at the N-terminus, and a SET domain at the C-terminus, and are unique to plant and fungi (Springer et al., 2003). The functions of these predicted plant HMTases have not yet been studied.

4.3.2

Histone demethylase

For many years, methylation of histones H3 and H4 was regarded as a permanent form of post-translational modiﬁcation, at least as compared to acetylation, because the enzymes that demethylate histones had not been characterised. However, recently, the human LSD1 (lysine-speciﬁc histone demethylase1) was shown to demethylate dimethylated K4 in histone H3 using ﬂavin adenine dinucleotide (FAD) as a cofactor in a two-step reaction, where one methyl group was removed in each step (Shi et al., 2004). LSD1 catalyses amine oxidation, converting an N methyl group to an imine group, which is subsequently hydrolysed by water to form an amine group and a formaldehyde byproduct (Shi et al., 2004). Demethylation of amino acid residue K4 of histone H3, and not amino acid residue K9, by LSD1 is consistent with its function as a co-repressor in silencing neuronal-speciﬁc genes in non-neuronal cells (Ballas et al., 2001). However, recent work indicates that LSD1 can also function as a transcriptional activator by demethylating amino acid residue K9 of histone H3 (Metzger et al., 2005; Wysocka et al., 2005). The substrate speciﬁcity depends on the protein cofactors that associate with LSD1 (Metzger et al., 2005; Wysocka et al., 2005). LSD1 possesses four domains: a SWIRM domain (Pfam accession: PF04433), which is an 85 amino acid residue α-helical domain that is involved in protein interactions; a DAO domain, which is an FAD-dependent oxidoreductase motif (Pfam accession: PF01266); the FAD-binding domain (Pfam accession: PF01494);

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and the amine-oxidase domain (Pfam accession: PF01593). There are four genes in Arabidopsis (HMA1–HMA4) that have sequence similarities to LSD1 (Shi et al., 2004). Interestingly, HMA1 is FLD (FLOWERING LOCUS D), which is a repressor of the ﬂowering repressor gene FLC. Although histone demethylase activity has not been demonstrated for FLD, loss-of-function mutations in FLD lead to increased histone H3 acetylation at FLC, resulting in activated FLC expression and a lateﬂowering phenotype (He et al., 2003).

4.4

Interplay between histone acetylation and methylation in transcriptional regulation

A gene can exist in a range of transcriptional states: an activated transcriptional state, a basal transcriptional state, a state competent for transcription and a silenced transcriptional state (Figure 4.5). Acetylation of histones is a mechanism that upregulates transcription from the basal to an activated state. This notion is consistent with the observation that mutations in Arabidopsis HAG1, HAF2 and GTE6 result in downregulation of gene expression, but do not eliminate transcription altogether. Moreover, as acetylation is reversible, transition from the activated state to the basal state is mediated by HDACs in a single-step reaction, and gene expression would be downregulated in the absence of stimuli. Thus, genes that are involved in cellular responses to environmental signals, such as cold-response, light-induced, pathogeninduced and stress-induced genes, are regulated by HATs and HDACs in plants. In contrast to histone acetylation, methylation at amino acid residue K4 of histone H3 is a mark for euchromatin, and is associated with competence for transcription (Schneider et al., 2004). Both transcribed and non-transcribed genes in euchromatin are associated with methylated K4 in histone H3 (Schneider et al., 2004; van Dijk et al., 2005). Over-expression of Arabidopsis SDG27, whose product methylates amino acid residue K4 of histone H3 in vitro, does not initiate transcription of target genes in cells that do not originally express these genes, suggesting that methylated K4 in histone H3 is associated with competence for transcription, and not transcription per se (Alvarez-Venegas et al., 2003). It can be envisaged that transition from the transcriptionally competent state to the basal transcriptional state involves recruitment of sequence-speciﬁc transcription factors, chromatin remodelling and assembly of the RNA polymerase machinery (Figure 4.5). In the activated transcriptional state, genes are dimethylated at amino acid residue K4 of histone H3, and acetylated at histones H3 and H4 (Osano and Ono, 2003). In the silent transcriptional state, genes are methylated, and associated with histones H3 with dimethylated K9, and are packaged into heterochromatin. Dimethylated K9 in histone H3 is recognised by HP1, which is involved in heterochromatin organisation. In addition, dimethylation of K9 in histone H3 is linked to DNA methylation; dimethylated K9 is recognised by the chromomethylase, CMT3, which methylates DNA (Bartee et al., 2001; Lindroth et al., 2001). Methylated DNA is bound by methyl-CpG-binding proteins, which associate with HDACs (Nan et al., 1998). HDACs in turn deacetylate K9 in histone H3, making the lysine residue free

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Figure 4.5

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Interplay between histone acetylation and methylation in transcriptional control.

for methylation (Lawrence et al., 2004). Moreover, HDACs may physically interact with HMTases, resulting in histone methylation (Czermin et al., 2001; Vaute et al., 2002). Thus, DNA methylation and dimethylation of K9 in histone H3 form a selfpropagating cycle that ensures a silenced gene stays silenced (Figure 4.5). Unlike the transition from the activated to the basal transcriptional state, which is mediated by deacetylation, transition to the silenced transcriptional state involves various epigenetic changes, including methylation of DNA, methylation of K9 in histone H3 and organisation into heterochromatin (Figure 4.5). In plants, DNA methylation and dimethylation of K9 in histone H3 are involved in long-term gene silencing

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that is maintained through cell division, resulting in silencing of transposon activity (Lippman and Martienssen, 2004), repression of ﬂoral homeotic genes in vegetative tissues (Goodrich et al., 1997) and silencing of rRNA gene in nucleolar dominance (Lawrence et al., 2004). Common lysine residues in histone H3 and H4 tails are subjected to acetylation or methylation for transcriptional regulation. Once acetylated, the lysine residue cannot be methylated, and vice versa. Following synthesis in the cytoplasm, histones H3 and H4 are acetylated at their N-terminal tails before they are transported into the nucleus and assembled into chromatin in animals and plants (Sobel et al., 1995; Jasencakova et al., 2000). Acetylation of histone H4 occurs at amino acid residues K5 and K12 for histone deposition into chromatin, whereas acetylation of histone H3 is less conserved (Sobel et al., 1995). HDACs play a central role in transcriptional regulation, because the acetylated N-terminal tails of histones H3 and H4 on the newly replicated chromatin are deacetylated before other post-translational modiﬁcations can occur. In addition, HDACs are involved in several aspects of transcriptional control; they regulate transition from the activated to the basal transcriptional state, and are also required for establishing silent transcriptional states (Figure 4.5). Histone deacetylation is a key event in silencing of active genes, which are associated with acetylated histones (Czermin et al., 2001). Hence, mutations in plant HDACs affect expression of pathogen-response and stress-response genes (Song et al., 2005; Zhou et al., 2005), and also abolish gene silencing (Lawrence et al., 2004). As a seedling grows into an adult plant, the chromatin structures of various genes are modiﬁed in response to cues from the developmental programmes and environmental factors, so that sets of genes are expressed at the right time and in the right place (Li et al., 2002). These epigenetic modiﬁcations have to be erased prior to or shortly after egg fertilisation, so that the newly formed zygote can start a similar life cycle again. In mammals, global chromatin remodelling such as genomewide DNA demethylation and acetylation of histones have been observed during spermatogenesis and embryogenesis (Hazzouri et al., 2000; Mhanni and McGowan, 2004). DNA methylation levels decreased by 80% during maturation of pollen grains, suggesting that global DNA demethylation also occurs during gametogenesis in plants (Oakeley et al., 1997). Future work should indicate whether the mechanisms that reset epigenetic patterns are similar in plants and animals.

4.5

Conclusions

Acetylation and methylation of histones are key mechanisms of transcriptional regulation in plants. Proteins that acetylate and methylate histones play important roles in plant development. Plants possess an open growth system, forming vegetative and ﬂoral organs continuously throughout their life cycle. Moreover, plant development is plastic, and growth patterns change with environmental factors. In contrast, animals possess a closed system of development; speciﬁcation of organ formation occurs mainly during embryogenesis and follows a well-deﬁned developmental programme, which is relatively unaffected by environmental factors. Thus, plants have

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more genes encoding HATs, HDACs, BRD proteins and SET-domain proteins than yeast, Drosophila and mammals to regulate the continuous process of organogenesis, and to switch developmental fates in response to environmental signals. In addition, plants have evolved unique chromosomal proteins such as HD2-type HDACs and BRD proteins to regulate biological processes speciﬁc to plant physiology. Plant chromatin research is likely to stay at the forefront of chromatin research, because plants are good experimental systems for studying the biological functions of posttranslational modiﬁcations of histones in a multicellular organism. Currently, little is known about other post-translational modiﬁcations such as ADP-ribosylation, ubiquitination and SUMOylation, and modiﬁcations of residues such as proline, serine and arginine in histones. Furthermore, the functions of many plant transcription factors involved in post-translational modiﬁcations of histones have not yet been investigated, and future work will resolve the role of each individual transcription factor in plant development.

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5 Chromatin remodeling and histone variants in transcriptional regulation and in maintaining DNA methylation J.C. Reyes, J. Brzeski and A. Jerzmanowski

5.1

Introduction

The days when transcription activation was mostly about DNA-binding proteins recruiting RNA polymerases are not too far away (Goodrich et al., 1996; Ptashne and Gann, 1997). However, during the 1990s a combination of genetic and biochemical studies demonstrated that chromatin structure plays a crucial role in eukaryotic transcription (for a recent review, see Mellor, 2005). Far from being a mere passive structure designed for DNA package inside the nucleus, chromatin is a dynamic frame with essential functions in transcriptional activation, repression, and memory of expression patterns. It is now clear that changes in the chromatin structure of promoters and enhancer regions, what is generally known as ‘chromatin remodeling’, determine transcriptional control in a natural chromosomal context. The building block of the chromatin is the nucleosome, constituted by two copies of each of the four core histones H2A, H2B, H3, and H4 surrounded by 147 base pairs of DNA (Luger et al., 1997). In addition, a linker histone H1 directs the path of DNA between the adjacent nucleosomes that make up the chromatin ﬁber. During the last years, numerous studies in yeast and animals have evidenced that the nucleosome is a dynamic structure. Thus, dynamism affects different nucleosomal characteristics. First, canonical histones of the core can be exchanged by histone variant proteins with speciﬁc functions. This is known as ‘histone replacement’ and may occur during cell cycle interphase in speciﬁc genes or chromosomal regions. Second, histones are post-translationally modiﬁed (by acetylation, methylation, phosphorylation, etc.) mostly in the unstructured amino-terminal tail of histones H3 and H4. These modiﬁcations are reversible, and different patterns of modiﬁcation can be recognized, in terms of structural complimentarity, by transcriptional coactivators, and therefore constitute a code (the histone code) (Jenuwein and Allis, 2001). Finally, positioning of a nucleosome is also dynamic. Thus, nuclear machines are able to unwrap the nucleosomal DNA, to slide the nucleosome along the DNA, or even to eject the histone octamer in an ATP-dependent manner. All these dynamic transitions in the structure of a nucleosome have been designated by the general term of chromatin remodeling. In the present chapter we will focus on how ATP-dependent chromatin remodeling and histone replacement control gene expression and silencing in plants.

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5.2

113

ATP-dependent chromatin remodeling

ATP-dependent chromatin-remodeling complexes (CRCs) are multisubunit nuclear enzymes able to alter the interactions between the histone octamer and the DNA and therefore able to increase the ﬂuidity of the chromatin (for recent reviews, see Flaus and Owen-Hughes, 2004; Cairns, 2005; Smith and Peterson, 2005). In vitro, nucleosomes are in a thermodynamic equilibrium between a fully wrapped state and a set of partially unwrapped states (Li et al., 2005). In fact, it has been shown that increased temperature can provoke changes in the nucleosomal positioning similar to those carried out by CRCs (Flaus and Owen-Hughes, 2003). Therefore, in this sense, CRCs act as classical enzymes accelerating a natural reaction. A number of in vitro assays have been designed to determine the activity of CRCs. In these assays, CRCs, in the presence of ATP, are able to increase the accessibility of nucleases to the nucleosomal DNA, to move nucleosomes in cis along a DNA template (sliding), to transfer a histone octamer from one DNA template to another in trans, or to create dinucleosome structures from mononucleosomes. However, the mechanism by which these processes occur remains unclear, and more importantly, the way that chromatin-remodeling machines work in vivo is also unknown. All the CRCs contain a protein of the SNF2 family of DNA-dependent ATPases that constitute the motor subunit of the complex. SNF2 family proteins carry out, per se, ATP-dependent nucleosome-remodeling activity in vitro in the absence of additional subunits, although less efﬁciently than the full complex (Phelan et al., 1999). SNF2 family, which consists of more than 500 currently known proteins, falls into the large superfamily of DEXD/H ATPases. The distinguishing feature of the SNF2 family is the SNF2 N domain, a variant of the typical DEXD/H domain, which contains a well-conserved C-terminal extension of approximately 100 amino acids. SNF2 N ATPase domain contains an ATP-binding pocket and mediates ATP hydrolysis. A variable elastic spacer connects SNF2 N to the C-terminally located HelicC domain. These two domains form the catalytic core of the enzyme. In DNA/RNA helicases which are more distant homologs of SNF2 family, the DEXD/H and HelicC domains form a molecular hinge that mediates helicase activity and processive movement of the enzyme along the nucleic acid molecule. The SNF2 family is usually arranged into several subfamilies based on their auxiliary (signature) domains, located in the less conserved part outside the catalytic core (Figure 5.1). In general, this classiﬁcation reﬂects phylogenesis, indicating that the history of SNF2 family involved a series of independent fusion events. Some domain fusions occurred several times throughout the family evolution – for example, the chromodomain independently fused to ATPase domain to form Mi2/CHD and ATRX subfamilies. Numerous studies indicate that the signature domains may play a vital role in substrate recognition as well as in modulation of the enzymatic activity of SNF2-like proteins. One example is the deletion analysis of SANT/HAND/SLIDE signature module of Drosophila ISWI protein (Grune et al., 2003). The deletion of the SLIDE domain completely abolished the ATPase and remodeling activities of ISWI. Thus, assuming that the common ancestor of the

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Figure 5.1 Domain organization of the Arabidopsis SNF2 family proteins discussed in the text. Number of amino acids of the full-length proteins is indicated. Domain detection has been carried out using the SMART program (http://smart.embl-heidelberg.de/), the Pfam database (http://www.sanger.ac.uk/ Software/Pfam/), or the authors’ own sequence alignments.

family had similar enzymatic activity, an interesting evolutionary consequence of the fusion to auxiliary domains might be the divergent evolution of the ATPase domain. It could evolve to change the interaction with substrate and/or toward different reaction mechanism. Signature domains do not occur in all subfamilies. For example, a comparison of the DDM1 subfamily sequences revealed two highly conserved stretches of amino acids located N- and C-terminally with respect to the ATPase domain. However, a distant homology search using PSI-BLAST detected homologous sequences in other subfamilies. This result indicated that in contrast to other subfamilies the DDM1 subfamily has no unique signature domain. From an evolutionary perspective, this might imply that DDM1 mode of action may closely resemble the common ancestor. Interestingly, nucleosomes are not the only substrates of SNF2 family members. At least MOT1 subfamily acts to regulate TATA-binding protein (TBP) association with promoter DNA. The enzymatic activities of many subfamilies have not yet been assayed. Thus SNF2 family requires broader description. It can be deﬁned as a family of chaperons that assists protein–DNA interactions. The analysis of the Arabidopsis genome has evidenced the existence of 42 putative genes encoding SNF2 family members (Plant Chromatin Database. http://chromdb.org). These proteins can be grouped into 13 clearly deﬁned subfamilies. Twelve of these subfamilies contain partners from other phylogenetic groups

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of organisms, while one of the subfamilies appears to be plant speciﬁc. So far, seven of these genes have been characterized (PICKLE, SPLAYED, ARABIDOPSIS THALIANA BRAHMA, DECREASE IN DNA METHYLATION1, DRD1, CHR11 and PHOTOPERIOD-INDEPENDENT EARLY FLOWERING1), although, multisubunit CRCs have not yet been puriﬁed from plants. In the next sections, we will review evidence that suggests that Arabidopsis SNF2-like proteins also form multisubunit complexes, as well as their role in plant transcription and development.

5.2.1

SWI/SNF-like complexes in plants

The SWI and SNF genes were ﬁrst identiﬁed in screenings to isolate Saccharomyces cerevisiae mutants affected in mating type switching (SWItch genes) or in sucrose metabolization (Sucrose Non-Fermenting), respectively (recently reviewed in Smith and Peterson, 2005). Early studies demonstrated that all the SWI and SNF mutations displayed similar phenotypes and defects in the activation of a subset of genes regulated at the transcriptional level, suggesting that SWI and SNF proteins act in the same genetic pathways or form a functional complex. In fact, biochemical analysis demonstrated that SWI and SNF proteins function together as a multisubunit complex (Cairns et al., 1994; Peterson et al., 1994) able to facilitate the binding of transcription factors to nucleosomal DNA in an ATP-dependent way (Cote et al., 1994). The puriﬁed complex is approximately 2 MDa in size and contains 11 subunits (Table 5.1). Different SWI/SNF-like complexes have been identiﬁed in yeast and metazoans. Although we will refer to them

Table 5.1 Subunits of Saccharomyces cerevisiae SWI/SNF, Drosophila BAP, human BAF and putative Arabidopsis homologs S. cerevisiae

Drosophila (BAP)

Human (BAF)

Arabidopsis

SWI1 SWI2/SNF2

Osa Brahma

BAF250 BRG1, hBRM

SWI3

Moira

BAF155, BAF170

SNF5 SNF6 SWP73

SNR1 — BAP60

SNF11 SWP82 SWP29 ARP7, ARP9

— —

hSNF5 — BAF60a,BAF60b BAF60c —— ENL, EF9 BAF53

— AtBRM SYD CHR12 CHR23 AtSWI3A (CHB1) AtSWI3B (CHB2) AtSWI3C (CHB4) AtSWI3D (CHB3) BSH — CHC1 CHC2 — — — AtARP4 AtARP5

BAP55

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in general as SWI/SNF complexes, two different subclasses have been characterized (reviewed in Mohrmann and Verrijzer, 2005). One subclass comprises yeast SWI/SNF, Drosophila BAP (Brahma-associated proteins), and mammalian BAF (Brahma-associated factors) complexes, whereas the second subclass includes yeast RSC (remodels the structure of chromatin), Drosophila PBAP (Polybromo Brahmaassociated proteins), and mammalian PBAF (Polybromo Brahma-associated factors). Brahma is the name of the Drosophila SWI2/SNF2 orthologous protein. The difference between both subclasses of complexes is the presence of a higher number of bromodomains in the RSC, PBAP, and PBAF complexes than in the SWI/SNF, BAP, and BAF complexes. The bromodomain is a 110 amino acid domain involved in the interaction with acetylated lysines (Zeng and Zhou, 2002), which suggests that those complexes containing more bromodomains would be recruited to loci or genome regions with a higher level of histone acetylation. Although yeast SWI/SNF and Drosophila BAP complexes were ﬁrst identiﬁed as transcription activators, today it is well established that SWI/SNF-like complexes are involved in both transcription activation and transcription repression. Thus, whole-genome expression analysis has shown that expression of about 5% of the yeast genes are affected by loss of SWI and SNF proteins, about half of them being upregulated (Sudarsanam et al., 2000). Animal SWI/SNF has been implicated in embryo development (Bultman et al., 2000; Klochendler-Yeivin et al., 2000) as well as in cell-speciﬁc gene expression of erythrocytes (Armstrong et al., 1998), myelocytes (Kowenz-Leutz and Leutz, 1999), myocytes (de la Serna et al., 2001; Simone et al., 2004), and adipocytes (Pedersen et al., 2001). Furthermore, mutations of several SWI/SNF subunits have been found in human cancers, suggesting that SWI/SNF factors are important tumor suppressors (Versteege et al., 1998; Wong et al., 2000). How does the SWI/SNF complex regulate transcription? Unfortunately, this question does not have a simple and single answer. The picture that is emerging from the still small number of well-known examples in yeasts and mammals is that the SWI/SNF complexes are recruited to promoters or/and regulatory regions by interacting with speciﬁc DNA-binding proteins (Krebs et al., 1999; Agalioti et al., 2000). Histone H3 and H4 acetylation state of neighboring nucleosomes can contribute to the recruiting process through bromodomains or may be important for the stabilization of the complex in the chromatin (Hassan et al., 2002). Once in the regulatory region, the SWI/SNF complex appears to remodel the structure of one or more nucleosomes in order to permit access to buried DNA sequences. This remodeled state allows the binding to the newly exposed sequence of an additional DNA, speciﬁc transcription factor, or a general transcription factor such as the TBP. As mentioned above, an SWI/SNF-like complex has not been so far puriﬁed from plants, although, the analysis of the Arabidopsis genome indicates the existence of genes encoding polypeptide homologs of the subunits of the complex. Table 5.1 summarizes the polypeptides of the yeast SWI/SNF complex and their homologs in Arabidopsis. The functional core of the SWI/SNF complex sufﬁcient to remodel chromatin in vitro comprises four polypeptides: a dimer of SWI3 protein type, a SWI2/SNF2 type, and a SNF5 type (Phelan et al., 1999). This core seems to be universally conserved in all characterized SWI/SNF complexes and is also conserved in

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plants. In addition, Arabidopsis also contains homologs of SWP73 and actin-related protein (ARP) subunits. The fact that Arabidopsis contains small gene families for several of the putative SWI/SNF subunits suggests the existence of a number of different SWI/SNF complexes and raises the issue of function speciﬁcity or redundancy. The ATPases of the SWI/SNF complexes are classiﬁed into the SWI2/SNF2 subfamily and are characterized by the following signature domains: Domain I and Domain II at the N-terminus (originally deﬁned for the Drosophila Brahma protein (Tamkun et al., 1992), and a bromodomain at the C-terminus. From the 42 ATPases of the SNF2 family found in Arabidopsis only 4 belong to the SWI2/SNF2 subfamily based on phylogenetic analysis of SNF2 N and HelicC domains: SPLAYED (SYD), ARABIDOPSIS THALIANA BRAHMA (AtBRM), CHR12, and CHR23 (Figure 5.1). The four polypeptides contain a region related to the Domain II of Brahma, and two of them (SYD and AtBRM) also contain a region related to the Domain I. However, only AtBRM presents a bromodomain (see Figure 5.1). Two of these genes, SYD and AtBRM, have been characterized at the functional level. Mutants in SYD were identiﬁed as phenotypic enhancers of a weak LEAFY allele (Wagner and Meyerowitz, 2002). SYD plays a role in phase transition, and in carpel and ovule development. The syd inﬂorescence terminate in a central carpelloid structure after forming 2–20 ﬂowers, suggesting that SYD is also required for the maintenance of the shoot apical meristem (SAM) during the reproductive phase. In agreement with this, it has been recently shown that SYD controls the SAM stem cell pool via direct transcriptional control of the WUSCHEL (WUS) gene (Kwon et al., 2005). Therefore, WUS is the ﬁrst demonstrated direct target gene of a SNF2 protein in plants. Reduction of the levels of AtBRM by RNA interference also results in a pleiotropic phenotype (Farrona et al., 2004). Comparison of AtBRM-silenced plants with syd mutants indicates that while they share some phenotypes, others are very different or even opposite, suggesting that there is very little functional redundancy between both homologous proteins. AtBRM-silenced ﬂowers exhibit short petals and stamens, fused stamens and immature anthers, as well as defects in organ identity such as second-whorl petals with patches of sepalloid tissue. AtBRM-silenced plants display an early ﬂowering phenotype both under short day and long day, caused by the upregulation of CONSTANS, FT, and SOC1. However, at the moment it is unknown whether any of these genes is a direct target of AtBRM. The SWI3-like small gene family is composed of four polypeptides termed AtSWI3A (CHB1), AtSWI3B (CHB2), AtSWI3D (CHB3), and AtSWI3C (CHB4) (Sarnowski et al., 2002). These proteins contain four well-deﬁned domains of unclear functions: a SWIRM (SWI3/Rsc8/Moira) domain, a zinc ﬁnger, a SANT (SWISNF, ADA, N-CoR, TFIIIB) domain, and a leucine zipper. A phylogenetic analysis indicates that AtSWI3A and AtSWI3B are closely related and clearly separated from AtSWI3C and AtSWI3D (Sarnowski et al., 2005). Interestingly, these phylogenetic differences have also functional consequences (see below). Analysis of interactions between AtSWI3 proteins by yeast two-hybrid demonstrates that they form dimers similarly to the yeast and Drosophila orthologous proteins. However, not all the combinations of AtSWI3 subunits seem to be permitted. Thus, only

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Figure 5.2 Schematic representation of the interactions within the putative Arabidopsis SWI/SNF complex. This model combines yeast two-hybrid system data from three different publications (Sarnowski et al., 2002, 2005; Farrona et al., 2004).

six dimer combinations are theoretically possible (AtSWI3A:AtSWI3A, B:B, A:B, A:C, B:C, and B:D; see Figure 5.2). Functional analysis indicates that AtSWI3 proteins have rather speciﬁc and nonredundant functions. Thus, AtSWI3A and AtSWI3B are required for embryo development while AtSWI3C and AtSWI3D are required for vegetative and reproductive development (Sarnowski et al., 2005). Thus, atswi3a and atswi3b homozygous embryos arrest in the late and early globular stadium, respectively. Furthermore, atswi3b mutations result in lethality of about half of both macro- and microspores. Mutations in AtSWI3D provoke severe dwarﬁsm, and several ﬂoral defects including highly degenerated gynoecium and complete male and female sterility. Interestingly, inactivation of AtSWI3C results in a phenotype strikingly similar to that observed in AtBRM-silenced plants. Thus, atswi3c knockout plants present a delayed development, characterized by short stature and small downward curled leaves. Flowers exhibit small petals and stamens, fused stamens, and anthers replaced by sepalloid tissue, suggesting defects of class B homeotic genes. In agreement with these observations, atswi3c plants present a reduction in AP3 and PI mRNA levels. The ﬁnding that AtBRM-silenced plants display similar phenotypes to those in atswi3c plants suggests that they may form part of the same functional SWI/SNF-like complex. This

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is consistent with the fact that AtBRM interacts with AtSWI3C in yeast two-hybrids (Farrona et al., 2004) (Figure 5.2). Arabidopsis contains a single SNF5 homolog termed BUSHY (BSH). BSH is able to partially complement yeast SNF5 mutations conﬁrming the functional homology between both proteins (Brzeski et al., 1999). BSH interacts with AtSWI3B and AtSWI3A but not with AtSWI3D and AtSWI3C (Figure 5.2). Since SNF5 is one of the subunits of the core complex it is predicted that BSH should be present in all putative Arabidopsis SWI/SNF complexes. This suggests that mutations in BSH should have more dramatic effects than mutations in SWI3 or SWI2/SNF2 homologs, which are encoded by small gene families. Consistently, partial silencing of BSH led to a dramatic pleiotropic phenotype characterized by reduction in apical dominance and infertility.

5.2.2

Other ATPases of the SNF2 family that control plant development

Arabidopsis pickle (PKL) mutants were identiﬁed during a screen for mutants that exhibit abnormal root development (Ogas et al., 1997). The PKL roots express many embryonic traits after germination and are referred to as ‘pickle roots’. Another PKL mutant allele, gymnos, enhance the carpel abaxial–adaxial polarity defects of crabs claw (crc) mutations (Eshed et al., 1999). Thus, a gym crc double mutant displays ectopic formation of placentae and ovules outside the carpels. Single gym mutants exhibit a delay in differentiation of several carpel cell types, suggesting that GYM is not speciﬁcally involved in organ or cell polarity but in cell differentiation. PICKLE encodes an SNF2-like protein similar to the human Mi-2 proteins. Mi-2 belongs to the Mi-2/CHD subfamily of SNF2-like proteins, which are characterized by the presence of a chromodomain, and a SANT domain (Woodage et al., 1997) (Figure 5.1). Human Mi-2 associates with histone deacetylases (HDAC1 and HDAC2) in a multisubunit complex named NuRD (for nucleosome remodeling and histone deacetylation) involved in repression of transcription (Ahringer, 2000). The human NuRD complex also contains two histone chaperons of the MSI family (RbAp46 and RbAp48), a methyl-cytosine-binding protein and two zinc ﬁnger proteins called MTA1 and MTA2. Whether PICKLE is integrated in a multisubunit complex in Arabidopsis or not is currently unknown. PKL is involved in repression of embryo-speciﬁc genes after embryogenesis by controlling negatively the LEAFY COTYLEDON (LEC) genes (Ogas et al., 1999; Dean Rider et al., 2003). LEC genes promote embryonic identity in Arabidopsis. Loss-of-function mutations of the LEC genes, LEC1, LEC2, and FUSCA3 (FUS3), result in the replacement of cotyledons with vegetative leaves, as well as in reduced accumulation of storage proteins and desiccation protectants (Meinke et al., 1994). Therefore, overexpression of these regulatory genes in adult PKL plants has opposite effects. In addition, PKL plants exhibit the phenotypic characteristics of plant defective in gibberellic acid (GA) response: PKL plants are dark green and dwarfed, and time to ﬂowering is increased (Henderson et al., 2004). FUS3 and LEC2 repress the expression of the enzyme AtGA3ox2 that catalyzes the conversion of inactive to bioactive GAs (Curaba et al., 2004; Gazzarrini et al., 2004). The levels of both LEC

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genes are increased in adult tissues of PKL plants, which leads to the repression of AtGA3ox2, decreasing the level of GA. Another member of the SNF2 family with important functions in Arabidopsis development is PHOTOPERIOD-INDEPENDENT EARLY FLOWERING1 (PIE1) (Noh and Amasino, 2003). The PIE1 mutant displays an early ﬂowering phenotype both under long day and under short day. Interestingly, PIE1 is required for high levels of FLOWERING LOCUS C (FLC) expression in the shoot. FLC is a MADSdomain transcription factor involved in ﬂowering repression. In addition to the SNF2 N and the HelicC domains, PIE1 has a HSA and a SANT domain (Figure 5.1). Our phylogenetic analysis indicates that PIE1 belongs to the SWR1 subfamily of SNF2 proteins. The yeast SWR1-associated complex (SWC) is capable of directing the replacement of H2A–H2B dimers by the histone variant containing dimers H2A.Z–H2B (Krogan et al., 2004; Mizuguchi et al., 2004) (see Section 5.4.1). In yeast, H2A.Z (Htz1p) helps to form boundaries that restrict the spreading of silent chromatin from the telomers. One of the subunits of the SWR1 complex is the actin-related protein ARP6. Arabidopsis ARP6 (also called suppressor of frigida 3) mutants show a phenotype strikingly similar to the pie1 mutants, including early ﬂowering and reduced levels of expression of FLC (Choi et al., 2005; Deal et al., 2005). This is consistent with the existence of a SWC-like Arabidopsis complex.

5.3

Chromatin remodeling and DNA methylation

Classically, heterochromatin is deﬁned as a highly compacted transcriptionally inert part of the genome. Cytosine methylation is one of the characteristic epigenetic markers of heterochromatin. In Arabidopsis, methylated DNA is mostly located in heterochromatic chromocenters, which contain centromeric and pericentromeric repeat sequences. In contrast to Metazoa, plants have three distinct classes of DNA methyltransferases that are speciﬁc to cytosines within different DNA sequence contexts: CpG, CpXpG, and asymmetric C (Finnegan and Kovac, 2000). The MET1 methyltransferase is mainly responsible for de novo methylation (Aufsatz et al., 2004) and its maintenance at CpG sites (Finnegan et al., 1996; Genger et al., 1999). CHROMOMETHYLASE 3 (CMT3) is required for maintenance of the methylation status at CpXpG sites (Lindroth et al., 2001), and it cooperates with DOMAINS REARRANGED METHYLASES 1 and 2 (DRM1 and DRM2) in maintaining CpXpG and asymmetric methylation at other loci (Cao and Jacobsen, 2002). DRM1 and DRM2 also act as de novo DNA methylases at cytosines in all sequence contexts (Cao and Jacobsen, 2002). The mechanisms by which particular DNA sequences are targeted and converted into heterochromatin are poorly understood. In the DNA methylation mutant met1, chromocenters are still present (although they are smaller than normal), which suggests that mechanisms other than DNA methylation operate to form heterochromatin (Soppe et al., 2002). RNA interference has been shown to participate in centromeric heterochromatin maintenance in Schizosaccharomyces pombe (Volpe et al., 2002). Similar mechanisms were proposed for the maintenance of H3K9 and DNA methylation in centromeric tandem

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repeats of Arabidopsis (Martienssen, 2003). Paradoxically, such mechanisms would require continuous transcription of one DNA strand to produce siRNAs, which in turn would promote silencing of the other strand. According to this scenario, heterochromatin would have relatively high transcriptional activity although very little of the mature full-length transcripts would be produced. DECREASE IN DNA METHYLATION 1 (DDM1) was identiﬁed in early genetic screens for Arabidopsis mutants impaired in DNA methylation (Vongs et al., 1993) and transgene silencing (Mittelsten Scheid et al., 1998; Mittelsten Scheid and Paszkowski, 2000). It was subsequently shown to encode an SNF2-class protein, DDM1. Biochemical analysis of recombinant DDM1 demonstrated speciﬁc interaction with mononucleosomes and ATP-dependent nucleosome sliding activity (Brzeski and Jerzmanowski, 2003). As DDM1 has not been analyzed using other chromatin-remodeling assays, very little is known about its reaction mechanism.

5.3.1

The effects of ddm1 mutation differ from those caused by met1

Sequence homology and the available biochemical evidence suggest that DDM1 is closely related to chromatin-remodeling factors, and this prompted the formulation of the ﬁrst model of DDM1 action in vivo. In this simple scenario, DDM1 accompanies DNA methyltransferase MET1 and its chromatin-remodeling activity facilitates access to hemimethylated nucleosomal DNA just after DNA replication. This model satisfactorily explains the strong reduction in DNA methylation observed in ddm1 plants. However, further examination of ddm1 and met1 lines has highlighted striking differences in their phenotypes. Depletion of MET1, either by expression of antisense RNA or by mutation, causes a strong pleiotropic phenotype (Finnegan et al., 1996; Kankel et al., 2003; Saze et al., 2003). In the met1-3 null allele homozygotic line, CpG methylation is almost completely absent in all analyzed loci (Saze et al., 2003). In contrast, the ddm1 lines are initially WT (Wild Type) for this phenotype, with the onset of hypomethylation observed only after prolonged inbreeding (Kakutani et al., 1996). In the ﬁrst mutant generation, the DNA methylation level is decreased by 70% but the changes are restricted to the repetitive, heterochromatic fraction of the genome, which is the major acceptor of DNA methylation. Euchromatic sequences begin to be demethylated only in subsequent generations.

5.3.2

The model of DDM1 action

In light of the above data, the previously described model has to be modiﬁed slightly. MET1 would require DDM1 assistance mainly in the heterochromatic environment, while DDM1 appears to play only a minor role in the replication of euchromatic DNA methylation. This model is supported by an immunolocalization study on LSH, the mouse ortholog of DDM1. LSH is found mainly in late-replicating heterochromatic foci where it colocalizes with DNA methyltransferase DNMT1 during late S-phase (Yan et al., 2003). However, it is not clear to what extent mechanisms involving DDM1-like proteins have been conserved during evolution. In addition,

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this second model has been challenged by more recent studies. DAPI staining of ddm1 and met1 nuclei has revealed reduced chromocenters, indicating that heterochromatic foci have been ‘dissolved’ (Soppe et al., 2002). Both mutations led to an approximately 25% reduction in the average heterochromatin content. Consistent with these results, ﬂuorescence in situ hybridization (FISH) analysis demonstrated that a number of low-copy pericentromeric sequences appear dislocated away from the chromocenters while tandem repeats, such as the 180-bp centromeric repeats and the transposon arrays, remained associated with chromocenters. However, in both mutated lines, tandem repeats underwent demethylation and in the ddm1 line this was almost fully restricted to the repetitive DNA. These observations led to the suggestion that dense DNA methylation is not an important factor in heterochromatinization. Alternatively, some other unique features of the tandem repeats might prevent their dissociation from chromocenters, even where DNA methylation has been erased. These features might include particular attributes of DNA sequences or unrecognized chromatin modiﬁcations such as a speciﬁc pattern of histone modiﬁcations or the presence of the CenH3 variant of histone H3. Strikingly, crossing the ddm1 and met1 lines caused a further decrease in the chromocenter size (Soppe et al., 2002). This additive effect suggests independent modes of action for DDM1 and MET1. It is noteworthy that the study discussed above did not use null alleles. The allele ddm1-2 has a single nucleotide mutation that creates an additional splicing acceptor site, and translation of the incorrect splicing product would produce a truncated protein lacking an essential part of the HelicC domain. Such a protein would lack enzymatic activity but it might still mediate some important molecular interactions that may be a part of DDM1 activity in vivo. The in vivo stability of this truncated DDM1 has not been assayed. In addition, the MET1 allele used was semifunctional and could mediate DNA methylation to some extent. FISH experiments using a som8 line, which is a null allele of DDM1, revealed the dissociation of CEN180 bp arrays away from chromocenters (Scheid et al., 2002), while CEN180 bp was fully associated with chromocenters in the nuclei of met1-3, a MET1 null line (Tariq et al., 2003). These data further suggest an additional function for DDM1 besides assisting MET1. Formation of chromocenters and heterochromatinization of DNA is developmentally regulated (Mathieu et al., 2003). In young 2-day-old seedlings only small prechromocenters can be observed. Chromocenters achieve their mature size between days 2 and 4 after germination. DDM1 is most likely to be involved in the latter steps of chromatin organization, since prechromocenters in a ddm1-2 line are of the same size as those in WT nuclei. However, the depletion of DDM1 function severely affects heterochromatin maturation. Prechromocenter size increases only very slightly in ddm1-2 nuclei. Maturation of heterochromatin not only involves the association of dispersed DNA with growing prechromocenters but also requires extensive reorganization of chromosomal structure. FISH painting experiments in 2-day-old nuclei demonstrated that 5S rDNA is entirely associated with prechromocenters. In 4-day-old nuclei a fraction of 5S rDNA disperses away from the chromocenters. The formation of 5S rDNA euchromatic loops correlates with increased transcription. In addition, the modiﬁcation status of 5S rDNA changes during these

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structural rearrangements. The overall DNA methylation level increases, although it is possible that postreplicative methylation is limited to the heterochromatic fraction of 5S rDNA because another heterochromatin marker, H3K9 methylation, is only weakly detectible in the euchromatic 5S rDNA loops. DDM1 seems to counteract 5S rDNA euchromatinization – the loops are much more extensive in mature ddm1-2 nuclei compared to WT nuclei. This observation supports the hypothesis assigning an active role to DDM1 in shaping chromosomal structures.

5.3.3

DDM1 and methylation of histone H3

An additional level of complexity, which has to be considered when constructing a model of DDM1 action, results from its inﬂuence on the patterns of other chromatin modiﬁcations. Mutation of DDM1 resets the methylation patterns of histone H3. In general, H3K9 methylation is decreased in many heterochromatic sequences and is often substituted by H3K4 methylation (Gendrel et al., 2002). In contrast to the overall decrease in cytosine methylation, H3 methylation levels are not signiﬁcantly altered in the ddm1-2 line. Extensive mapping of chromatin modiﬁcation using chromatin immunoprecipitation has in fact revealed heterochromatic loci that exhibit more H3K9 methylation in ddm1-2 compared to WT. Therefore, the effects of ddm1 mutation on the methylation of cytosine and histone H3 are clearly different: the former shows a global decrease while the pattern of the latter is altered. These modiﬁcations are closely connected, but a discussion of their interdependence is beyond the scope of this review. The global reduction in DNA methylation in genetic backgrounds producing hypomethylation, such as ddm1 and met1, is often accompanied by local hypermethylation in some loci including AGAMOUS (AG) and SUPERMAN (SUP) (Jacobsen et al., 2000). This phenomenon mirrors to some extent the resetting of patterns of H3 methylation. Genetic screens for suppressors of the hypermethylated SUP epiallele clark kent (clk) identiﬁed DNA chromomethylase CMT3 (Lindroth et al., 2001) and H3K9-speciﬁc histone methyltransferase (HMT) KRYPTONITE (KYP) (Jackson et al., 2002). In good agreement with the genetic data, clk showed increases in CpXpG cytosine methylation and in H3K9 methylation. RNA interference mechanisms are presumably involved in this process, since the Argonaut family protein AGO4 was also identiﬁed in the same genetic screen (Zilberman et al., 2003). It is tempting to speculate that global hypomethylation of the genome might lead to transcriptional derepression of many loci and to random production of aberrant RNAs. Stochastic transcription and degradation of these transcripts might produce siRNAs that would guide RNA-dependent chromatin modiﬁcation apparatus. Such a mechanism would provide an additional layer of complexity to epigenetic repression. The results discussed above suggest that the mode of action of DDM1 is more complex than just increasing MET1 substrate accessibility. One attractive hypothesis is that DDM1 serves as a chromatin chaperon that actively shapes heterochromatin. The two models described above are not mutually exclusive because DDM1 activity apparently partially overlaps that of MET1. However, both are still highly speculative and further experimental evidence is required to establish their validity.

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Models of DDM1 targeting

Transient expression of DDM1 fused to GFP (green ﬂuorescent protein) revealed two distinct patterns of DDM1 subnuclear distribution (Zemach et al., 2005). Type I nuclei showed an intense signal in the chromocenters with much weaker staining of euchromatin. In type II nuclei the DDM1–GFP signal was uniformly dispersed throughout the nucleus. What might be the targeting signal for DDM1? It could be provided by heterochromatic epigenetic markers such as DNA or H3K9 methylation. Recombinant DDM1 is unable to sense the methylation status of DNA (Brzeski and Jerzmanowski, 2003). However, DDM1 might interact with auxiliary proteins that can speciﬁcally bind to methylated DNA. Recently DDM1 was shown to interact in vitro and colocalize in vivo with methyl CpG binding (MBD) proteins, which recognize methylated CpG dinucleotides (Zemach et al., 2005). Speciﬁc interactions between DDM1 and modiﬁed histones have not yet been examined. If DDM1 assists MET1 in DNA methylation, speciﬁc recognition of hemimethylated DNA would be expected. MBD proteins recognize symmetrically methylated CpG but recent in silico simulations of the recognition process demonstrated that only one of the methyl groups signiﬁcantly contributes to the binding energy (Rauch et al., 2005). A number of speculative scenarios can be envisaged to describe the role of MBDs in DDM1 targeting. MBDs could bind to newly methylated DNA while DDM1 participates in DNA methylation processes. DDM1–MBD interaction would then provide a spreading mechanism causing DDM1 and presumably MET1 to ‘slide’ along the chromatin ﬁber. At the same time, MBD proteins would decorate chromatin to lock up the heterochromatic state. Alternatively, DDM1 might act during the latter stages of heterochromatin formation. MBD-covered chromatin could attract DDM1, which would act to mature the heterochromatic environment to prevent demethylation. Such a mechanism could involve further compaction of heterochromatin promoted by the remodeling activity of DDM1. Contrary to the scenarios described above, LSH targeting is unchanged in DNA hypomethylating cell lines (Yan et al., 2003). Interestingly, LSH localization is affected in cells treated with a histone deacetylase inhibitor. In Arabidopsis, mutation of the sil1 histone acetyltransferase (HAT) leads to decreases in DNA and H3K9 methylation (Lippman et al., 2003). In contrast to ddm1- and met1-mediated DNA demethylation, the sil1 effect is unstable. Backcrossing to WT causes remethylation to reappear very quickly. Histone acetylation/deacetylation has a very high turnover rate and is therefore unlikely to serve as a stable epigenetic marker. At present it is not clear whether histone acetylation is involved in DDM1 targeting.

5.3.5

DRD1 – another SNF2 family protein involved in control of DNA methylation

Recently, another plant SNF2 family member, DRD1, has been implicated in DNA methylation control (Kanno et al., 2004, 2005). DRD1 has no obvious orthologs in fungi and animals and appears to belong to a plant-speciﬁc subfamily. DRD1 was identiﬁed in a genetic screen for suppressors of RNA-directed DNA methylation. The screen consisted of two transgenes integrated into the Arabidopsis genome: a

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‘reporter transgene’ encoding GFP and a ‘silencer transgene’ that produced short double-stranded RNA complementary to the promoter region of the reporter transgene. In the wild-type population, the silencer transgene effectively guided RNAdirected DNA methylation to block expression of the target transgene. In drd1 mutants, DNA methylation in the siRNA complementary region was signiﬁcantly reduced. However, the drd1 mutation did not affect global DNA methylation in heterochromatic regions. Thus, DRD1 is thought to act locally during de novo methylation of DNA complementary to siRNA. Intriguingly, DRD1 was required for the efﬁcient erasure of a methylation mark, after outcrossing of the siRNA source. The precise role of DRD1 in the dynamic regulation of DNA methylation has yet to be revealed.

5.4

Histone variants in the regulation of chromatin functions

Both animals and plants, in addition to the major class of replication-dependent (RD) histones, have a class of characteristic histone forms, usually encoded by singlecopy genes, the expression of which is not restricted to S-phase. These variants, also known as replication-independent (RI) or replacement histones, may play a role in the modulation and inheritance of chromatin states. They should be distinguished from nonallelic subtypes of major histones that are common in many lineages. A distinctive feature of the variants is an early evolutionary origin, which explains why they are more closely related to each other in phylogenetically distant branches, than to the major core histone forms of their own species.

5.4.1

Occurrence and functional role of core histone variants

Of the four core histones, only H3 and H2A have characteristic, evolutionarily conserved variants (Table 5.2). The biological importance of these forms is best illustrated by H3 variant CenH3. This centromere-speciﬁc protein determines the maintenance and inheritance of centromeric chromatin independently of the type of DNA satellite sequences involved, and is critical for correct assembly of the proteins comprising kinetochores (Henikoff et al., 2004). The characteristic feature of CenH3 is the N-terminal part that bears no homology to the N-terminal tail of Table 5.2 Major replication-independent variants of H3 and H2A histones and their function in vertebrates and ﬂowering plants Histone variant

Occurrence and function/animals

Occurrence and function/plants

CenH3

+

+

H3.3 H2AF/Z H2A.X MacroH2A H2ABdb

+ + + + +

Organization of centromeres kinetochore assembly/function Transcriptional activation Transcriptional activation and repression DNA repair/recombination X-chromosome inactivation Transcriptional activation

+ + + − −

Organization of centromeres kinetochore assembly/function Transcriptional activation Not determined Not determined

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canonical H3 forms and can be of variable length in different lineages. The histonefold domain (HFD) of CenH3 is only 50% identical to the HFD of H3, with the most distinctive change being the replacement of a conserved glutamine in the α1 helix and the extension by a few amino acids of the loop 1 region connecting helices α1 and α2. Interestingly, loop 1 is one of the conserved fragments through which H3 interacts with nucleosomal DNA. The enlargement of this particular element could cause altered DNA-binding properties, resulting in stronger contacts of CenH3 with nucleosomal DNA (Malik and Henikoff, 2003). The characteristic loop 1 region of CenH3 is both necessary and sufﬁcient for its centromeric localization (Vermaak et al., 2002). The unique and variable N-terminal sequences of CenH3 contain binding domains for kinetochore proteins (Malik et al., 2002). Overall, the variability within the CenH3 family reﬂects the accelerated evolution of this variant, compared to major H3 forms. Plant CenH3 (HTR12) has been identiﬁed and analyzed in Arabidopsis (Talbert et al., 2002). Differences in the N-terminal tail between the CenH3 of Arabidopsis thaliana and the closely related Arabidopsis arenosa conﬁrm the rapid adaptive evolution of this protein in plants. Arabidopsis HTR12 is present in both mitotic and meiotic centromeres. The fast changes in CenH3 variants may be driven by the selective pressure to counteract the spread of deleterious forms of centromeric DNA resulting from rapid evolution of satellite sequences occurring due to meiotic drive (Henikoff et al., 2001). H3.3 another evolutionarily old variant, differs from the conserved canonical H3 in only four amino acids. One of these residues is located in the N-terminal tail and three are in the HFD α1 helix. In H3.3 from different species the replacement amino acids vary, and so both residue substitution and lack of conservation in these positions in addition to RI expression distinguish H3.3 from H3. The correlation between high transcriptional activity and H3.3 deposition argues strongly for structural alterations affecting the accessibility of nucleosomal DNA for transcription. Interestingly, in Drosophila, the replacement of the three amino acids in the HFD region is necessary and sufﬁcient to confer RI deposition of H3 into chromatin, suggesting that these amino acids are critical for recognition by nucleosome assembly factors (Ahmad and Henikoff, 2002). In Lilium longiﬂorum the expression of a gene encoding an H3.3-like protein is considerably upregulated in vegetative cells of the developing bicellular pollen, which are characterized by highly active chromatin (Sano and Tanaka, 2005). As shown for the ﬁrst time in alfalfa (Waterborg, 1990) and later in Drosophila (McKittrick et al., 2004) and Arabidopsis (Johnson et al., 2004), H3 and H3.3 show different patterns of post-translational modiﬁcation. Characteristically, modiﬁcations usually associated with active chromatin, like methylation of K4 and K79 and acetylation of K9, K14, K18, and K23, were found to be two- to ﬁvefold enriched in H3.3 compared to canonical H3. On the other hand, the latter was selectively enriched in methylated K9, a modiﬁcation associated with transcriptionally inactive chromatin. H2AF/Z is an evolutionarily old and universally occurring RI variant of H2A with an essential function in animals. It differs from the canonical H2A in a number of amino acids, with the most pronounced differences in the ‘docking domain’ near the C-terminus, a part of H2A involved in critical interaction with the H3–H4

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dimer. Structural studies indicate looser compaction of H2A.F/Z-containing nucleosomes and suggest that H2A and H2A.F/X cannot coexist in the same nucleosome (Malik and Henikoff, 2003). While there is a strong indication that H2A.F/Z is required for maintaining a transcriptionally open chromatin state, it has also been linked with the repression of transcription (Swaminathan et al., 2005). In Arabidopsis, variants corresponding to H2A.F/Z are encoded by four genes. The expression of one of these genes was shown to be insensitive to inhibitors of DNA replication and strictly correlated with proliferative activity (Callard and Mazzolini, 1997). Another universally conserved RI variant of H2A is H2A.X, characterized by the C-terminal peptide SQ(E/D), where is a hydrophobic amino acid. This variant is critical for genome stability. The phosphorylation of its C-terminal serine in response to double-strand breaks occurring during replication or recombination mediates the recruitment of proteins directly involved in DNA repair (Malik and Henikoff, 2003). H2A.X is present in Arabidopsis, where it is encoded by two genes. Its importance for plant biology has not yet been assessed in detail. In addition to the above universal RI variants, there are some plant-speciﬁc forms of H2A that differ structurally from the canonical form. One is an H2A RI variant characterized in wheat, with a short C-terminal tail lacking the SPKK motifs (Huh et al., 1997). On the other hand, some major RI variants of H2A that occur in animals have not been detected in plants (Table 5.2). The replication- and repair-coupled assembly of nucleosomes using canonical core histones is mediated by chromatin assembly factor 1 (CAF-1). It is a complex composed of three conserved subunits: p150, p60, and p48 in human and Cac1, Cac2, and Cac3 in yeast. The CAF-1 complex is also active in nucleosome assembly in plants. Mutations in the Arabidopsis genes FAS1 and FAS2, homologs of Cac1 and Cac2, respectively, disrupt meristem activity resulting in similar phenotypes distinguished by aberrant shoot development and deﬁcient root growth (van Nocker, 2003). MSI, the homolog of the third subunit Cac3, is also required for proper shoot and root development, but in addition it acts as a component of Polycomb complexes that control seed and embryo development (Hennig et al., 2003). Different complexes mediate the RI deposition of histone variants. The FACT complex, composed of SSRP1 and Spt16 subunits, displaces the H2A/H2B dimers during transcription, without changing nucleosome positioning (Belotserkovskaya et al., 2003). H2A.Z has been found in two complexes: one characterized by the presence of the H2A/H2B histone chaperon assembly protein Nap1 and the other containing the Swi/Snf-type ATPase Swr1. The Swr1-complex is critical for the substitution of H2A.Z/H2B by H2A/H2B in the nucleosome. It is possible that the action of Swr1 and FACT are coordinated during transcription to enable effective incorporation of H2A.Z/H2B heterodimers. As mentioned in Section 5.2.2, a close homolog of yeast Swr1 in Arabidopsis is PIE1, a gene required for activation of FLC and ﬂoral repression (Noh and Amasino, 2003). Interestingly, PIE1 has a SANT domain, which has been shown to be involved in interactions with HATs and HDACs. The Arabidopsis homolog of the FACT complex has been shown to associate with actively transcribed genes (Duroux et al., 2004). H3.3 is deposited by a HIRA

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complex mediating RI chromatin assembly, which contains a histone regulator A (HirA) protein. A gene encoding a HIRA homolog is present in Arabidopsis. Available experimental evidence indicates that deposition of both H2A.X and H3.3 occurs during transcription. In Drosophila cells there is sufﬁcient H3.3 to package all transcribed genes. Given the fact that H3.3 mostly carries modiﬁcations associated with active chromatin, whereas the canonical H3 is enriched in modiﬁcations linked to transcriptional repression, it is conceivable that the modiﬁcation status of histones on a particular gene is linked with the nucleosome assembly pathway (McKittrick et al., 2004). This implies that histone-modifying complexes (like those containing HDAC, HMT, and HAT activities) are associated with protein machines responsible for RC or RI nucleosome assembly. If this is indeed the case, and given the conservative nature of RC nucleosome assembly, the transcription-linked replacement of histone variants, rather than the replication (by as yet unknown mechanisms) of the pre-existing modiﬁcation pattern, could be a major driving force in the epigenetic inheritance of chromatin states (Henikoff et al., 2004).

5.4.2

Role of H1 histone in chromatin and signiﬁcance of nonallelic H1 variants

The assessment of global linker (H1) histone function in plants and animals has been hampered by compensation among numerous variants, a phenomenon reﬂecting strong pressure to maintain a physiological H1-to-nucleosome ratio in chromatin. Reversal of the normal ratio of major to minor H1 variants in tobacco, while not affecting the growth and development of the plant, led to disturbances in male gametogenesis and ultimately produced a male sterility phenotype (Przewloka et al., 2002). In mice, the individual somatic subtypes were found to be dispensable even in animals lacking the H10 variant. However, mice lacking three main somatic H1 variants and showing a 47% reduction in the H1–nucleosome ratio died, demonstrating that linker histones are essential for vertebrate development (Fan et al., 2003). Arabidopsis plants with a >90% reduction in H1 expression exhibited a spectrum of aberrant developmental phenotypes, some of which resembled those observed in DNA hypomethylation mutants (Wierzbicki and Jerzmanowski, 2005). While the downregulation of H1 genes did not cause substantial genome-wide DNA hypo- or hypermethylation, it was correlated with minor but statistically signiﬁcant changes in the methylation patterns of repetitive and single-copy sequences, occurring in a stochastic manner. These ﬁndings suggest an important and previously unrecognized link between linker histones and speciﬁc patterns of DNA methylation. Notably, a similar effect of H1 depletion on DNA methylation has been recently reported for mice (Fan et al., 2005). H1-dependent higher order chromatin structures have been shown to interfere with Swi/Snf-mediated nucleosome remodeling (Horn et al., 2002). It is thus possible that an H1-stabilized ordered chromatin conformation is required for correct targeting of DNA and core histone modiﬁcations. The nonallelic H1 variants could provide this system with additional levels of subtle regulation. The variability of linker histones is the greatest among all histones. In general, one can distinguish between the macroheterogeneity resulting from lineage-speciﬁc

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variation and microheterogeneity occurring within lineages. The alignment of conserved H1 globular domains (GH1s) shows a hotspot for insertion located in the WING subdomain. An analysis of the size of the insert yielded a tree that separates H1 histones into four major classes: (1) H1 without an insert, including all known plant H1s and Dictyostelium H1; (2) H1 with a three amino acid insert including yeast and other fungal H1s; (3) H1 with a ﬁve amino acid insert including the majority of animal H1s; and (4) H1 with an eight- to ten amino acid insert including some special ‘cleavage-stage’ animal H1 variants. An independent parsimonious tree based on full length GH1 sequences conﬁrmed the above classiﬁcation (Jerzmanowski, 2004). The WING of GH1 plays a key role in DNA recognition (Gajiwala et al., 2000). Deletion or insertion of several amino acids in this region can thus be of critical importance for the overall strength and speciﬁcity of H1 binding in chromatin. This is analogous to the situation revealed for variants of H3 and H2A, in which changes to a few amino acids in crucial interacting regions caused huge overall effects on chromatin structure (see above). The relationships between linker histones within kingdoms have been deduced from phylogenetic analyses (see Jerzmanowski, 2004, for review). Within animal H1s there are several well-separated isoforms. One is the major form of H1 in vertebrates. Another readily distinguished isoform is represented by the cell-cycleindependent forms of H1, characteristic of the whole subkingdom of deuterostomes: H1D of Echinodermata, B4-like and H5 and H10 of Vertebrata. The B4-like isoforms belong to a class characterized by an eight- to ten amino acid insert in the WING domain. Unlike the canonical animal H1 histones, B4 does not prevent the remodeling of chromatin by ATP-dependent complexes and thus might be at least partly responsible for the totipotency of early embryonic chromatin (Saeki et al., 2005). It would be interesting to know if this effect is due to changes in the WING subdomain. The general ‘plant-type’ H1 is also characterized by alterations of the WING, albeit by shortening rather than extension of the ‘insert’ region. However, the characteristic binding properties of the WING might be distorted by both extending and shortening of this critical region. It remains to be seen whether plant H1s affect chromatin accessibility in a similar way to that shown for B4. The occurrence of the novel, highly distinct isoforms of H1 throughout the history of animals reﬂects the adaptive evolution of H1. Plant H1s have apparently evolved in a similar way. Phylogenetic analysis has revealed a distinct branch of so-called ‘drought-inducible’ variants of H1, the expression of which is upregulated upon water stress. They represent an old isoform, which existed before the separation of mono- and dicotyledonous plants. Another striking feature of plant H1s is a branch representing ‘hybrid’ proteins. It groups sequences in which a typical GH1 domain is fused to domains characteristic of proteins from outside the H1 family, like MYB and HMG (Jerzmanowski et al., 2000). The general scheme based on comparisons of the most evolutionarily conserved GH1 domain does not reveal the rich microheterogeneity of linker histones, which stems from differences between the less well-conserved basic tails. Such variants, often referred to as somatic subtypes, occur in both plants and animals. The N- and

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C-terminal tails of the subtypes differ in length, amino acid composition, and the frequency and distribution of phosphorylation sites. The importance of the variability of plant linker histones is still not understood. A characteristic feature of the drought-inducible variants is a much shorter C-terminal tail (about 80 residues) compared to that of the major somatic H1s (125– 150 residues). The drought-inducible variants are not only smaller but also notably less basic than somatic H1s. This feature is due to the fact that the C-terminal domains of linker histones are highly enriched in basic residues. Thus, the Lys + Arg to Asx + Glx ratio for tobacco drought-inducible variant H1C is 1.2, whereas this ratio for the tobacco major somatic H1 (H1B) is 2.5 (Prymakowska-Bosak et al., 1999). The C-terminal domain of H1, which can adopt a segmental α-helical conformation, binds to the linker DNA, neutralizing its negative phosphate charges and facilitating chromatin condensation. In transgenic tobacco plants in which the proportion of smaller and less charged H1 variants (including drought-inducible variants) was considerably increased at the cost of the major somatic variants, the chromatin is less tightly packed than in plants where the dominating forms of H1 are major variants (Prymakowska-Bosak et al., 1999). Interestingly, among 64 transcripts expressed preferentially in Arabidopsis guard cells there are two variants of H1: a major somatic variant and a drought-inducible variant (Leonhardt et al., 2004). These two variants of H1 are the only chromatin-related proteins with a global regulatory function which are speciﬁcally upregulated in guard cells. It remains to be seen whether this correlates with the rapid modulation of transcriptional activity required for guard cell function.

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6 Matrix attachment regions and transcriptional gene silencing William F. Thompson, Steven Spiker and George C. Allen

6.1

Introduction

It was realized early in the history of transgenic work that the expression of genes transferred to plant genomes was not always stable or predictable. Such variation has often been attributed to position effects, such as those known to occur in Drosophila (Pal-Bhadra et al., 2004). Position effects are presumed to reﬂect pre-existing differences in chromatin structure or other genomic features at different sites of transgene integration. However, it is now clear that transgene expression is also affected, and may even be blocked altogether (silenced), by mechanisms that are largely independent of chromosomal integration site. For example, in 1989 the Matzke group reported inactivation and methylation of transgenes from a ﬁrst transformation following a second transformation with another T-DNA. Soon thereafter, back to back papers from Napoli et al. (1990) and van der Krol et al. (1990) reported cosuppression of transgene and homologous host genes, and Lindbo et al. (1993) reported that transgene-induced virus resistance was associated with a cytoplasmic activity that targets speciﬁc RNA sequences for inactivation. Many subsequent reports have highlighted the fact that transgenes are quite frequently subject to position effects and silencing. One particularly dramatic example comes from work by Meyer et al. (1992), who set up an experiment designed to trap transposons inserting into a transgene in petunia. The maize A1 gene, transferred to a white-ﬂowered mutant of petunia, conferred a salmon-red color phenotype in the ﬂowers. Transposon insertions inactivating the transgene should, therefore, create white sectors in otherwise salmoncolored ﬂowers. Expecting such events to be rare, Meyer et al. set up a large ﬁeld experiment involving 30 000 transgenic individuals. Instead of the expected rare events, however, they found a variety of white-ﬂowered phenotypes, including fully white and variegated ﬂowers, at a very high frequency. A few of the white ﬂowers were found to be associated with deletions of the transgene, but many others, including those showing variegation and developmental shifts in expression, were associated with variation in the methylation status of the 35S promoter. The likelihood of methylation seemed to increase with the age of the plant from which the seed was derived, as well as in response to several environmental factors such as temperature.

MARs AND GENE SILENCING

6.2

137

Costs and consequences of transgene expression variation

These and many other examples illustrate a complex of epigenetic processes that complicate both the use of transgenes as research tools and their application in plant improvement programs (Iyer et al., 2000; Gepts, 2002; Lorence and Verpoorte, 2004). Variability attributable to silencing and related processes necessitates the analysis of many more transformation ‘events’ than might otherwise be necessary to interpret phenotypic effects of transgenes, increases labor costs, and triggers regulatory concerns. In addition, because silencing can occur in later generations of lines initially showing good expression (Bourdon et al., 2002; Vain et al., 2002; Bregitzer and Tonks, 2003; Levin et al., 2005), selecting good expressors from a population of primary transformants, or even from the T1 generation, is not sufﬁcient to guarantee stable performance over subsequent generations. Typically, a considerable number of candidate lines must be maintained through multiple generations before selecting those in which expression is stable and predictable.

6.3

Position effects

Position effects are not always clearly distinguished from other forms of gene silencing. However, position effects are manifest in cis, and, in the classic cases in Drosophila they involve spreading of heterochromatin from nearby loci in such a way that the transgene insertion site is occluded. Due to the stochastic nature of the spreading, position effects sometimes produce a somatically sectored or variegated phenotype. Also, position effects may sometimes reﬂect the activity of nearby enhancers or suppressors, as exempliﬁed by the results of activation tagging experiments (Masaki et al., 2005; Pan et al., 2005; Xu et al., 2005; Yoo et al., 2005). Position effects are generally regarded as sequence independent, in the sense that they do not depend on insertion of multiple transgene copies; nor do they depend on homologies between transgene and endogenous sequences. Gene silencing, on the other hand, is often triggered by interactions between homologous sequences, which can be located either in cis (e.g., within the transgenic locus) or in trans (multiple transgene loci, or homologies with endogenous sequences elsewhere in the genome) (Wolffe, 1997; Henikoff, 1998; Allen et al., 2000; Hsieh and Fire, 2000; Stam and Mittelsten Scheid, 2005). The extent to which position effects inﬂuence transgene expression in plants is currently the subject of some controversy. Activation tagging experiments (Masaki et al., 2005; Pan et al., 2005; Xu et al., 2005; Yoo et al., 2005) clearly demonstrate that at least one kind of position effect can occur when a transgene inserts near a strong enhancer element. However, recent reports (De Buck et al., 2004; Schubert et al., 2004; Nagaya et al., 2005) show that insertions at many different sites in the Arabidopsis genome are expressed similarly when a strong promoter is used and the analysis is restricted to simple, non-rearranged single-copy inserts. In these and

138

REGULATION OF TRANSCRIPTION IN PLANTS

most other experiments, transformants are selected on the basis of drug resistance conferred by a marker linked to the gene of interest, which should prevent recovery of insertions into heterochromatin or other regions of the genome that do not support expression. Francis and Spiker (2005) have shown that such insertions do in fact occur, and can be recovered by screening directly for inserted DNA. Such insertions show that ‘cold spots’ – regions where transgenes are poorly expressed – exist even in the simple, mostly nonrepetitive Arabidopsis genome. It seems likely that such regions occur much more often in the more complex and highly repetitive genomes of typical crop plants.

6.4

Gene silencing

If position effects were the only source of variation in transgene expression, insertions at the same locus should display the same activity in independent transformants. This is not always the case, as elegantly demonstrated by the work of Day et al. (2000). These and other data highlight the existence of gene-silencing mechanisms other than position effects. In many cases, these mechanisms appear to depend on homology within or between transgenes, or between transgenes and endogenous genes. Most current models postulate that these types of gene silencing evolved to protect against invading nucleic acids, either viruses or transposons, and to silence transcription in large blocks of repetitive DNA (Iglesias et al., 1997; Matzke et al., 2000; Miura et al., 2001; Lippman et al., 2003; Volpe et al., 2003; Bender, 2004; Herr et al., 2005; Pontier et al., 2005; Slotkin et al., 2005).

6.4.1

Post-transcriptional gene silencing

Many examples of gene silencing in plants, including the cosuppression phenomena initially described in petunia (Napoli et al., 1990; Van de Krol et al., 1990), involve post-transcriptional gene silencing (PTGS). In PTGS, transcription apparently continues but mRNA fails to accumulate and is thought to be degraded in the cytoplasm. (Transcription measurements in plants usually involve run-on assays, which measure the association of RNA polymerase with a gene of interest, and its ability to elongate transcripts in vitro. Factors controlling elongation in vivo may be lost during nuclear isolation, and so such assays may not quantitatively reﬂect in vivo transcriptional activity.) After its discovery in plants, this type of silencing was demonstrated in nematodes and other animals, where it is commonly referred to as RNAi (for RNA interference) (Matzke and Birchler, 2005; Tomari and Zamore, 2005; Venken and Bellen, 2005; Wassenegger, 2005). It is now known that formation of short double-stranded RNA (dsRNA), often referred to as short interfering RNA (siRNA), is critical to the process. The siRNA is incorporated into the RNA-induced silencing complex (RISC), a protein complex capable of degrading mRNA and simultaneously producing additional fragments of dsRNA. These new siRNAs continue the cycle, resulting in an extremely effective silencing system that can amplify the effect of minute quantities of initiating dsRNA.

MARs AND GENE SILENCING

139

It is also known that once induced, PTGS can spread through a plant, moving through plasmadesmata and in the phloem. However, silencing is not always complete, and spatially heterogeneous, or patchy, phenotypes are commonly observed. In this case, in contrast to position effect variegation, the patterns of active and inactive areas do not necessarily correspond to developmental cell lineages. In both cases, however, spatial heterogeneity can seriously complicate assays in which tissue samples must be taken ‘blindly’, without visualizing the pattern of expression in vivo (Kerschen et al., 2004). Interestingly, although many examples of gene silencing involve multiple-copy insertions, there are many other examples in which PTGS seems to be triggered simply by high-level expression of a single-copy transgene. An excellent example is the work of Que et al. (1997). Readers are also referred to a recent review by Jorgensen (2003). Strong, high-frequency silencing from single-copy transgenes is most commonly observed with constructs designed for high-level protein overexpression. Such data have led to the concept of a threshold above which mRNA would become a template for RNA-dependent RNA polymerase (RDRP), and then be degraded by Dicer and the RISC complex. Constructs not designed for protein overexpression seem not to be silenced by the same mechanism. In these cases, silencing occurs most frequently when integrated transgenes are present as inverted repeats (Que et al., 1997; Stam et al., 1997a), suggesting that dsRNA production may occur without RDRP involvement. In many cases, it is unclear to what extent transgene repeats and rearrangements may have led to the production of dsRNA. However, it is clear that deliberate production of dsRNA from (for example) engineered hairpin constructs (Wesley et al., 2001; Stoutjesdijk et al., 2002; Guo et al., 2003; Lacomme et al., 2003) can lead to efﬁcient RNA silencing.

6.4.2

Transcriptional gene silencing

Transcriptional gene silencing (TGS) can also be homology dependent (Breyne et al., 1992; Meyer et al., 1992; Meyer and Saedler, 1996; Park et al., 1996; Meyer, 2000), although in this case both run-on transcription and cytoplasmic mRNA accumulation are inhibited. Recent work has shown that many of the proteins and protein complexes involved are similar to those involved in PTGS (Sijen et al., 2001). Short dsRNAs appear to play a role in TGS quite similar to their role in PTGS, being incorporated into an RNA-induced transcriptional gene-silencing complex (RITS), which is analogous to the RISC complex involved in cytoplasmic mRNA degradation (Parker et al., 2004; Schramke et al., 2005). Current models postulate that the RITS complex attracts histone and DNA modiﬁcation enzymes to the site of silencing, helping to convert open chromatin into condensed, transcriptionally inactive heterochromatin (Motamedi et al., 2004; Noma et al., 2004; Cam et al., 2005; Schramke et al., 2005). Plate 1 shows an example in which integration of multiple transgene copies resulted in a transcriptionally silenced locus (Probst et al., 2003). In this example, a locus containing 15 copies of a 35S-HPT, some of them rearranged during integration, was expressed in the initial transgenic plant but lost expression in progeny.

140

REGULATION OF TRANSCRIPTION IN PLANTS

The locus is hypermethylated and forms cytologically detectable heterochromatic knobs clearly distinguishable from centromeric heterochromatin. One interesting consequence of recent models of dsRNA-dependent transcriptional silencing is that chromatin must be transcribed in order to be silenced (Martienssen, 2003). It is likely that such transcription occurs at low levels in many, if not all, regions of the genome, even where transcripts do not accumulate.

6.4.3

Repeats and rearrangement effects

Given the role of dsRNA in both major forms of silencing, it is perhaps not surprising that transgenic loci containing multiple rearranged or scrambled copies are especially subject to being silenced, particularly if inverted repeats are present (Cluster et al., 1996; Stam et al., 1997a, 1998; Jacobsen, 1999; Meins, 2000; Muskens et al., 2000; De Buck et al., 2001; Beclin et al., 2002; Matzke et al., 2002; Muller et al., 2002). Inverted repeats in the RNA that reaches the cytoplasm would be targets for cytoplasmic PTGS, while aberrant transcripts that remain in the nucleus may attract the RITS complex and induce transcriptional silencing. A particularly interesting case arises when promoter sequences are transcribed in complex loci. In such cases, dsRNA is produced and transcriptional silencing occurs (Mette et al., 1999; Melquist and Bender, 2003), characteristically in association with methylation of cytosine residues in the promoter. Effects of this sort can occur in trans if there are corresponding promoter sequences elsewhere at the locus or in the genome.

6.5

Matrix attachment regions

Matrix attachment regions (MARs) are operationally deﬁned as DNA sequences that bind to the nuclear matrix. The biological role of MARs has been envisioned as the organization of chromatin into a series of topologically isolated loop domains ranging in size from about 5 to 300 kb of DNA. Although not included in the operational deﬁnition, a number of characteristics have been associated with MARs. They are approximately 1 kb in size. They are AT rich (typically more than 70% AT) and they contain a number of sequence motifs and features (e.g., A-boxes, T-boxes, Drosophila topoisomerase II consensus sequences, ARS consensus sequences, TG/CA-motifs, CT-rich stretches, kinked DNA, and curved DNA) (Cockerill and Garrard, 1986; Gasser and Laemmli, 1986a,b; Amati and Gasser, 1988; Boulikas, 1993, 1995). Even though all these (and more) sequence motifs and features have been found in MARs, it is clear that the simple presence of one or more of the motifs is not sufﬁcient to establish a DNA fragment as a MAR (Michalowski et al., 1999; Liebich et al., 2002). Thus, a number of bioinformatic approaches have been devised with the goal of identifying MARs based on sequence information (Singh et al., 1997; Glazko et al., 2001; http://futuresoft.org/MAR-Wiz/). These bioinformatic approaches rely on sequence motifs previously found in MARs. The problem with this tactic is

MARs AND GENE SILENCING

141

that even though a motif may be present in a MAR, the motif may not be a factor involved in the binding of the MAR to the nuclear matrix. Typically, programs such as MAR-Wiz are used to identify potential MARs in genomes or portions of genomes without subsequent validation of MARs by actual matrix-binding studies (e.g., Rudd et al., 2004). When such validation studies have been carried out (Namciu et al., 2004), MARs identiﬁed by matrix binding and MARs identiﬁed by bioinformatic approaches have not correlated well. There is a value in studies incorporating bioinformatic-based approaches for mapping MARs, but results of such studies should be viewed in light of their limitations. Another characteristic associated with MARs (the characteristic that has probably attracted the most attention) is their ability to increase and stabilize transgene expression. This property was ﬁrst demonstrated in animal cell cultures (Stief et al., 1989) and has been observed in a large number of systems (reviewed by Allen et al., 2000 and Bode et al., 2000). The operational deﬁnition and general characteristics of MARs noted above are useful to a degree, but ambiguous for several reasons. First, binding studies are generally carried out in vitro, with isolated nuclear matrices. Thus, there is no compelling evidence that the DNA sequences that are operationally deﬁned as MARs actually serve to anchor loop domains in vivo. Second, although there is a huge volume of literature describing the nuclear matrix both microscopically and biochemically (see Nickerson, 2001, for review), the existence of such a network of nucleoprotein ﬁbers has been controversial (Pederson, 1998, 2000; Hancock, 2000, 2004). Some observers counsel neither full-ﬂedged acceptance nor rejection of the reality of the nuclear matrix, but rather the adoption of an open mind (Martelli et al., 2002; Jackson, 2003, 2005). Third, the deﬁnition of a MAR as a matrix-binding DNA sequence has a limitation in that all DNA sequences will bind to the biochemically deﬁned nuclear matrix in the absence of competitor DNA (Michalowski et al., 1999). Even DNA sequences that bind in the presence of competitor DNA have a continuum of afﬁnities ranging from barely detectable to very strong (Brun et al., 1990; Michalowski et al., 1999). Furthermore, the concentration of competitor DNA and its characteristics will determine the relative afﬁnity for the nuclear matrix of any MAR candidate. Thus, it is impossible to set meaningful cutoffs to distinguish MARs from non-MARs. This becomes an issue when bioinformatic approaches are used to identify MARs in silico. These approaches yield a ‘matrix association potential’, but ‘potential’ denotes potential to be a MAR and is not an estimate of binding strength. When predicted MARs are checked for validity by binding experiments, the program used can (1) correctly identify a MAR, (2) identify a DNA sequence as a MAR even though the DNA has negligible afﬁnity for the nuclear matrix, or (3) fail to identify a sequence as a MAR even though it has appreciable afﬁnity for the nuclear matrix (Glazko et al., 2001). How successful a program will be depends, in part, on how great the afﬁnity of a DNA sequence for the nuclear matrix must be in order for it to be judged a MAR. One approach to identifying MARs based on sequence alone depends on calculated DNA duplex destabilization energy rather than the density and arrangement of sequence motifs (Benham et al., 1997). This approach shows considerable promise

142

REGULATION OF TRANSCRIPTION IN PLANTS

because quantitative estimates of stress-induced DNA duplex destabilization correlate well with experimentally measured binding strengths (Bode et al., 2006). The fourth ambiguity relating to MARs concerns their ability to increase and stabilize transgene expression. Although many studies have documented such an effect on transgene expression (reviewed in Allen et al., 2000 and Bode et al., 2000), augmentation of transgene expression has not always been noted and the overall picture is complex (Breyne et al., 1992; Bonifer et al., 1994; Huber et al., 1994; Phi-Van and Str¨atling, 1996; Vaucheret et al., 1998; Brouwer et al., 2002; De Bolle et al., 2003; Sidorenko et al., 2003). The complexity of MAR augmentation and stabilization of transgene expression is the subject of this review.

6.6

MARs and transgene expression

MARs are known to affect the expression of transgenes. Our early experiments, such as shown in Plate 2, showed effects as high as 60-fold when tobacco suspension culture cells were transformed by bombardment (Allen et al., 1996). Subsequent experiments in which plants were used in place of suspension cells and different methods of DNA delivery were tested have shown positive MAR effects in most cases, although the magnitude of the effect is usually much smaller, more on the order of a three- to tenfold increase in expression. Reports of MAR effects in various plant systems are summarized in Table 6.1. Multiple copies of the transgene were introduced in the early experiments, and it is likely that rearrangements often occurred during microprojectile-mediated transformation. On the basis of recent data highlighting the role of complex repeats in TGS and heterochromatin formation (Stam et al., 1997b; Henikoff, 1998; Hsieh and Fire, 2000; Volpe et al., 2002; Ascenzi et al., 2003; Fransz et al., 2003; Martienssen, 2003; Probst et al., 2003; Matzke and Birchler, 2005; Pecinka et al., 2005), it seems likely that this type of transformation favors transcriptional silencing. In addition, Mitsuhara et al. (2002) have shown that rapidly dividing cells show reduced levels of post-transcriptional silencing. If MARs protect against TGS but not PTGS, especially large MAR effects would be expected in situations in which TGS is strong and PTGS is weak. In such cases, strong TGS would reduce transcription of control transgenes lacking MARs, while weak PTGS would allow full expression of MAR constructs that might otherwise be inhibited by cytoplasmic mRNA degradation. More evidence for this hypothesis is presented in the following paragraphs. By comparison, transformation methods leading to lower copy numbers and less rearrangement would be expected to minimize TGS, while assays involving mostly nondividing cells in expanded leaves would be expected to be strongly inﬂuenced by PTGS.

6.6.1

MARs reduce gene silencing

In early reports, it was shown that only relatively small MAR effects are seen in transient expression assays, which are conventionally regarded as measuring the expression of transgenes prior to integration in the chromosome. These data were

Chicken (A element)

Tobacco (RB7) Tobacco (RB7) Tobacco (RB7) Arabidopsis (ARS-like)

Chicken (A element)

Tobacco (RB7) Yeast (ARS1) Tobacco (RB7)

Tobacco plants

Tobacco plants

Tobacco cells Poplar explants Tobacco leaf disks Tobacco plants

Maize cells

Rice plants

Tobacco plants

35S-GUS Phaseolin-GUS

Chicken (A element) Bean (Phaseolin)

Tobacco plants Tobacco cells Tobacco plants

35S-GUS 35S-GUS 35S-GUS

35S-cab1-GUS

35S-GUS 35S-GUS 35S-GUS 35S-GUS

Enh35S-GUS

Nos-GUS Nos-GUS Heat shock-GUS 35S-GUS Lhca3-GUS

Soybean (P1) Human (β-globin) Soybean (Gmhsp17.6-L) Yeast (ARS1) Chicken (A element)

Tobacco cells

Promoter-reporter

Source of MAR

Biolistic Biolistic Biolistic

Biolistic

Biolistic Agrobacterium Agrobacterium Agrobacterium

Agrobacterium

Agrobacterium Agrobacterium

Agrobacterium Biolistic Agrobacterium

Agrobacterium

DNA transfer

Effect of ﬂanking MARs on transgene expression and variability in plants and plant cells

Plant system

Table 6.1

2.5-fold increase 3-fold increase 2-fold increase

60-fold increase 10-fold increase Small 5- to 10-fold increase 36-fold increase

2-fold increase

3-fold increase 3-fold increase

Small decrease No effect 9-fold increase 12-fold increase 4-fold increase

Effect on expression level

Small Small Small

Increase

No effect Small Small No effect

2-fold decrease

7-fold decrease 2-fold decrease

Small decrease Small decrease No effect Small 3-fold decrease

Effect on expression variability

(Continued)

¨ Ulker et al. (1999)

Odell and Krebbers (1998) Vain et al. (1999)

Liu and Tabe (1998)

Van der Geest et al. (1994) Mlyn´arov´a et al. (1995) Allen et al. (1996) Han et al. (1997)

Sch¨ofﬂ et al. (1993) Allen et al. (1993) Mlyn´arov´a et al. (1994)

Breyne et al. (1992)

Reference

Lhca3-GUS 35S-LUC 35S-LUC 35S-LUC Rsyn7-GUS Apt-Lc-cDNA Apt-Lc-cDNA 35S-LUC Lhca3-GUS

Chicken (A element) Yeast (ARS1) Maize (Adh1 5 ) Maize (Mha1 5 ) Maize (Adh1 5 ) Arabidopsis (HSC80 5 )

Yeast (ARS1) Chicken (A element)

Chicken (A element)

Arabidopsis plants

Tobacco plants

Maize cells

Enh35S-GUS

Chicken (A element)

Chrysanthemum plants

35S-GUS 35S-GUS 35S-NPTII Enh35S-LUC

Tobacco (RB7) Synthetic Tobacco (TJ1) Chicken (A element)

Actin-GUS

Tobacco (RB7)

Tobacco cells Tobacco plants Tobacco cells Tobacco plants

Enh35S-GUS:nptII Actin-GFP

Tobacco (RB7) Tobacco (RB7)

Pine callus Rice plants

Promoter-reporter

Source of MAR

Agrobacterium

Agrobacterium Biolistic Biolistic Biolistic Biolistic Agrobacterium

Agrobacterium

Biolistic Agrobacterium Biolistic Agrobacterium

Biolistic

Agrobacterium Biolistic

DNA transfer

None

Slight decrease None

None 5.8-fold 26.8-fold 1.5-fold 87-fold decrease None

3- to 4-fold 3.3- to 18-fold increase 376- to 650-fold increase 42-fold increase 2.3 to 3.8-fold Slight 0- to 2-fold decrease None

Effect on expression level

Effect of ﬂanking MARs on transgene expression and variability in plants and plant cells (Continued)

Plant system

Table 6.1

ND 1- to 15-fold decrease 1- to 18-fold decrease

Slight increase None None None ND ND

ND Slight increase ND None to slight increase None

Slight

Decrease Slight

Effect on expression variability

Mlyn´arov´a et al. (2002)

Holmes-Davis and Comai (2002)

Brouwer et al. (2002)

Mendu et al. (2001) Nowak et al. (2001) Shimizu et al. (2001) Van Leeuwen et al. (2001) Annadana et al. (2002)

Levee et al. (1999) (Cheng et al., 2001)

Reference

Tobacco (RB7)

Tobacco (RB7)

Chicken (A element)

Maize (P1-rr)

Tobacco cells

Tobacco cells

Cacao plants

Tobacco plants

Maize plants

Sorghum Rice plants

Tobacco (RB7) Synthetic (SM1)

Maize (Adh1 MAR)

Tobacco (5 CHN5)

Tobacco plants Arabidopsis plants

Rice plants

Soybean (P1) Petunia (TBS) Tobacco (RB7) Yeast (ARS1) Tobacco (RB7) Chicken (A element)

Barley plants

(P1-rr,WP, Rsyn7)-GUS (P1-rr,WP, Rsyn7)-GUS Ubiquitin-GUS Gos2-GUS

Enh35S-GUS

35S-NPTII 35S-GUS 35S-GUS 35S-GUS 35S-GUS 35S-GUS Mas-GUS 35S-GUS (MAR-ﬂanked) 35S-GUS (MAR-5 ) 35S-GUS 35S-GUS AtAhas-GUS PsFed1-GUS GmHspL-GUS Nos-GUS Ocs-GUS E12omega-GFP

Biolistic Biolistic

Biolistic

Agrobacterium

Agrobacterium

Biolistic

Agrobacterium

Biolistic Agrobacterium

Biolistic

Biolistic

2-fold increase 0- to 1.9-fold

None

None None

None

None

ND

ND ND ND ND ND ND ND ND Slight decrease

10-fold None 5.3-fold None None 3.1-fold 4.9-fold 15.3-fold 2.2-fold MAR blocked RNAsilencing None

4.6-fold None None None ND None None ND

3.4-fold None 2.5-fold 3.1-fold Slight None None 15-fold

(Continued)

Able et al. (2004) Van der Geest et al. (2004)

Sidorenko et al. (2003)

Maximova et al. (2003) Mlyn´arov´a et al. (2003)

Mankin et al. (2003)

(Fukuda and Nishikawa, 2003)

(Ascenzi et al. (2003) De Bolle et al. (2003)

Vain et al. (2002)

Petersen et al. (2002)

Synthetic (SM1) Maize (Adh1 MAR) Chicken (A element) Chicken (A element) Chicken (A element) Tobacco (RB7) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Tobacco (TM-2) Chicken (A element)

Arabidopsis plants Maize Arabidopsis plants (WT) Arabidopsis plants (sgs2) Arabidopsis plants (sgs3) Tobacco cells Rice calli

Rice plants

Rice roots

Rice leaves

Source of MAR Act2-GUS Ubiquitin-GUS 35S-GUS 35S-GUS 35S-GUS 35S-GFP 35S-GUS Ubi-GUS PNZIP-GUS 35S-GUS Ubi-GUS PNZIP-GUS 35S-GUS Ubi-GUS PNZIP-GUS Rice SBE 1-glgB

Promoter-reporter

Agrobacterium

Agrobacterium Agrobacterium

Agrobacterium Biolistic Agrobacterium

DNA transfer 1.6- to 3.7-fold None 1.7-fold decrease 5-fold 12-fold 2- to 3.7-fold 3.2-fold 4-fold 2.3-fold 5.4-fold 9.9-fold 4-fold 6.2-fold 7.8-fold None Transgenic rice had twofold greater branching ratio

Effect on expression level

Effect of ﬂanking MARs on transgene expression and variability in plants and plant cells (Continued)

Plant system

Table 6.1

None Increase None None None Not determined None None None None None None None None None None

Effect on expression variability

Kim et al. (2005)

Halweg et al. (2005) Xue et al. (2005)

Torney et al. (2004) Butaye et al. (2004)

Reference

Tobacco (RB7)

Tobacco (RB7)-full, direct repeats

Tobacco plants

Tobacco cells

Rice leaves

540-bp 5 end of RB7 MAR

BP-MAR 1300 bp of Chicken (A element) Tobacco (RB7)

Rice plants

35S-GUS

35S-GUS

TetOp35S-LUC

35S-Tomato Spotted Wilt Virus Coat protein

Act1-GFP

Biolistic

Biolistic

Agrobacterium

Agrobacterium Signiﬁcantly greater resistance in R1 through R4 generations Signiﬁcant increase, less silencing with delayed induction Full RB7 MAR resulted in a 77-fold increase in transgene expression Flanking 540-bp of 5 RB7 MAR in various orientations had no effect

None

All RB7 MAR constructs had twofold less variation

Not determined

Copy number dependence Not determined

Verma et al. (2005)

Abranches et al. (2005)

(Levin et al., 2005)

Oh et al. (2005)

148

REGULATION OF TRANSCRIPTION IN PLANTS

thus interpreted as indicating that at least the majority of the MAR effect was seen only after integration, and thus that MARs were not simply acting as classic enhancers of transcription. Subsequent reports showed that MARs reduced the loss of ¨ transgene expression from one generation to the next (Conner et al., 1998; Ulker et al., 1999; Vain et al., 1999). As the copy number or Southern pattern of the integrated transgenes did not change, this loss can be attributed only to gene silencing. Thus MARs are considered to reduce gene silencing, rather than merely stimulating transcription. MARs have also been reported to reduce the loss of virus resistance in tobacco plants containing a transgene engineered to induce resistance by producing transcripts homologous to viral RNA (Levin et al., 2005), a result most consistent with a protective effect of MARs at the transcriptional level. Consistent with this hypothesis, Ascenzi et al. (2003) showed that a viral suppressor of PTGS relieves silencing in tobacco plants containing MAR constructs, but not in controls without MARs. Thus, most of the available data are consistent with the hypothesis that MARs protect against transcriptional silencing, but do not affect PTGS (Butaye et al., 2004).

6.6.2

MARs have a dual effect

Both position effects and gene silencing are known to give rise to variegated or patchy expression (Meyer et al., 1992; Neuhuber et al., 1994; Van Blokland et al., 1994; Ten Lohuis et al., 1995; Chinn et al., 1996; Que et al., 1997). Most often, however, assays are conducted in a way that averages large populations of cells, entire leaves, etc., and it is usually impossible to distinguish changes in the percentage of cells affected from changes in the intensity of expression in individual cells. This question is important to the interpretation of MAR effects as well. If MARs reduce the statistical likelihood of gene silencing in each cell generation, we might expect an increase in the percentage of cells with detectable expression, while a uniform increase in the intensity of expression in all cells might reﬂect other mechanisms, such as an increase in chromatin availability or polymerase loading. We have addressed this problem by adapting ﬂow cytometry to analyze green ﬂuorescent protein (GFP) expression on a cell-by-cell basis in populations of tobacco protoplasts (Halweg et al., 2005). In the past, such measurements have been complicated by the fact that plant protoplasts lose GFP when membrane integrity is compromised, leading to artiﬁcially high estimates of nonexpressing cells. However, we were able to take advantage of the fact that compromised cells are selectively stained with propidium iodide to eliminate this population from the analysis. The resulting proﬁles provide a good indication of the statistical proﬁle of GFP expression. Figure 6.1 shows an example of data from these experiments. Clearly, a major effect of MARs is to decrease the fraction of cells that appear to be silenced – i.e., the fraction of cells that show little or no GFP expression. This result is consistent with the idea that MARs decrease the likelihood of silencing, rather than increasing expression in unsilenced cells. In addition, however, the GFP proﬁles for the MAR lines in Figure 6.1 have a shoulder on the high end, indicating the presence of a subpopulation of cells in which expression is higher than in any of the cells in

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Figure 6.1 The RB7 MAR increases the likelihood and magnitude of GFP expression in cultured cells. NT1 tobacco suspension cells were transformed by Agrobacterium containing a CaMV:smRSGFP reporter cassette. The cassette was ﬂanked either by two copies of the RB7 MAR (MGFPM, dark grey) or by two copies of an 1194-bp fragment of lambda DNA, which served as a spacer control (LGFPL, light grey). The black line represents control cells transformed with the GFP cassette alone. Each line represents average ﬂuorescence histograms of 30 individual cell lines, each of which was measured individually by ﬂow cytometry. GFP expression, measured in relative ﬂuorescence units (RFU), is shown on the X axis and the number of cells with a given ﬂuorescence intensity is shown on the Y axis. Cells with ﬂuorescence lower than 17 RFU (vertical line on X axis separating negative from positive) are considered negative for GFP expression, as untransformed controls display ﬂuorescence at this level. (This ﬁgure is reproduced, with permission from the American Society of Plant Biologists, from Figure 6A in Halweg et al. (2005).

a control population. Thus, MARs appear to have a dual effect. They reduce the fraction of cells in which silencing occurs, while simultaneously promoting higher levels of expression in some cells.

6.6.3

Hypotheses to explain MAR effects

Early models to explain MAR effects on animal cells postulated that MARs functioned as boundary elements, anchoring the ends of chromosomal domains and preventing the spread of heterochromatin into transgenes ﬂanked by MARs. However, this class of model works best in the context of position effects, such as the canonical position effect variegation phenomenon in Drosophila (Dorer and Henikoff, 1994; Csink and Henikoff, 1996; Dernburg et al., 1996; Walters et al., 1996; Girard et al., 1998). As noted above, much of the variation in transgene expression that occurs in plant cells seems to involve homology-dependent gene silencing, rather than position effects. This fact requires us to consider alternatives to the boundary element model. We have previously discussed several possible models (Allen et al., 2000); only two will be mentioned here. First, the ‘carpet tack’ hypothesis postulates that MARs

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Figure 6.2 The terminator hypothesis. The model envisions complex loci containing transgene and vector DNA in various orientations. (A) In the absence of MARs, transcription initiates correctly but in cases of poor termination continues into the surrounding DNA, which can produce promoter transcripts or inverted repeats and activate one or more RNA-silencing pathways. (B) When MARs ﬂank a transgene, transcriptional read-through and subsequent silencing may be reduced if the MARs function to terminate transcription. An extension of the terminator hypothesis (not shown) envisions transcripts initiating in surrounding chromatin and extending into the transgene locus, with subsequent silencing. MARs might also prevent such transcripts from reaching the transgene.

keep a transgene locus physically close to the nuclear matrix, where there may be higher concentrations of RNA polymerase and transcription factors, and that they may also constrain the chromatin ﬁber to reduce pairing interactions within complex multicopy loci. Another attractive hypothesis postulates that MARs act as transcriptional terminators, as illustrated in Figure 6.2. This terminator function might prevent transcription from extending from one transgene to another in a complex locus (reducing the potential for inverted repeat formation in the transcripts) or from the transgene into adjoining repeated sequences in the genome. Repeat transcripts and dsRNA that may be produced in this manner might attract the RITS complex and cause heterochromatin formation and TGS, while MAR effects might result from minimizing the production of dsRNA or other aberrant RNAs. Support for this class of model comes from a report by Nap’s group (Mlyn´arov´a et al., 2003), who used site-speciﬁc recombinases to excise a MAR from a transgenic locus in tobacco after insertion and initial analysis. After excision of the MAR, the locus became more vulnerable to silencing. The authors were able to detect transcription extending into adjacent repeated DNA, as well as small dsRNAs similar to those associated with RNA-mediated silencing. Both of these hypotheses are consistent with results indicating that MARs work more effectively in cis than in trans. Vaucheret et al. (1998) showed that strong trans-silencing loci could also silence genes ﬂanked by MARs. Ascenzi et al. (2003) detected a protective effect of MARs against other silencing loci, weaker than those

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tested by Vauchert et al., but conﬁrmed the major observation that MAR effects are most prominent in cis. An additional prediction of our hypothesis is that MARs would protect the transcriptional potential of genes with low expression levels, whereas actively transcribed genes would be susceptible to silencing by PTGS. To test this hypothesis, we used a tetracycline inducible promoter system (Abranches et al., 2005) in which a noninduced luciferase reporter transgene was stably transformed into tobacco NT1 cells (Nicotiana tabacum), which were grown for many division cycles. The cells were then induced and transgene expression was compared between the control and the MAR-ﬂanked transgenes. Nearly 85% of the lines with the MAR-ﬂanked transgenes could be induced, in contrast to only 40% induction observed in the two groups of control lines (Abranches et al., 2005).

6.7

MAR effects in Arabidopsis

Up to this point, our discussion has focused primarily on work with tobacco and other plants that have relatively large, repetitive genomes. Given the importance of Arabidopsis as a model for plant molecular genetics, we and others have been interested in examining MAR effects in this species as well. At this time, in wildtype Arabidopsis, there are three reports showing either no effect or a negative effect of MARs (Holmes-Davis and Comai, 2002; De Bolle et al., 2003; Butaye et al., 2004) and one report of a two- to fourfold increase in expression (Van der Geest et al., 2004) (Table 6.1). Might this small effect be because there is little transcriptional silencing in this extremely small, mostly nonrepetitive genome? Position effects have been reported to be minimal in Arabidopsis (Schubert et al., 2004; Nagaya et al., 2005), but examples of silencing, both TGS and PTGS, are widely reported (Mittelsten Scheid and Paszkowski, 2000; Melquist and Bender, 2003; Probst et al., 2003) and Arabidopsis mutants are, in fact, the main tools for molecular genetic analysis of silencing (Amedeo et al., 2000; Mittelsten Scheid and Paszkowski, 2000; Morel et al., 2000; Mourrain et al., 2000; Steimer et al., 2000; Miura et al., 2001; Beclin et al., 2002; Tariq et al., 2002; Turnage et al., 2002; Vaistij et al., 2002; Gazzani et al., 2004; Muangsan et al., 2004; Kidner and Martienssen, 2005; Yoshikawa et al., 2005). However, it remains possible that TGS is less important – at least relative to PTGS – in Arabidopsis than in other species. In addition, differences in analytical methods may also play a role. Gene expression assays in Arabidopsis, unlike those with other model systems, commonly involve extracting whole plants rather than isolated organs, and are often carried out at advanced developmental stages. Our previous work with tobacco had shown that suppressors of PTGS could relieve silencing of MAR constructs, but not control constructs lacking MARs, leading to the supposition that strong PTGS could ‘hide’ the otherwise signiﬁcant MAR effects at the transcriptional level (Ascenzi et al., 2003). We therefore set out to test the hypothesis that PTGS might suppress gene expression in mature Arabidopsis plants

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so that MAR effects would not be detected, whereas they might be detected in young seedlings or certain growth conditions in which PTGS activity is lessened.

6.7.1

Testing the effect of developmental stage

We used the RB7 MAR from tobacco, as in our previous work, and carried out Agrobacterium-mediated transformation by the ﬂoral dip procedure (Clough and Bent, 1998). Agrobacterium transformation is expected to give mostly single- and low-copy insertions with little rearrangement. Our expectation is that it should therefore lead to less gene silencing in control constructs and corresponding smaller MAR effects than those that we have seen with microprojectile transformation. By using a luciferase reporter (Mankin et al., 1997) we were able to examine transgene expression in the same plants as they progressed through different developmental stages. Our results (Callaway et al., in preparation) showed a strong inﬂuence of developmental stage. MAR effects at the seeding stage were consistently positive, averaging about threefold. At the rosette stage, however, the MAR effect was more variable, and a statistically robust effect was not detected. Later in development, at the bolting stage, we saw a statistically signiﬁcant negative MAR effect. In another study, this time with GUS as a reporter gene (Francis et al., in preparation), we found that the RB7 MAR increased reporter gene expression in leaf tissues of Arabidopsis plants measured 14 days after germination. The increases in transgene expression were highly statistically signiﬁcant, but as expected they were only in the twofold range as compared to the tenfold or greater increases observed in tobacco cells in culture. The MAR-mediated increases in reporter gene expression were lost when measurements were made on leaves of 28-day-old plants, and by 42 days a negative MAR effect was sometimes noted. These effects were consistent in T2, T3, and T4 generations of transgenic Arabidopsis plants.

6.7.2

How might MARs decrease net transgene expression?

How can we account for developmental variation in the magnitude of MAR effects? One hypothesis is based on the observations that suppressors of post-transcriptional silencing (Ascenzi et al., 2003) or mutants that block PTGS function ((Butaye et al., 2004) can ‘rescue’ expression that would otherwise be masked by posttranscriptional silencing. When coupled with the observations of Mitsuhara et al. (2002) these results provide a likely explanation of the developmental variation we see. Mitsuhara et al. showed that PTGS of a luciferase transgene in tobacco is greatly reduced in proliferating tissues such as meristematic tissue and developing leaves. In young seedlings, therefore, we expect MAR effects on transcriptional activity to be reﬂected in reporter gene expression, with relatively little interference from PTGS. Later in development, however, the onset of severe PTGS in mature tissues may counteract transcriptional stimulation, so that MAR effects are no longer observed. Mitsuhara et al. (2002) also showed that PTGS was reduced in callus cultures, a result that may help to explain why some of the largest MAR effects have been seen in rapidly dividing suspension cultures (Allen et al., 1993, 1996, 2000).

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Interactions between transcriptional and post-transcriptional effects may also explain the instances in which we see a negative inﬂuence of MARs. Suppose, for example, that strong PTGS is triggered when transcription (or mRNA production) exceeds a certain threshold. If MARs increase transcription (or reduce TGS), transgene mRNA production might exceed the threshold more often in the case of MAR constructs than in controls. In such cases, a positive MAR effect on transcription would lead to increased PTGS and a decrease in steady state mRNA abundance.

6.7.3

MAR effects in PTGS mutants

Recently, the relative importance of MAR effects and PTGS has been systematically addressed by Butaye et al. (2004), who analyzed expression of MAR constructs in Arabidopsis plants carrying the either sgs2 or sgs3 (suppressor of gene silencing) mutations, which block PTGS. Although little or no MAR effect could be seen in wild-type plants, mutant lines transformed with the same constructs showed large (ca. ﬁvefold) MAR effects. The use of MARs with PTGS mutations had a multiplicative effect, so that transgene expression was increased 35-fold relative to wild-type controls. This combination, which is currently available for licensing as the ‘MARs Plus’ system (http://www.pbltechnology.com/), seems to hold great promise for protein expression or metabolic engineering studies.

6.8

Conclusions

In summary, our own data and our reading of the literature lead us to conclude that MARs increase both the frequency and the intensity of transgene expression in populations of transformants. We believe this effect is mostly or entirely at the level of TGS, and that it is heritable over multiple plant generations. The observed effect of MARs on mRNA abundance or reporter gene expression is strongly affected by variations in post-transcriptional silencing, which can be strongly inﬂuenced by developmental processes as well as by viral suppressor proteins and mutations in host genes. Under certain circumstances, MAR-mediated increases in transcription may trigger enough PTGS to create an overall negative effect on gene expression. However, by combining MAR constructs with mutations or suppressors of PTGS it is possible to achieve high levels of protein expression that are expected to be developmentally and genetically stable.

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7 Polymerase I transcription Julio S´aez-V´asquez and Manuel Echeverr´ıa

7.1

Introduction

Regulation of RNA polymerase I (pol I) transcription is an important mechanism in controlling the abundance of ribosomes (Bailey-Serres, 1998; Fatica and Tollervey, 2002; Fromont-Racine et al., 2003), and thereby in controlling the protein synthetic capacity of the cell. In actively growing animal and yeast cells, ribosomal RNA synthesis driven by RNA pol I represents about 50% of total cellular RNA production (Warner, 1999; Raska et al., 2004). Stimulation of rRNA transcription can be due to either a higher rate of transcription of active genes or an increase in the number of active rRNA genes (Warner, 1999; Grummt, 2003; Moss, 2004; Russell and Zomerdijk, 2005). Plant cells can employ diverse mechanisms to control rRNA synthesis, from silencing individual rRNA genes (collectively known as rDNA) to silencing of complete rDNA loci, known as nucleolus organizer regions (NORs), which contain hundreds or even thousands of rRNA genes. The development of genomics in Arabidopsis thaliana and other plant species coupled with biochemical explorations has helped to include plants at the forefront of research aimed at understanding rRNA gene regulation in eukaryotes. In this chapter, we review the cis- and trans-acting elements that regulate transcription of rDNA by RNA pol I and the responses of rRNA genes to general and speciﬁc plant regulatory signals.

7.2

Organization of rRNA genes

In eukaryotes, ribosomal RNA genes are arranged in simple head-to-tail tandem arrays in copy numbers ranging from several hundred in mammals to several thousand in plants (Long and Dawid, 1980). The rRNA genes clustered at a single locus comprise NORs, so named because the nucleolus, the site of ribosome synthesis, is organized around active rRNA genes during interphase (Hernandez-Verdun, 2005; Lam et al., 2005; Shaw and Doonan, 2005). Each rRNA gene transcription unit consists of sequences encoding a precursor transcript that includes the 18S, 5.8S, and 25S structural rRNAs, and is separated from the adjacent gene in the array by an intergenic spacer (IGS) (Pikaard, 2002; Grummt, 2003). In plants, as in animals, coding sequences for the three structural rRNAs are very highly conserved between even distantly related species, but the IGS and sequences that are removed during processing, including the internal

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transcribed spacers (ITS) and the external transcribed spacers (ETS), are much less well conserved (Reeder, 1992; Cordesse et al., 1993; Da Rocha and Bertrand, 1995) (Figure 7.1). Analysis of complete IGS sequences reveals considerable length and sequence heterogeneity in different plant species, including radish (Delcasso-Tremousaygue et al., 1988), wheat (Vincentz and Flavell, 1989), A. thaliana (Gruendler et al., 1991), rice (Cordesse et al., 1993), Brassica (Tremousaygue et al., 1992; Da Rocha and Bertrand, 1995), Nicotiana (Borisjuk et al., 1997), and Solanum species (Volkov et al., 2003). However, all ribosomal IGS contain repeated sequences. IGS organization in plant rRNA genes resembles IGS organization in most higher eukaryotes, including at least one array of tandemly repeated sequences located upstream from the transcription initiation site (TIS). In Xenopus (Pikaard and Reeder, 1988) and mouse (Pikaard et al., 1990a), repeated sequences in this location have been shown to possess enhancer activity, increasing the expression of the adjacent promoter after injection into frog oocytes or embryos or after transfection into cultured cells. Though Arabidopsis spacer repeats cloned adjacent to a Xenopus rRNA gene promoter act as enhancers in frog oocytes (Doelling et al., 1993), there is no evidence that they have analogous enhancer activity in plant cells (Wanzenbock et al., 1997). Nonetheless, questions persist as to whether or not IGS heterogeneity affects rRNA transcription, possibly playing a role in the differential activation or silencing of rDNA genes inherited from the different parents in interspeciﬁc hybrids (nucleolar dominance) and/or in stimulating rRNA transcription levels among active rRNA genes. Other studies have shown that the IGS, in addition to possessing rDNA transcription regulatory elements, contains origins of replication as well as barriers to replication fork progression (Hernandez et al., 1993). As IGS sequences have diverged rapidly, even between closely related species, a major question is whether the trans-acting factors implicated in these different roles have coevolved with the interacting rDNA sequences.

7.3

Ribosomal RNA transcription and the nucleolus

Biogenesis of ribosomes takes place in the most prominent subnuclear structure: the nucleolus (Scheer and Hock, 1999; Lam et al., 2005). Here, the tandem rRNA genes encoding the 18S, 5.8S, and 25S structural rRNAs are transcribed by RNA pol I as a precursor or pre-rRNA, which is then processed into mature forms that assemble with ribosomal proteins to form ribosome particles (Shaw and Jordan, 1995; Gerbi et al., 2003; Raska et al., 2004). The driving force for the assembly of the nucleolus is transcription of the tandem rRNA gene repeats, as has been shown conclusively in yeast (Oakes et al., 1998; Trumtel et al., 2000) and Drosophila (Karpen et al., 1988) by the assembly of nucleoli at active rRNA genes integrated at ectopic locations. The synthesis of rRNA is completely inhibited during mitosis, when nucleoli disassemble and the rDNA is arranged in a partially condensed form at the NORs. When rRNA synthesis resumes at the end of mitosis, nucleoli reassemble (Hernandez-Verdun et al., 2002; Shaw and Doonan, 2005).

Figure 7.1 Schematic cartoon of rDNA gene repeats transcribed by RNA polymerase I (pol I). The top portion shows tandemly arrayed rDNA genes separated by intergenic spacers (IGSs). ‘T’ indicates potential terminator sites. In the middle part, an enlarged rDNA unit, delimited by successive terminator, is presented, with positions of the gene promoter (closed box) and DNA repeat elements found in all plant species. The primary rRNA (pre-rRNA), transcribed from the transcription initiation site (TIS) and containing18S, 5.8S, and 25S rRNA (gray boxes) sequences separated by the external transcribed spacers (ETS) and internal transcribed spacers (ITS), is shown in gray. In A. thaliana, two spacer promoters (open boxes) are located between the repeat elements containing Sal I restriction sites. In the bottom part, the A. thaliana rRNA gene promoter is enlarged to show the minimal sequences required to initiate in vivo- and in vitro-speciﬁc RNA pol I transcription (from −55 to +6). The initiator element TATATAGGGGG (+1 italicized) characterized in A. thaliana is highly similar to sequences surrounding putative transcription sites in different plants species. The B. oleracea RNA pol I holoenzyme binds and protects the rDNA promoter region from −30 to +20 (black rectangle) and initiates in vitro speciﬁc transcription from +1.

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The basic structure of the nucleolus can be divided into the ﬁbrillar center (FC), dense ﬁbrillar component (DFC), and granular component (GC) (Thiry and Lafontaine, 2005). Even though the relationships between the function and organization of plant and animal nucleoli seem to be well conserved, the nucleolar ultrastructure is very different in these organisms. Whereas in animal nucleoli the FC are surrounded by dense, relatively small regions of DFC (L´eger-Silvestre and Gas, 2004; Mosgoeller, 2004), in plants the DFC is extensive and can occupy most of the nucleolar volume (Shaw and Doonan, 2005). It has been accepted for some time that ribosome biosynthesis occurs in a vectorial pattern within the nucleolus. The transcription of pre-rRNA takes place in the FC, the early processing steps of pre-rRNA occur in the DFC, and the later processing and RNA modiﬁcation steps, together with the formation of preribosomal particles, take place in the GC. However, the distribution of sites of active rDNA transcription inside the nucleolus remains somewhat controversial. In animal cells, different research groups have localized active ribosomal genes either in the FC and FC/DFC border zone or in the DFC together with the DFC/FC (Raska, 2003; Thiry and Lafontaine, 2005). In plant cells, the site of rRNA transcription is proposed to be in the border zone area between the FC and the DFC (de Carcer and Medina, 1999; Gonzalez-Melendi et al., 2001; Tao et al., 2001a,b). Many years ago, Miller and Beaty (1969) used a chromatin-spreading technique to visualize active rRNA genes by transmission electron microscopy, revealing ‘Christmas tree’ structures (Miller and Beaty, 1969), in which the trunks of the trees are rDNA and the branches are nascent pre-rRNA transcripts. Since then, similar Christmas tree structures have been visualized in many different species, including plants (Shaw et al., 2002). However, it has been very difﬁcult to determine whether or not this structure occurs in the nucleolus in vivo. Shaw et al., using bromouridine labeling, presented evidence that rDNA transcription units are linear, compacted Christmas trees in intact Pisum sativum nucleoli (Gonzalez-Melendi et al., 2001). Importantly, this work clearly revealed the DFC as the subnucleolar domain containing the active transcription units, whereas the FC serves as a reserve of inactive or very weakly expressed genes (Shaw and Doonan, 2005). The work of Shaw and collaborators also revealed that only 200–300 rRNA genes are active in meristematic tissue of root tips of P. sativum. This is only ∼5% of the total number of rRNA genes in this species (Gonzalez-Melendi et al., 2001; Shaw et al., 2002). However, rRNA gene silencing seems not to be fully randomized in the NORs. Studies by Caperta et al. in rye, a diploid species with only one pair of homologous NOR, demonstrate that at metaphase, NORs always show condensed inactive rDNA chromatin in the centromere proximal region whereas the more active rDNA chromatin is located in the NORs region that decondenses progressively toward the satellite (Caperta et al., 2002). There is evidence that differential expression of rDNA genes at the different rye NORs is established after each cell division or reﬂects patterns that are imposed early in development and are then maintained (Caperta et al., 2002). Consistent with the latter view, numerous studies in mammalian cells have shown that during mitosis the pol I machinery is associated only with NORs that were transcribed in the previous interphase cycle

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and that will be transcriptionally active in the next cell cycle (Scheer and Rose, 1984; Roussel et al., 1993; Gebrane-Younes et al., 1997).

7.4

rRNA gene promoters and transcription factors

In animals and yeast, rRNA gene promoters share a common bipartite structure consisting of a core promoter (CP) sequence, which includes the TIS, and an upstream control element (UCE), which enhances rRNA transcription (Grummt, 2003; Moss, 2004; Russell and Zomerdijk, 2005). In mammals, at least four factors in addition to RNA pol I are required to initiate rRNA transcription. The multisubunit transcription factor TIF-IB/SL1, which is composed of TATA-binding protein (TBP) and three TBP-associated factors or TAFs; the HMG-box protein, upstream binding factor (UBF); the TIF-IA/RRN3 protein; and TIF-IC (reviewed in Cavanaugh et al., 2004). In yeast, rDNA transcription requires upstream activation factor (UAF) and core factor (CF), as well as Rrn3p, the yeast homolog of mammalian TIF-1A. The UAF factor is a multisubunit complex of at least six proteins and CF is composed of TBP and three stably associated proteins (Nomura et al., 2004). In plants, most of our knowledge of cis-acting DNA elements that regulate rRNA transcription comes from studies of the A. thaliana IGS, the size and organization of which is similar to that of Xenopus laevis (Pikaard, 2002). Both Xenopus and Arabidopsis rRNA gene IGS sequences include multiple spacer promoters in addition to the gene promoter, as well as reiterated sequence elements that act as enhancers of transcription, at least in Xenopus (Labhart and Reeder, 1985; Pikaard, 1994). Using transient expression in Arabidopsis protoplasts, Doelling et al. demonstrated that sequences extending from −33 upstream to +6 downstream from the transcription start site (+1) are sufﬁcient to program minimal accurate transcription initiation in vivo, though sequences between −55 and +6 constitute a more reliable minimal promoter (Doelling et al., 1993; Doelling and Pikaard, 1995). More recently, analysis of the wheat rRNA promoter demonstrated that promoter sequences localized between −113 and +15 are sufﬁcient to program speciﬁc RNA pol I transcription (Akhunov et al., 2001). Remarkably, sequences surrounding the TIS in Arabidopsis (TATATAGGGGG, +1 is italicized) are highly similar between different plant species (Delcasso-Tremousaygue et al., 1988; Cordesse et al., 1993; Fan et al., 1995). The importance of this sequence was demonstrated by experiments showing that mutations in this consensus region abolish or inhibit rRNA transcription and inﬂuence the position of the TIS (Doelling and Pikaard, 1995) (Figure 7.1). In addition to the gene promoter, the A. thaliana IGS has at least two spacer promoters and blocks of repeated elements bearing Sal I restriction sites (Sal I repeats) that are located between the gene promoter and each duplicated spacer promoter (Pikaard, 2002). The spacer promoter sequences share 90% similarity with the gene promoter (from −92 to +6), although they are only ∼10% as active as the gene promoter (Doelling et al., 1993). Deletions of the Sal repeat sequences show no qualitative or quantitative differences in transcription initiation activity,

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suggesting that upstream repeat sequences of the rDNA intergenic region do not act as transcriptional enhancers for RNA pol I in Arabidopsis (Doelling et al., 1993; Wanzenbock et al., 1997). Nevertheless, when Sal repeats are cloned adjacent to an X. laevis ribosomal RNA gene promoter, they enhance transcription activity at least ﬁve- to tenfold, as discussed previously (Doelling et al., 1993). Moreover, when they are cloned upstream from the β-glucuronidase GUS reporter gene, reporter expression increases fourfold in A. thaliana plants (Schlogelhofer et al., 2002). In summary, at present there is no ﬁrm evidence for a bipartite structure of rRNA gene promoters in plants, as has been demonstrated in animals and yeast. Instead, plant rRNA gene promoters may be more like the promoters of Acanthamoeba, with a relatively small CP that is sufﬁcient for transcription initiation both in vivo and in vitro (Kownin et al., 1985; Radebaugh et al., 1997). The repeat elements present in the IGS regions of all studied species might have a structural role in establishing chromatin organization and/or nucleolus structure. Furthermore, we can speculate that upstream sequences in the plant IGS may play a regulatory role during development and/or under different environmental conditions. Therefore, a role for additional sequences may become clearer as additional assays are developed. Can rRNA gene promoters from a close or distant plant species be recognized and transcribed by the transcriptional machinery of another plant? In mammalian cells, it is known that pol I transcription is species speciﬁc due to the coevolution of the promoter and TIF-1B/SL1 transcription factor (Learned et al., 1985; Schnapp et al., 1991; Heix and Grummt, 1995). Species speciﬁcity in plants has been studied in vivo as well as in vitro and has revealed interesting results. In one study, the rRNA gene from tobacco was reported to be actively transcribed in tobacco nuclear extracts, but a broad bean rRNA gene was inactive in the tobacco extract (Fan et al., 1995), in keeping with the expectations derived from the studies in mammals. Interestingly, when a tomato rRNA gene promoter was transfected into A. thaliana protoplasts, it was shown to program transcription initiation, but from an unusual start site located 32 nucleotides downstream from the normal RNA pol I TIS (Doelling and Pikaard, 1996). In the same study, when the gene promoter from Brassica oleracea, a species closely related to A. thaliana, was transfected into A. thaliana protoplasts, transcription initiation was detected both from the normal RNA pol I TIS and from a novel site 29 nucleotides downstream from the expected start site (Doelling and Pikaard, 1996). Doelling and Pikaard reasoned that in a heterologous system, in which the pol I transcription machinery does not efﬁciently recognize the rRNA gene promoter, the conserved TATATA sequence located at the normal TIS might serve as a TATA box. If so, recognition of the TATA box by the TBP within the transcription factor complex TFIID might program pol II transcription, which typically initiates 25–30 nt downstream of a TATA box (Muller and Tora, 2004). Consistent with this hypothesis, mutations of the Brassica TATA sequence, which eliminated +29 transcription and expression of a linked reporter protein gene, were rescued by cotransfection of TBP genes that contained suppressor mutations. Importantly, the transcription initiating from +1, attributable to pol I transcription, was unaffected by the mutations or TBP suppressor gene (Doelling and Pikaard, 1996). These experiments showed that the TATATA sequence within the conserved initiator region

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of plant rRNA gene promoters is capable of serving as a TATA box recognized by TBP, but in the context of pol I transcription, the conserved TATA-containing sequence serves a function other than TBP binding. In plants, little is known concerning speciﬁc transcription factors that comprise the rRNA transcriptional machinery. Early biochemical and immunological studies revealed that B. oleracea RNA pol I core enzyme is an approximately 600-kDa multimeric enzyme containing 12–15 subunits (Guilfoyle et al., 1976; Guilfoyle and Jendrisak, 1978; Guilfoyle and Malcolm, 1980). In the following 20 years, a number of efforts to identify potential pol I transcription factors relied on electrophoretic mobility shift assays to detect proteins interacting with the promoter or promoterproximal sequences (Echeverria et al., 1992; Jackson and Flavell, 1992; Griess et al., 1993; Ashapkin et al., 1995; Kneidl et al., 1995), although the identity of these proteins remains unknown. Sequencing of genomes from A. thaliana (TAG Initiative, 2000) and other plant species (IRGS Project, 2005) has allowed the identiﬁcation of potential transcription factors described in the animal and yeast systems. For instance, the A. thaliana genome codes for at least one protein with multiple HMG boxes, reminiscent of the vertebrate UBF family (Soullier et al., 1999), and two proteins with signiﬁcant similarity to TIF-1A/RRN3 proteins (Saez-Vaquez and Pikaard, unpublished results). On the other hand, no Arabidopsis genes encoding proteins with detectable homologies to any of the TAFs of TIF-IB/SL1 or yeast CF, nor to the yeast UAF proteins, are readily apparent in the genome. It is possible that functional homologs could have diverged beyond recognition in the rapidly evolving pol I/rRNA gene transcription system. In animals, UBF is an HMG protein involved in pol I transcription activation, as mentioned previously. UBF can bend and wrap rDNA using its HMG boxes (Putnam et al., 1994; Stefanovsky et al., 1996) and is implicated in rRNA gene regulation, rDNA chromatin organization, and NOR morphology (Schnapp and Grummt, 1991; Voit et al., 1992, 1997; Mais et al., 2005). Recently, a protein distantly related to UBF, HMO1, was identiﬁed in yeast. This protein is a ∼25-kDa polypeptide that contains a single HMG domain, localizes to the nucleolus, and stimulates rRNA transcription (Gadal et al., 2002). Moreover, Hmo1p bends DNA and may play a role in chromatin structure (Kamau et al., 2004). Thus, factors that are functionally equivalent to UBF may be present in a wide range of eukaryotes. It is possible that a functional homolog of UBF might exist in plants, although this has not yet been demonstrated. The putative UBF-like protein in A. thaliana mentioned previously has a predicted molecular mass of 53 kDa and contains three HMG boxes, whereas the molecular mass of vertebrate UBF proteins range from ∼85 to 97 kDa (Pikaard et al., 1990b; O’Mahony and Rothblum, 1991; Kuhn et al., 1994) and have ﬁve or six HMG boxes (Pikaard et al., 1990b; Bachvarov and Moss, 1991; Hisatake et al., 1991; O’Mahony and Rothblum, 1991; Kuhn et al., 1994). Both rice and maize also have predicted proteins that contain three HMG boxes as in Arabidopsis. Moreover, antibodies against mammalian UBF have been shown to cross-react with a single 58-kDa polypeptide on immunoblots and interact with one or more proteins in the nucleolus of Allium cepa (Rodrigo et al., 1992; de Carcer

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and Medina, 1999; Tao et al., 2001a,b). Collectively, these data provide tantalizing hints that a UBF-like protein could be present in plants, but this remains highly speculative, and no role for a UBF-like protein in plant rRNA transcription has yet been demonstrated. Another important DNA element that has been shown to regulate RNA pol I promoter activity in other species, including mouse (Kuhn et al., 1988), yeast (van der Sande et al., 1989), and Xenopus (McStay and Reeder, 1986), is the pol I transcription terminator. In mouse and Xenopus, the terminator is an element located just downstream from the 28S rRNA coding sequences at the 5 end of the IGS but is repeated again just upstream from the rRNA gene promoter. In mouse, the terminator element is recognized by the transcriptional terminator factor 1 (TTF1) (Grummt, 2003). In plants, potential transcription termination sites have been identiﬁed in Raphanus sativus (Delcasso-Tremousaygue et al., 1988) and Vigna radiata (Schiebel et al., 1989), but the factors have not yet been identiﬁed and the role of these sites in rRNA gene regulation remains to be determined.

7.5

RNA pol I holoenzymes: evidence and controversies

The development of cell-free transcription systems has allowed the identiﬁcation of basal and regulatory transcription factors involved in rRNA transcription in animals as well as in yeast. Whole cell extracts that appear to program speciﬁc rRNA transcription initiation have been described for Vicia faba (Yamashita et al., 1993) and Nicotiana tabacum (Fan et al., 1995). These systems, together with the puriﬁcation of a cell-free transcription system for pol I prepared from broccoli (B. oleracea) (Saez-Vasquez and Pikaard, 1997), should facilitate the characterization of regulatory factors and mechanisms involved in transcription of rRNA genes in plants. In B. oleracea, a highly puriﬁed in vitro transcription system led to the ﬁrst evidence in any eukaryote that the RNA pol I core enzyme and its essential transcription factors can assemble into a multicomponent holoenzyme complex that is capable of binding to the promoter and programming accurate transcription initiation. The key observation is that the B. oleracea RNA pol I holoenzyme can be puriﬁed through multiple different chromatography columns, and single fractions at each step remain capable of programming accurate, promoter-dependent transcription initiation (Saez-Vasquez and Pikaard, 1997). The fact that all activities required to direct accurate rDNA transcription copurify through ﬁve different chromatography steps suggests that all the necessary transcription factors are stably associated with RNA pol I to form a single multiprotein complex or holoenzyme. Based on gel ﬁltration, the B. oleracea RNA pol I holoenzyme complex displays a molecular mass of approximately 2 MDa and contains approximately 30 distinct polypeptides. In addition to several proteins identiﬁed immunologically as subunits of RNA pol I, a casein kinase II (CKII)-like protein kinase (Saez-Vasquez et al., 2001) and a histone acetyltransferase (HAT) activity (Saez-Vasquez and Pikaard, unpublished results) copurify with pol I holoenzyme activity. Likewise, CKII and HAT activities were also found in an RNA pol I holoenzyme puriﬁed from X. laevis

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(Albert et al., 1999), suggesting that a general feature of RNA pol I holoenzymes is an ability to respond to growth signals and modify chromatin structure to activate transcription. DNase I footprinting revealed that the Brassica RNA pol I holoenzyme binds to and protects the CP region from ≈−30 to +20 (Saez-Vasquez and Pikaard, 2000), in good agreement with the boundaries of the minimal rDNA promoter deﬁned in vivo and in vitro (Doelling et al., 1993; Doelling and Pikaard, 1995) (Figure 7.1). Furthermore, the minimal promoter sequences required to program transcription by the Brassica pol I holenzyme correspond to the same sequences that are required for transcription in vivo following transfection and transient expression of rRNA minigenes (Saez-Vasquez and Pikaard, 1997). Therefore, the puriﬁed holoenzyme activity appears to account for the known characteristics of Brassica and Arabidopsis rRNA transcription in vivo. Another observation that supports the existence of a pol I holenzyme is that in an agarose electrophoretic mobility shift assay, highly puriﬁed B. oleracea RNA pol I holoenzyme fractions contain a promoter-speciﬁc DNA-binding activity that associates and dissociates from the promoter in a single step, with no intermediate complex(es) observed (Saez-Vasquez and Pikaard, 2000). The discovery of RNA pol I holoenzymes, not only in plants but also in different organisms and transcriptional systems (Wang et al., 1997; Myer and Young, 1998), has raised interest in their role in rRNA transcription initiation as well as some debate concerning their signiﬁcance. Time-lapse microscopy studies of ﬂuorescently tagged proteins involved in pol I transcription in mammalian cells suggested that in contrast to the holoenzyme model, RNA pol I subunits assemble in vivo at the rRNA genes in a sequential manner via metastable intermediates, with increasing stability achieved as more subunits are added (Dundr et al., 2002). A model developed from these observations proposes that at the end of each transcription cycle, RNA pol I dissociates into individual subunits, which then leave the nucleolus. However, these results are inconsistent with a detailed study in yeast, which showed that Rrn3p–Pol I complexes form even in the absence of rRNA gene promoters and that RNA pol I subunits remain stably associated with one another through many transcription cycles (Schneider and Nomura, 2004). The observations in yeast are compatible with the existence of holoenzymes that presumably include the essential factor, Rrn3p/TIF-IA. Although one cannot exclude the possibility that after homogenization of tissues and breakage of cells, RNA pol I holoenzymes complexes might be artiﬁcially generated, this is unlikely because both plant and animal holoenzymes have been identiﬁed and puriﬁed under very stringent biochemical conditions (Saez-Vasquez et al., 2003) and by using different approaches (Seither et al., 1998; Hannan et al., 1999). Also, it is possible that the experimental conditions of Dundr et al. do not allow analysis of RNA pol I holoenzyme complexes because only a small fraction of RNA pol I is tightly associated with transcription factors to form a pool of holoenzyme complexes (Saez-Vasquez and Pikaard, 1997; Albert et al., 1999). Finally, it is always possible that both models are correct, with the holoenzyme potentially being the initiation-competent form of pol I, but representing a small proportion of the total pol I pool, much of which is engaged in transcriptional elongation, rather than initiation, on each rRNA gene. Dissociation of holoenzyme

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subcomplexes following initiation may be part of the transcription cycle, and would necessitate reassociation of the subcomplexes with pol I core enzyme complexes that are released from the template upon transcriptional termination.

7.6

Coupling rDNA transcription and processing of pre-rRNA

In the nucleolus, transcription of rDNA is linked to processing of the primary transcript (pre-rRNA) synthesized by RNA pol I. Soon after transcription of the fulllength pre-rRNA, containing 18S, 5.8S, and 25S–28S rRNA, external transcribed spacers (5 ETS and 3 ETS) and internal transcribed spacers (ITS-1 and ITS-2) are removed and involve multiple cleavage events (Figure 7.1). Likewise, modiﬁcation of numerous rRNA residues takes place, mainly by pseudouridylation and 2 -Oribose methylation. All these events are directed by nucleolar proteins and small nucleolar RNAs (snoRNAs) that form different small nucleolar ribonucleoprotein (snoRNP) complexes that transiently interact with the pre-rRNAs (Venema and Tollervey, 1999; Fromont-Racine et al., 2003). One of the ﬁrst events occurring cotranscriptionally on the nascent pre-rRNA is the formation of a 5 ‘terminal ball’ that can be visualized by electron microscopy of rRNA genes subjected to the so-called Miller chromatin-spreading technique (Miller and Beaty, 1969). These terminal balls correspond to a large U3 snoRNP that directs the early cleavages of the pre-rRNA (Mougey et al., 1993). Characterization of this complex in yeast identiﬁed ﬁbrillarin and 27 other nucleolar proteins that associate with the highly conserved U3 snoRNA (Dragon et al., 2002). Further genetic dissection of the yeast U3 snoRNP identiﬁed a subcomplex of proteins (Utp complex) that forms in the absence of U3 and directly interacts with the rDNA 5 ETS region. Most remarkably, it was shown that this interaction is important for subsequent assembly of U3 snoRNP on the pre-rRNA (Gallagher et al., 2004). A similar situation probably occurs in plants. A U3 snoRNP of ∼600 kDa that has been puriﬁed and characterized from cauliﬂower inﬂorescence binds to prerRNA and accurately produces the ﬁrst cleavage of the pre-rRNA in vitro (SaezVasquez et al., 2004b). In addition to U3 snoRNA, ﬁbrillarin and a nucleolin-like protein were identiﬁed in this complex. These are two major nucleolar proteins implicated in pre-rRNA processing in animals and yeast (Tollervey et al., 1991; Ginisty et al., 1998). Interestingly the plant U3 snoRNP was puriﬁed based on its sequence-speciﬁc rDNA-binding activity. It was demonstrated that the plant U3 snoRNP complex speciﬁcally binds to a double-stranded rDNA sequence just upstream from the primary cleavage site in the pre-RNA 5 ETS (Caparros-Ruiz et al., 1997). Altogether, these data support a model whereby the U3 snoRNP processing complex might assemble ﬁrst on rDNA and subsequently interact with nascent prerRNA that is produced when RNA pol I traverses the DNA element (Saez-Vasquez et al., 2004a,b). In this model the plant nucleolin-like protein could play an important regulatory role. In vertebrates, nucleolin has been shown to bind to pre-rRNA and is essential for 5 ETS cleavage. In addition, nucleolin also binds to rDNA and can interfere with

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RNA pol I-directed transcription: overexpression of nucleolin in Xenopus oocytes represses RNA pol I transcription (Roger et al., 2002). On the other hand, experiments using oocytes injected with nucleolin and actinomycin D revealed that overexpression of nucleolin affects processing of pre-rRNA only when it is present at the same time of transcription (Roger et al., 2003). Thus, in plants, animals, and yeast various lines of evidence indicate a link between RNA pol I transcription and assembly of processing complexes on nascent pre-rRNA, but the mechanisms for this linkage remain unknown. An important question is whether or not processing activities are directly interacting with RNA pol I. Such a link is well documented for RNA pol II and the processing of pre-mRNAs. It has been shown that capping, splicing, and polyadenylation factors are recruited to transcription sites by direct interaction with the carboxy-terminal domain (CTD) that protrudes from the largest RNA pol II (Neugebauer, 2002). The large subunit of RNA pol I lacks a CTD-like domain and a different mechanism is probably involved. In plants and yeast the U3 snoRNP and Utp complexes respectively interact with the rDNA independently of rRNA transcription and do not require RNA pol I. Transcription by RNA pol I is probably required to assemble processing complexes on the nascent pre-rRNA, but RNA pol I does not recruit these complexes to the rDNA. Thus, the next challenge in plants will be to elucidate the mechanism regulating the assembly of the 5 ETS processing complex on the rDNA and its subsequent binding to nascent pre-rRNA.

7.7

Growth and hormonal control of RNA pol I transcription

In all eukaryotes, rRNA synthesis is highly sensitive to environmental conditions, including nutrient availability or stress conditions. Synthesis of rRNA is also stimulated by diverse physiological effectors, including growth signals and phytohormones (Nomura et al., 1984; Moss, 2004). In plants, early work carried out by Guilfoyle and collaborators showed that auxin treatment increases the amount of extractable RNA pol I activity, assayed using heterologous template DNA (promoter-independent, ribonucleotide incorporation using a nicked or sheared DNA template) (Guilfoyle et al., 1975). Increased RNA pol I activity in response to auxin treatment could be correlated with increased amounts of RNA pol I, but no apparent modiﬁcation of RNA polymerase subunits was detected (Guilfoyle and Malcolm, 1980). Later, Gaudino and Pikaard showed that exogenous cytokinin upregulates pol I transcription from the Arabidopsis rRNA gene promoter, whereas auxin had no discernible effect (Gaudino and Pikaard, 1997). Because auxin treatment can increase RNA pol I abundance and yet does not increase transcription from the rRNA gene promoter, as does cytokinin, it is possible that cytokinin regulates a rate-limiting step, such as post-translational modiﬁcation of one or more key activities in order to upregulate promoter-dependent transcription (Gaudino and Pikaard, 1997). One prediction is that treatment with both auxin and cytokinin might show a synergistic effect in upregulating rRNA gene promoter activity, but this experiment has not yet been reported. Thirty years ago, Teissere et al. reported four fractions – alpha, beta, gamma, and delta – that stimulate the activity

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of RNA pol I in lentil roots (Teissere et al., 1975). At least one of these factors, the gamma factor, is an auxin-induced protein (Teissere et al., 1975). The possibility that the gamma factor could also be induced by cytokinin remains untested. The identiﬁcation of CKII and HAT activities associated with the B. oleracea pol I holoenzyme suggests that the holoenzyme is equipped to respond to growth signals and modify chromatin as necessary, to activate transcription (Saez-Vasquez et al., 2001). Growth-dependent changes in rDNA transcription in animals have been correlated with the phosphorylation of UBF by CKII (Voit et al., 1995). Furthermore, the HAT p300/CBP-associated factor (PCAF) is implicated in the control of cell growth and differentiation and is known to acetylate TIF-1B/SL1 and activate RNA pol I transcription (Muth et al., 2001). Moreover, acetylation of UBF by CREB-binding protein (CBP) activates rRNA transcription, whereas the retinoblastoma (Rb) protein promotes UBF deacetylation and suppresses rRNA transcription (Pelletier et al., 2000). As mentioned previously, a TIF-1B/SL1-like activity has not been identiﬁed in plants; however, Rb protein has been described as participating in cell proliferation in A. thaliana (Ebel et al., 2004; Park et al., 2005). It is possible that Rb may play a role in regulating rRNA transcription during growth or cell proliferation in plants, as in animals, but there is no direct evidence at this time. It has been shown that plant growth and proliferation can be induced in the absence of cytokinins by overexpressing cyclin D3 (Riou-Khamlichi et al., 1999). Because RNA pol I and D cyclins are under the control of Target of Rapamacyn (TOR) in yeast and mammals (Schmelzle and Hall, 2000), a plant TOR pathway could also be involved in rRNA regulation in plants. The A. thaliana genome contains one TOR gene (AtTOR) (Menand et al., 2002) as well as other potential orthologs of the animal and yeast TOR pathway (Menand et al., 2004). Therefore, the TOR pathway in plants might be a nodal point that is able to integrate hormonal and developmental signals with rRNA transcription. Clearly, the study of signaling pathways involved in growth and hormonal control of rRNA transcription in plants merits further investigation.

7.8

Nucleolar dominance

Plants and animals typically have hundreds of rRNA genes, not all of which are active, such that the mechanisms responsible for the selective activation and/or silencing of subsets of the rRNA genes have been sought for many years. Considerable progress has been achieved during the last decade – thanks to the study of nucleolar dominance in plants, a phenomenon that offers a unique model for understanding large-scale transcriptional regulation of rRNA genes in higher eukaryotes. When two species are crossed to form an interspeciﬁc hybrid, a NOR-bearing chromosome from one progenitor species may form a nucleolus while its homolog inherited from the other parent does not. This phenomenon, known as nucleolar dominance, was ﬁrst described in plants in 1934 by Navashin (Navashin, 1934) and was called ‘differential amphiplasty’. It has since been shown to occur in insects, amphibia, and mammals, as well as in plants (Reeder, 1985).

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Nucleolar dominance has been demonstrated in numerous plant species, including three allotetraploids of the genus Brassica (Chen and Pikaard, 1997a,b), several cereal hybrids (Houchins et al., 1997; Neves et al., 1997), and more recently in artiﬁcial Solanum allopolyploids (Komarova et al., 2004). Nucleolar dominance has also been reported in the natural species Arabidopsis suecica, an allotetraploid derived from A. thaliana and Arabidopsis arenosa (also know as Cardaminopsis arenosa), in which the A. thaliana rRNA genes are repressed and those of A. arenosa are expressed (Chen et al., 1998). Interestingly, nucleolar dominance does not occur in all strains of A. suecica (Pontes et al., 2003). Some species show almost complete silencing of A. thaliana genes, whereas in others signiﬁcant A. thaliana rRNA gene expression is detected (Pontes et al., 2003). The basis of this natural variation in nucleolar dominance is not clear, but is likely the result of subtle genetic (or epigenetic) variation rather than dramatic genome-restructuring events. Although nucleolar dominance seems to be a manifestation of a dosage control system that limits the number of active rRNA genes (Lawrence et al., 2004), the system responds to growth or developmental conditions. For instance, in the allotetraploid B. napus, the B. oleracea-derived rDNA is normally suppressed and B. rapa-derived rDNA is active in vegetative tissue (Chen and Pikaard, 1997a). However, rDNA transcripts from B. oleracea are found in all organs derived from ﬂoral meristems (ﬂoral buds, sepals, petals, anthers, and siliques), suggesting that the B. oleracea genes silenced during vegetative growth are derepressed on ﬂowering (Chen and Pikaard, 1997b). In agreement with these results, Komarova et al. recently observed developmental modulation of dominant and underdominant rDNA genes in Solanum allopolyploid species (Komarova et al., 2004). Several hypotheses have been proposed to explain nucleolar dominance in plants, based either on differences in rRNA gene–pol I transcription factor interactions or on chromatin modiﬁcations that completely repress one set of rRNA genes (Pikaard, 2000). Studies using transfection of cloned rRNA genes from B. rapa and B. oleracea demonstrated that both genes are equally active in B. oleracea, B. rapa, or B. napus (the allotetraploid hybrid of B. oleracea and B. rapa) cells, ruling out the hypothesis that species-speciﬁc transcription factors play a role in nucleolar dominance in B. napus (Frieman et al., 1999). In addition, in vitro transcription assays using a cell-free transcription system from B. oleracea also revealed that dominant and underdominant rRNA genes are equally transcribed (Frieman et al., 1999). The hypothesis that the rRNA genes with longer IGSs (which might contain more putative enhancer repeats) are dominant is inconsistent with experiments in vivo and in vitro showing that dominant or underdominant genes, with either minimal promoters or complete IGSs, are similarly transcribed (Chen et al., 1998; Frieman et al., 1999). Furthermore, dominant species can sometimes have a relatively long IGS and more repeats than do underdominant rRNA genes, or they can have an IGS that is shorter and contains fewer repeats (Neves et al., 1997; Pikaard, 1998; Komarova et al., 2004), allowing the conclusion that there is no clear correlation between IGS size or repeat number and nucleolar dominance. The earliest evidence suggesting that nucleolar dominance is controlled by chromatin modiﬁcation came from observations of the level of methylation of NORs in

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wheat and maize (reviewed by Pikaard, 2002). In these two cases, rRNA genes at active NORs were shown to be slightly less methylated and more DNase accessible than rRNA genes at repressed NORs. More recent experiments showed that treatment of Brassica and Arabidopsis hybrids with an inhibitor of cytosine methyltransferase, 5-aza-2 -deoxycytoine (aza-dC), induced reactivation of underdominant rRNA genes and suppressed NORs (Chen and Pikaard, 1997a,b; Chen et al., 1998). However, DNA methylation is not the only player in activation or repression of rRNA genes. Treatment with trichostatin or sodium butyrate, chemicals that cause histone hyperacetylation due to inhibition of histone deacetylase (HDAC) activity, also induced rRNA gene derepression in Brassica and Arabidopsis hybrids (Chen and Pikaard, 1997a,b). Thus, these results suggested that underdominant rRNA genes are silenced as a consequence of covalent chromatin modiﬁcations. In Arabidopsis hybrids, the promoters of silenced rRNA genes are hypermethylated and are associated with histone H3 dimethylated on lysine 9 (H3dimethyl K9), whereas hypomethylated promoters (active genes) are associated with histone H3 trimethylated on lysine 4 (H3trimethyl K4) (Lawrence et al., 2004). Likewise, rRNA gene derepression is associated with loss of H3dimethyl K9 and gain of H3trimethyl K4 (Lawrence et al., 2004). Interestingly, blocking DNA methylation causes changes in histone modiﬁcation, and blocking histone deacetylation induces cytosine demethylation. Since treatment with both aza-dC and trichostatin does not have a synergistic effect, this suggests that cytosine methylation and histone deacetylation act in the same pathway of rRNA gene repression. In fact, the available data suggest a model for a self-reinforcement pathway for rRNA silencing. In this model, H3K9 methylation and H3K9 acetylation are mutually exclusive, suggesting that H3K9 deacetylation precedes H3K9 methylation. A potential H3K9 deacetylase is HDT1 (AtHD2a), whose knockdown by RNA interference causes the derepression of underdominant rRNA genes (Lawrence et al., 2004). Interestingly, mutation in the RPD3-like HDAC AtHDA6 gene affects the H3K4 methylation status at rDNA loci, and although no effect of HDA6 on rRNA gene expression has yet been reported, it may play some role in rRNA gene silencing in nucleolar dominance (Probst et al., 2004). The identity of the H3K9 methylase remains unclear. What do we know about factors and mechanisms directing rDNA chromatin silencing or activation? Grummt et al. showed that the nucleolar chromatinremodeling complex, NoRC, is implicated in silencing of rRNA reporter genes in mammalian cells (Santoro et al., 2002). In this case, RNA silencing is initiated by recruitment of NoRC to the Pol I promoter by interacting with transcriptional terminator factor 1 (TTF-1) at the terminator site located just upstream from the rRNA gene promoter. Subsequently, NoRC interacts with HDAC and DNA methyltransferases that mediate histone H4 deacetylation, H3K9 methylation, and cytosine methylation (Santoro and Grummt, 2005). On the other hand, recent genetic data have demonstrated silencing of transposable elements and other repeated sequences via small interfering RNA (siRNA). This silencing mechanism involves catalytic subunits for a fourth RNA polymerase in plants (RNA pol IV). The data suggest that pol IV, together with factors RDR2 and DCL3, produces siRNAs that target de novo cytosine methylation of homologous sequences via a pathway that also involves

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AGO4 and DRM (Herr et al., 2005; Onodera et al., 2005; Pontier et al., 2005; Vaughn and Martienssen, 2005). This siRNA silencing mechanism is implicated in cytosine methylation of 5S rRNA genes, and so it is tempting to speculate that methylation of silenced RNA pol I genes is also directed by the same pathway, but no direct evidence has been presented for a role of pol IV in rRNA silencing or nucleolar dominance. However, Onodera et al. showed that in pol IV mutants, NORs partially dissociate from each other, suggesting a role of pol IV in establishing the heterochromatin environment for nucleolar dominance (Onodera et al., 2005). Future studies will be necessary to understand if the NoRC complex and/or RNA pol IV is involved in nucleolar dominance in plants.

7.9

Final remarks

The plant rRNA gene transcription machinery seems to have similar modes of regulation as in animals and/or the yeast system, and the pol I transcription machinery can apparently interact to form holoenzymes in plants, Xenopus, mouse, and rat. However, several of the key basal and regulatory transcription factors found in other systems seem to be missing, or have not been identiﬁed in plants, suggesting that some transcription factors for plant rRNA genes are likely to be plant speciﬁc. This is not unexpected, given the rapid evolution of the pol I–rRNA gene transcription system. Full characterization of puriﬁed in vitro transcription (and processing) systems combined with the use of genetic resources in Arabidopsis should help us to identify and characterize the different players involved in rRNA gene transcription regulation in plants. Although there is considerable information on mechanisms involved in nucleolar dominance in plants, major questions remain unanswered. For instance, what makes plants repress one parental set of rRNA genes rather than expressing both sets at reduced levels? How do chromatin-remodeling factors direct and/or maintain heterochomatin formation at underdominant rDNA genes? Recent work suggesting that there is crosstalk between transcription and pre-rRNA processing provides evidence for novel mechanisms involved in the regulation of rRNA transcription, and plants are currently at the forefront of this new area of investigation. Determining the identity and function of factors involved in the different stages of rRNA transcription regulation (transcription activation, coordination between different stages of rRNA synthesis, establishment and/or maintenance of silencing) should help us to better understand rRNA transcription regulation in plants. Building upon the considerable progress that has been achieved in the last decade, there are certainly many more advances awaiting us in the next decade.

Acknowledgment We thank Dr Craig Pikaard at Washington University (St Louis, MO, USA) for critical reading and advices that contributed to improve the manuscript. We also thank the head of the LGDP laboratory,

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M. Delseny, for supporting this work and Richard Cooke for comments and corrections of English. We apologize to colleagues whose work we did not mention in this chapter for reason of space.

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8 Transcription of plastid genes Karsten Liere and Thomas B¨orner

8.1

Introduction

Virtually all plant cells contain plastids. Exceptions are generative and/or sperm cells of those plant species that exhibit uniparental maternal inheritance of the plastid genome (plastome; Hagemann, 2004). Plastids accomplish important metabolic functions. In the various tissues of higher plants exist different types of plastids with specialized roles, the most intensively studied of them being the photosynthetically active chloroplast in green tissues. Plastids divide in a similar manner as bacteria (Aldridge et al., 2005). Each plastid in a plant contains identical plastome copies. Restriction mapping of chloroplast DNA provided evidence for circular chromosomes, ﬁrst shown for maize (Bedbrook and Bogorad, 1976) and spinach (Herrmann et al., 1976) and later found in most investigated plants including algae (for a recent review see Maier and Schmitz-Linneweber, 2004). In addition to monomeric circles, there exist not only dimers, trimers, and tetramers, but also numerous linear and even more complex molecules of different sizes (Bendich, 2004). Similar to bacterial chromosomes, plastid DNA is organized in nucleoids. Developing and mature chloroplasts contain several nucleoids, and each nucleoid contains several copies of the genome. The copy number of plastid chromosomes and transcript levels vary drastically between different tissues. Highest levels are found in chloroplasts of photosynthetically active cells (Aguettaz et al., 1987; Baumgartner et al., 1989; Isono et al., 1997a). Several DNA-binding proteins are known and proposed to organize and maintain nucleoid structure (‘plastid chromatin’), to bind DNA to membranes, and to be involved in replication, repair, and inheritance of the plastome (Kuroiwa, 1991; Sato et al., 2003; Heinhorst et al., 2004). Only few data exist about effects of conformation of plastid DNA on plastid gene expression (Stirdivant et al., 1985; Gauly and K¨ossel, 1989; Sekine et al., 2002). Effects of DNA methylation on plastidial gene activity have been described, but seem to be an exception rather than the rule (Ngernprasirtsiri et al., 1989; Kobayashi et al., 1990; Ngernprasirtsiri and Akazawa, 1990; Hess et al., 1993; Isono et al., 1997a). Plastomes are remnants of the chromosome of their cyanobacterial ancestor. There is ample evidence for plastids being descendants of a cyanobacterium taken up as endosymbiont by the ancestral cell of the green lineage of eukaryotes (Martin et al., 2002; Dyall et al., 2004; Gray, 2004). During further coevolution of plastid (endosymbiont) and host cell, a massive loss of genes from the plastome has occurred. Many of those genes have been transferred to the nucleus. Gene transfer from the organelle to the nucleus is a relatively frequent, ongoing

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process (Herrmann et al., 2003; Timmis et al., 2004; Leister, 2005). Plastid chromosomes of embryophytes have a size of about 150 kb (ranging from 117 kb in Pinus koraiesis to 164 kb in Oenothera elata subsp. hookeri) and a gene content between approximately 100 and 120 (Hupfer et al., 2000; Gray, 2004; Maier and Schmitz-Linneweber, 2004) (for a compilation of all sequenced chloroplast genomes, see http://megasun.bch.umontreal.ca/ogmp/projects/other/cp list.html). Plastid genes code for the 16S, 23S, 5S, and 4.5S RNAs, for tRNAs sufﬁcient to translate all codons, for proteins needed in ﬁrst line for gene expression and photosynthesis, and for only a few proteins involved in other metabolic processes. As in bacteria, genes are organized in operons, but promoters also serve transcription of single genes (Sugiura, 1995; Maier and Schmitz-Linneweber, 2004). Several plastid genes contain introns belonging to the group I and group II families. Transcript maturation includes splicing, C to U (rarely U to C) editing, and excision of monocistronic mRNAs from polycistronic precursors. Trimming and polyadenylation at 3 ends are steps leading to degradation of transcripts (for reviews see Sugita and Sugiura, 1996; Bock, 2000; Barkan, 2004; Marchfelder and Binder, 2004). Gene expression in plastids is highly regulated at the level of post-transcriptional processes that are not subject of this chapter (for recent reviews see Barnes and Mayﬁeld, 2003; Barkan, 2004; Bollenbach et al., 2004; Herrin and Nickelsen, 2004; Marchfelder and Binder, 2004; Zerges, 2004). In the following discussion, we review our current understanding of the transcription in plastids of higher plants, with a focus on RNA polymerases, transcription factors, promoters, and the regulation of transcription by endogenous and environmental factors.

8.2

RNA polymerases

Cyanobacteria, the ancestors of chloroplasts, as other bacteria, use one RNA polymerase to transcribe all genes. The core enzyme consists of several subunits encoded by the rpoA, B, C1, and C2 genes (Bergsland and Haselkorn, 1991). For promoter recognition and initiation of transcription, the core polymerase is complemented by a σ -factor to constitute the holoenzyme. Cyanobacteria possess several σ -factors to transcribe different sets of genes (Imamura et al., 2003). Although chloroplast genomes are much smaller than bacterial ones, the transcription machinery in plastids is more complex as compared to that of bacteria. At least in angiosperms, transcription of plastid genes needs more than one type of RNA polymerase and different σ -factors. Originally, transcription of plastid genes was thought to depend exclusively on a nuclear-encoded RNA polymerase. RNA synthesis was detected in rye and barley plastids lacking all plastid-encoded proteins, indicating that one or more nuclear genes code for transcriptional activity in plastids (B¨unger and Feierabend, 1980; Siemenroth et al., 1981). The nuclear-encoded RNA polymerase was shown to synthesize plastidial rRNAs (Siemenroth et al., 1981) and, more recently, to transcribe many other genes in ribosome-free plastids (Falk et al., 1993; Han et al., 1993; Hess et al., 1993; H¨ubschmann and B¨orner, 1998; Zubko and Day, 1998).

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With the knowledge of ﬁrst complete sequences of plastid chromosomes it became evident that plastid genomes contain rpoA, B, C1, and C2 genes for all subunits of a core RNA polymerase of the (cyano)bacterial type (Ohyama et al., 1986; Shinozaki et al., 1986). Later, these genes were shown to indeed code for subunits of an active bacterial-type RNA polymerase (Hu and Bogorad, 1990; Hu et al., 1991). Inactivation of rpo genes in transplastomic tobacco plants led to an albino phenotype, demonstrating the essential role this RNA polymerase is playing for chloroplast development and function. However, the plastid genes were still transcribed in rpo plants, providing further evidence of the importance of the nuclear-encoded plastidial RNA polymerase (Allison et al., 1996; Hajdukiewicz et al., 1997; Krause et al., 2000; Legen et al., 2002). Thus, plastids of most angiosperms need at least two types of transcriptases, nuclear-encoded plastid RNA polymerases (NEP) and plastid-encoded plastid RNA polymerases (PEP) (Hajdukiewicz et al., 1997). PEP is the bacterial-type RNA polymerase encoded by the plastid rpoA, B, C1, and C2 genes (Figure 8.1). NEP was originally deﬁned as a transcriptase that is active in plastids even in the absence of PEP and plastid translation. Later, plastid-targeted phagetype RNA polymerases were recognized as potential candidates for NEP (Figure 8.1; Hedtke et al., 1997; reviewed by Gray and Lang, 1998; Hess and B¨orner, 1999). The transcriptional machinery might be even more complex, as Bligny et al. (2000) observed transcription of rRNA in spinach chloroplasts by an RNA polymerase activity that showed the expected features neither of a bacterial-type PEP nor of a phage-type NEP. Simpler, however, might be the transcriptional apparatus in plastids of certain parasitic, nonphotosynthetic angiosperms with reduced plastid genomes lacking rpo genes or containing only rpo pseudogenes. Consequently, they should lack PEP activity and rely solely on NEP to transcribe their plastid genes (Ems et

Figure 8.1 The nuclear-encoded plastid RNA polymerase (NEP) is related to phage-type singlesubunit enzymes. The catalytic subunit RpoT may need additional, yet unknown protein factors for promoter recognition. The plastid-encoded plastid RNA polymerase (PEP) is a multisubunit enzyme homologous to bacterial RNA polymerases. PEP needs one of several nuclear-encoded σ -factors to bind to the promoter. The composition shown here is typical for PEP in etioplasts. In chloroplasts, PEP is associated with more proteins. (TIS, transcription initiation site).

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al., 1995; Lusson et al., 1998; Krause et al., 2003; Berg et al., 2004). In contrast, algal chloroplasts may need only the PEP enzyme. In the case of Chlamydomonas reinhardtii no indications for a NEP were found (A. Weihe et al., unpublished data). NEP and PEP recognize different sets of promoters. NEP promoters resemble in their architecture the promoters in the genomes of mitochondria and T-bacteriophages, whereas PEP binds to sequence motives known from the −10 and −35 boxes of bacterial promoters.

8.2.1

NEP: Nuclear-encoded plastid RNA polymerase

There is accumulating evidence for NEP activity being represented by phage-type RNA polymerase(s). The genomes of several bacteriophages contain a gene for an RNA polymerase. The best characterized bacteriophage RNA polymerase is that of T7 phages (Steitz, 2004). In contrast to bacterial, archaeal, and eukaryotic RNA polymerases, the phage enzymes are single-subunit RNA polymerases; i.e., promoter recognition, initiation of transcription, and RNA synthesis (elongation) are performed by just one polypeptide (Steitz, 2004). The mitochondrial genome of baker’s yeast, Saccharomyces cerevisiae, was the ﬁrst nonphage genome demonstrated to be transcribed by a phage-type RNA polymerase (Masters et al., 1987; Schinkel et al., 1988). Mitochondrial genes of almost all eukaryotes are transcribed by related phage-type RNA polymerases (Cermakian et al., 1996). The only known exception to date is Reclinomonas americana, a freshwater protozoon belonging to the jakobids. Reclinomonas uses a mitochondrial-gene-encoded multisubunit RNA polymerase of the bacterial type (Lang et al., 1997). Moreover, plants possess nuclear genes for phage-type RNA polymerases (Figure 8.1; referred to as RpoT genes and RpoT polymerases, for RNA polymerases of the T3/T7-type; Hedtke et al., 1997). Some of these genes code for RNA polymerases that are targeted to mitochondria, as shown for dicots (Hedtke et al., 1997, 1999, 2000, 2002; Weihe et al., 1997; Kobayashi et al., 2001a), monocots (Chang et al., 1999; Ikeda and Gray, 1999; Emanuel et al., 2004; Kusumi et al., 2004), and the moss Physcomitrella (Kabeya et al., 2002; Richter et al., 2002). These polymerases are regarded as transcriptases of plant mitochondria, although direct experimental evidence for this proposed function is lacking. We have recently observed that the Arabidopsis mitochondrial RpoT polymerase (RpoTm) is able to recognize mitochondrial promoters and initiate transcription in vitro, strongly suggesting that this enzyme is indeed active in mitochondrial transcription (K. K¨uhn et al., unpublished data). The ﬁrst indication for a phage-type RNA polymerase in chloroplasts was reported by Lerbs-Mache (1993), who observed an RNA polymerase activity recognizing a T7 promoter in a 110-kDa protein fraction isolated from spinach chloroplasts. The ﬁrst candidate RpoT gene for a plastidial RNA polymerase of the phage-type (RpoTp) was discovered in the nuclear genome of Arabidopsis. It is proposed to originate from duplication of the RpoTm gene (Hedtke et al., 1997). Homologous nuclear RpoTp genes have been described for Nicotiana tabacum, Nicotiana sylvestris, Hordeum vulgare, Zea mays, Triticum aestivum, and Oryza sativa (Chang et al.,

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1999; Ikeda and Gray, 1999; Kobayashi et al., 2001a; Hedtke et al., 2002; Emanuel et al., 2004; Kusumi et al., 2004) and seem to be present in all angiosperms. Plastid localization of RpoTp polymerases is supported by chloroplast targeting of green ﬂuorescent protein (GFP) fused to the putative transit sequences. RpoTp polymerases have also been detected in chloroplasts of rice and maize by immunological methods (Chang et al., 1999; Kusumi et al., 2004). That RpoTp is indeed involved in transcription of plastid genes has recently been demonstrated using transgenic tobacco plants overexpressing this polymerase (Liere et al., 2004). Embryophytes are the only eukaryotes reported to possess more than one RpoT gene. Cereals have two RpoT genes coding for a mitochondrial (RpoTm) and a plastidial RNA polymerase (RpoTp; Chang et al., 1999; Ikeda and Gray, 1999; Emanuel et al., 2004; Kusumi et al., 2004). Arabidopsis and N. sylvestris have three (Hedtke et al., 2000, 2002; Kobayashi et al., 2001a,b, 2002) and the amphidiploid genome of N. tabacum harbors even six RpoT genes (two sets of three genes from each parental species; Hedtke et al., 2002). The RNA polymerase of the third gene in Arabidopsis and Nicotiana (and possibly other eudicots) is proposed to be targeted to both mitochondria and plastids (referred to as RpoTmp polymerase) as deduced from the localization of GFP fused to the putative N-terminal transit peptide (Hedtke et al., 2000, 2002; Kobayashi et al., 2001a). The localization of RpoTmp to Arabidopsis plastids has more recently been questioned by a study on transgenic plants expressing GFP fused to the putative transit peptide together with the 5 -UTR of RpoTmp. GFP ﬂuorescence was detected only in mitochondria of these plants (Kabeya and Sato, 2005). Baba et al. (2004) analyzed mitochondrial and chloroplast transcripts in an Arabidopsis line with a defective RpoTmp gene bearing a T-DNA insertion. The mutation affected the transcription of several plastidial but not of mitochondrial genes. Evidently, more investigations are needed to clarify localization and role of RpoTmp polymerases. All three RpoT genes are active in roots, leaves, and ﬂowers of Arabidopsis, though RpoTm and RpoTmp seem particularly active in meristems and young cells of all organs, whereas RpoTp is most expressed in green tissues (Emanuel et al., 2006).

8.2.2

PEP: Plastid-encoded plastid RNA polymerase

Plastid genomes contain the rpoA, B, C1, and C2 genes coding for the α (38 kDa), β (120 kDa), β (85 kDa), and β (185 kDa) subunits, respectively, of a bacterialtype RNA polymerase (Sugiura, 1995). Like in cyanobacteria, rpoB, C1, and C2 on one hand and rpoA together with genes for ribosomal proteins on the other hand form operons (Hudson et al., 1988; Purton and Gray, 1989; Kaneko et al., 1996). Two α subunits and one each of the β, β, and β subunits build up the core polymerase that performs the elongation step of RNA synthesis, but is able to bind to the promoter and to initiate transcription only when completed with one of several nuclear-encoded σ -factors (Figure 8.1). Similar to the core polymerase, σ -factors and promoters used by PEP are closely related to the corresponding components in bacteria (see below). PEP has been detected in the soluble fraction of chloroplast preparations and as an insoluble, DNA-bound activity, the so-called transcriptionally

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active chromosome (TAC; Little and Hallick, 1988; Suck et al., 1996; Pfalz et al., 2006). The soluble form of PEP isolated from etioplasts consists mainly of the core subunits, while additional proteins assemble with the core subunits to a larger complex in chloroplasts (Pfannschmidt and Link, 1994, 1997; Link, 1996; Baginsky et al., 1999; Pfannschmidt et al., 2000), probably reﬂecting the need of regulating PEP in response to changing light conditions and photosynthetic activity. Yet, it is unclear if NEP forms a complex with PEP or if the two RNA polymerases operate entirely independently of each other. Since PEP and NEP recognize different promoters (see below), the latter might be the case.

8.3 8.3.1

Plastidial promoters PEP promoters

The plastid-encoded plastid RNA polymerase (PEP) has evolved from a eubacterialtype RNA polymerase. Accordingly, plastidial promoters contain a variant of the −35 (TTGaca) and −10 (TAtaaT) consensus sequences of typical σ 70 -type Escherichia coli promoters (Reznikov et al., 1985; for reviews see Gruissem and Tonkyn, 1993; Link, 1994; Hess and B¨orner, 1999; Weihe and B¨orner, 1999; Liere and Maliga, 2001; Weihe, 2004). In fact, plastidial σ 70 -type promoters are accurately recognized by the E. coli RNA polymerase (e.g., Gatenby et al., 1981; Bradley and Gatenby, 1985; Boyer and Mullet, 1988; Eisermann et al., 1990). Besides, some plastidial σ 70 -type promoters contain additional regulatory cis-elements. Early data derived from in vitro transcription experiments established that the psbA gene, which encodes the D1 photosystem II reaction center polypeptide, is transcribed from a σ 70 -type promoter with the typical conserved −10 and −35 elements (Link, 1984; Gruissem and Zurawski, 1985; Boyer and Mullet, 1986; Boyer and Mullet, 1988). In vivo psbA transcription is developmentally timed and activated by light (Klein and Mullet, 1990; Schrubar et al., 1990; Baumgartner et al., 1993). A detailed in vitro characterization of the mustard psbA promoter identiﬁed a TATATA promoter element between the −10 and −35 hexamers resembling the TATA box of nuclear genes transcribed by RNA polymerase II (Eisermann et al., 1990; Link, 1994). The TATATA element and −10 region were sufﬁcient to obtain basic transcription levels in vitro in plastidial extracts prepared from both dark- and light-grown plants. Nonetheless, presence of the −35 element was essential for enhanced transcription rates characteristic of chloroplasts of light-grown plants (Link, 1984; Eisermann et al., 1990). The barley psbA promoter also contains the TATA motif between the −35 and −10-elements, but, unlike in mustard, the −35 sequence is absolutely required for transcription in vitro (Kim et al., 1999b). Such TATA box is also present in the wheat psbA promoter, but does not seem to be important. Constitutive (light-independent) transcription by PEP isolated from the leaf base (base-type PEP; young plastids) required both the −10 and the −35 elements for promoter activity. However, transcription by PEP isolated from the leaf tip (tip-type PEP; mature plastids) was dependent only on the −10 region, which additionally

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Figure 8.2 Different types of PEP and NEP promoters. PEP promoter: schematic overview of the wheat psbA (TaepsbA), barley psbD BLRP (HvupsbD), and tobacco rrn16 PEP promoters (Ntarrn16). Conserved −10/−35 consensus elements as well as individual promoter elements as the TATA box, extended −10 sequence (TGn), AAG box, and RUA element are shown. The less conserved −35 element in the barley psbD BRLP is shown in gray. NEP promoter: schematic overview of Type I and Type II NEP promoters, with examples from tobacco given in brackets. The YRTa promoter core and GAA box are marked. (TIS, transcription initiation site, indicated by arrows).

contains a TGn motif upstream of the −10 element (Figure 8.2; extended −10 sequence; Bown et al., 1997; Satoh et al., 1999). It was proposed that the basaland tip-type PEPs differ by their associated transcription factors, and hence, that the extended −10 sequence may be involved in promoter recognition by the tip-type PEP in mature plastids (Satoh et al., 1999). Since the mustard, barley, and wheat psbA promoter sequences are highly conserved, differences in the utilization of ciselements possibly are the result of a divergent evolution of trans-factors in these species. In addition to the core promoter regions, regulatory sequence motifs were identiﬁed in the proximity of the psbD-psbC, rbcL, and psaA-psaB promoters (see Section 8.4.3 for details).

8.3.2

NEP promoters

Transcription initiation sites for a nuclear-encoded transcription activity (i.e., NEP) were unambiguously identiﬁed in plants in which the transcriptional activity by PEP had been reduced or eliminated. Such systems comprise the ribosome-deﬁcient plastids of the monocot albostrians barley and iojap maize mutants (H¨ubschmann and B¨orner, 1998; Silhavy and Maliga, 1998a), tobacco rpo plants lacking PEP in dicots (Allison et al., 1996; Hajdukiewicz et al., 1997; Serino and Maliga, 1998), and photosynthetically inactive tobacco and rice suspension cultures, with elevated levels of NEP activity (Vera et al., 1996; Kapoor et al., 1997; Miyagi et al., 1998; Silhavy and Maliga, 1998b). While photosynthetic genes and operons have PEP promoters, most nonphotosynthetic genes involved in housekeeping functions such as transcription and translation have promoters for both RNA polymerases. NEP transcripts of these genes

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are, with a few exceptions, rarely detectable in chloroplasts and were therefore mostly analyzed in PEP-deﬁcient plants (see above). Only a few genes are known to be transcribed exclusively from a NEP promoter, i.e., accD, encoding a subunit of the acetyl-CoA carboxylase in dicots; clpP, encoding the proteolytic subunit of the Clp ATP-dependent protease; ycf2, encoding a protein with a yet unknown function; rpl23, encoding a ribosomal protein in monocots; and, most interestingly, the rpoB operon encoding three of the four PEP core subunits in all higher plants (Hajdukiewicz et al., 1997; H¨ubschmann and B¨orner, 1998; Silhavy and Maliga, 1998a). Thus, PEP abundance and activity depends on the nuclear-encoded RNA polymerase. NEP promoters do not have conserved eubacterial σ 70 -type promoter elements, but resemble mitochondrial and phage promoters, and based on their sequence properties they can be grouped into three types (Figure 8.2; Weihe and B¨orner, 1999; Liere and Maliga, 2001). Type I promoters analyzed thus far are characterized by a conserved YRTa motif critical for rpoB promoter recognition embedded in a small DNA fragment (−15 to +5) upstream of the transcription initiation site (+1) (PatpB289 – Kapoor and Sugiura (1999), Xie and Allison (2002); PaccD-129 – Liere and Maliga (1999b); PrpoB-345 – Liere and Maliga (1999a)). Although, in vitro, no additional sequence elements outside the promoter core modiﬁed rpoB transcription (Liere and Maliga, 1999a), transient expression of chimeric Arabidopsis rpoB 5 -ﬂanking region::GUS deletion-constructs in cultured tobacco cells suggested the existence of upstream regulatory regions for rpoB expression (Inada et al., 1997). Similar transient transcription assays to examine the 5 -ﬂanking region of the tobacco accD gene revealed that possibly further sequence elements up- and downstream of the promoter determine its strength (Hirata et al., 2004). A subset of Type I NEP promoters possesses a second, conserved sequence motif (ATAN0−1 GAA) ∼18–20 bp upstream of the YRTa motif, designated box II or GAA box (Figure 8.2; Silhavy and Maliga, 1998a; Kapoor and Sugiura, 1999). Mutational analyses of the GAA box in in vitro and in vivo transcription experiments suggest, at least for the tobacco PatpB-289 promoter, a functional role of this element in promoter recognition (Kapoor and Sugiura, 1999; Xie and Allison, 2002). Hence, Type I promoters are classiﬁed into two subclasses: Ia, with only the YRTa motif; and Ib, carrying both YRTa- and GAA box (Weihe and B¨orner, 1999; Liere and Maliga, 2001). Type II NEP promoters lack the YRTa motif and differ completely in sequence and organization from Type I promoters. So far, this class is represented by a single example, a promoter of the ClpP protease subunit gene (Figure 8.2). The tobacco PclpP-53 was characterized using a transplastomic in vivo approach demonstrating that critical promoter sequences are located mainly downstream of the transcription initiation site (−5 to +25; Sriraman et al., 1998a). The clpP-53 promoter motif and transcription initiation site are conserved among monocots, dicots, conifers, and liverworts, pointing toward an early appearance of the NEP transcription machinery in evolution. But, although the tobacco PclpP-53 sequence motif also is present in rice and Chlamydomonas, it is not used as a promoter. Although, if the rice sequence is introduced into tobacco plastids, the tobacco NEP recognizes this conserved Type II promoter. One may speculate that the lack of transcription in rice from

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the PclpP-53 homolog is due to the lack of either a Type II speciﬁcity factor or a distinct NEP enzyme not present in monocots (e.g., RpoTmp, see Section 8.2.1; Sriraman et al., 1998a; Liere et al., 2004). However, experimental data supporting these scenarios are still missing.

8.3.3

tRNAs with internal promoters

Most plastidial tRNAs are transcribed by the PEP from upstream σ 70 -type promoters. However, transcription of some tRNA genes such as the spinach trnS, trnR, and trnT (Gruissem et al., 1986; Cheng et al., 1997b) as well as trnS, trnH, and trnR from mustard (Neuhaus and Link, 1990; Nickelsen and Link, 1990; Liere and Link, 1994), and the Chlamydomonas trnE gene (Jahn, 1992), is assumed to be mediated by internal promoters. The transcription start site of the spinach trnS gene was mapped 12 nucleotides upstream of the mature tRNA coding region (Wu et al., 1997). While the coding region (+1/+93) promoted basal levels (8%) of transcription in in vitro assays, inclusion of an AT-rich region between −31 and −11 upstream of the coding region restored wild-type promoter strength. No sequences resembling either NEP or PEP promoters were found in this region. However, the trnS coding region contains sequences resembling the A and B blocks of nuclear tRNA promoters transcribed by the eukaryotic RNA polymerase III (Galli et al., 1981; Geiduschek et al., 1995). Upon injection into Xenopus oocyte nuclei, the tRNAArg (ACG) gene from Pelargonium zonale was efﬁciently transcribed (Hellmund et al., 1984), suggesting that the plastidial tRNAs may be transcribed by an RNA polymerase III-type enzyme in plastids. Thus far, in silico analyses of the Arabidopsis genome did not reveal a plastid-targeted polymerase of this type (K. Liere and T. B¨orner, unpublished). Therefore, the biochemical properties and enzyme composition of this transcription activity remains to be determined. Alternatively, specialized NEP or PEP enzymes associated with distinct transcription factors may recognize internal promoter structures and transcribe such tRNAs.

8.4

Regulation

Transcriptional control is thought to be a key element to manage expression of nuclear-encoded plastid-localized gene products (Kuhlemeier, 1992). Although post-transcriptional events may contribute more signiﬁcantly to regulation of plastidial gene expression (Deng and Gruissem, 1987; Stern et al., 1997; Barkan and Goldschmidt-Clermont, 2000; Monde et al., 2000), transcription of plastid genes was also shown to respond to factors such as light and plastid-type (Rapp et al., 1992; Mullet, 1993; Mayﬁeld et al., 1995; Link, 1996). At an early stage of light-induced plastid development, transcription activity of the majority of plastid-encoded genes increases to support rapid construction of the photosynthesis apparatus. Furthermore, it has been shown that light-dependent plastid transcription occurs in mature leaves as well as leaves under greening (Greenberg et al., 1989; Schrubar et al., 1990; Baumgartner et al., 1993; DuBell and Mullet, 1995; Hoffer and Christopher, 1997;

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Shiina et al., 1998; Satoh et al., 1999; Baena-Gonzalez et al., 2001; Chun et al., 2001; Nakamura et al., 2003). Most prominent examples are photosynthesis-related genes as psbA, psbD-psbC, petG, and rbcL, but also housekeeping genes as atpB (Klein et al., 1988; Haley and Bogorad, 1990; Klein and Mullet, 1990; Sexton et al., 1990; Isono et al., 1997a). Transcriptional activation of photosynthesis-related genes by distinctive photoreceptors has been analyzed (Chun et al., 2001; Thum et al., 2001). Light-quality perception may depend on the developmental stage. In dark-adapted mature leaves, red light only partially increased overall plastid transcription activity whereas blue light further enhanced it. Therefore, global activation of plastidial transcription after dark adaptation is probably mediated by cryptochromes. A further role is suggested for phyA, since an Arabidopsis phyA mutant exposed to blue light/UV-A displayed, in comparison to the wild type, reduced psbA and rrn16 transcript activities (Chun et al., 2001). As illustrated while describing plastid promoters, transcriptional response to developmental and environmental changes is likely to involve interaction of the core RNA polymerase with speciﬁc regulatory molecules (e.g., σ -factors), which might be available only under certain conditions. Additionally, various pathways routing developmental and environmental cues may regulate these factors.

8.4.1

Role of diverse and multiple promoters in developmental regulation of gene expression

The region upstream of the rrn16 operon is greatly conserved between different plant species. In vivo and in vitro dissection of the σ 70 -type PEP promoter (P1 or Nt-Prrn114; Vera and Sugiura, 1995; Allison et al., 1996) in tobacco plastids identiﬁed an essential hexameric sequence upstream of the −35 element (Figure 8.2; GTGGGA, rRNA operon upstream activator – RUA) that is conserved in monocot and dicot species. Interaction between the PEP and an RUA-binding transcription factor is proposed to replace the σ -factor interaction with the −10 element (Suzuki et al., 2003). Also in barley, maize, and pea the rrn operon is transcribed from the P1 σ 70 -type PEP promoter (Figure 8.3; Strittmatter et al., 1985; Sun et al., 1989; H¨ubschmann and B¨orner, 1998). Additionally, the rrn operon in tobacco has a second, NEP promoter (Figure 8.3; P2 or Nta-Prrn-62), inactive in chloroplasts, but functional in BY2 tissue culture cells and in plants lacking PEP (Vera and Sugiura, 1995; Allison et al., 1996). Conversely, in maize plastids there is no active NEP promoter directly upstream of the rrn operon (Silhavy and Maliga, 1998a). In spinach chloroplasts, transcription of the rrn operon initiates in a region, which contains typical −10/−35-elements active as rrn operon promoters in other species. However, the σ 70 -type promoter sequences are not utilized in vivo. Instead, transcripts initiate from a site between the conserved −10/−35 hexamers (Figure 8.3; Pc promoter; Baeza et al., 1991; Iratni et al., 1994, 1997). Sequences relevant for transcription initiation from Pc have yet to be identiﬁed. Interestingly, the Pc site appears to be faithfully recognized by partially puriﬁed mustard PEP in vitro (Pfannschmidt and Link, 1997). A good candidate for the Pc-activating factor in

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Figure 8.3 Differential rRNA operon promoter usage in spinach, Arabidopsis, tobacco, and barley. The schematic representation of the transcription initiation sites between trnV and rrn16, indicated by arrows, shows the distinctive promoters used in different species. P1 (open circle) and P2 (ﬁlled circle) mark transcription initiation sites by PEP and NEP respectively. Pc marks transcript initiation in spinach and Arabidopsis from a yet uncharacterized promoter. A dashed vertical line indicates an RNAprocessing site. Also denoted are marker genes used in transplastomic plants introducing the tobacco rrn promoter sequence in Arabidopsis (aadA: spectinomycin resistance) and the spinach sequence in tobacco (uidA: β-glucuronidase).

spinach is CDF2, the binding of which is correlated with transcription from Pc (Iratni et al., 1994, 1997). CDF2 is supposed to exist in two distinct forms, CDF2-A and CDF2-B. While CDF2-A represses transcription initiation of PEP at the rrn16 P1 promoter (named P2 in spinach), CDF2-B possibly binds NEP-2, a yet-to-becharacterized nuclear transcription activity, and initiates transcription from the rrn16 Pc promoter (Bligny et al., 2000). In Arabidopsis, rrn operon transcripts were mapped to both the major tobacco PEP P1 and the spinach Pc initiation sites (Figure 8.3). A study of rrn promoters in heterologous plastids indicates that tobacco plastids lack the factor required for transcription from Pc, while spinach has an intact P1 promoter but lacks the cognate P1 activator (Figure 8.3; Sriraman et al., 1998b). However, in tobacco a RUA region that is conserved in monocot and dicot species has been identiﬁed in vitro (Figure 8.2; Suzuki et al., 2003). It was suggested that the −10 element plays only a limited role in rrn16 P1 recognition and that σ -factor interaction is replaced in part by direct PEP–RUA (protein–DNA) interaction or by protein–protein interaction between the PEP and a putative RUA-binding transcription factor. The rrn16 promoters are an example of the diversity of promoter usage even in closely related species. Similarly, the tobacco atpB gene is transcribed from at least ﬁve NEP (PatpB-255, -502/-488, -611) and PEP promoters (PatpB-289, -329; Figure 8.4; Hajdukiewicz et al., 1997), but only one PEP promoter is driving this gene in Arabidopsis (PatpB-520/-515; D. Kaden, K. K¨uhn, and K. Liere, unpublished),

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Figure 8.4 Genes with multiple promoters. Schematic synopsis that shows the multiple PEP promoters of the barley psbD/C operon (HvupsbD), PEP and NEP promoters of the tobacco atpB (NtaatpB), and clpP genes (NtaclpP). Boxes below the line represent genes on the opposite strand, open arrowheads denote PEP promoters, ﬁlled black arrowheads Type I NEP promoters, and ﬁlled gray arrowheads Type II NEP promoters. The promoters are named based on their position with respect to the translation initiation site (+1).

whereas in maize one NEP (PatpB-601) and one PEP promoter (PatpB-298) are responsible for atpB expression (Silhavy and Maliga, 1998a). One NEP promoter precedes the tobacco accD gene (PaccD-129; Hajdukiewicz et al., 1997); however, two NEP promoters were found to transcribe the Arabidopsis accD gene (PaccD172, -251; D. Kaden, K. K¨uhn, and K. Liere, unpublished). In case of clpP the tobacco gene has two Type I NEP (PclpP-173, -511), one PEP (PclpP-95), and one Type II NEP initiation sites (PclpP-53; Figure 8.4; Hajdukiewicz et al., 1997; Sriraman et al., 1998a), the Arabidopsis gene has one PEP (PclpP-117) and one Type II NEP initiation site (PclpP-57; M. Swiatecka and K. Liere, unpublished; Sriraman et al., 1998a), whereas the maize gene is transcribed by a sole Type I NEP promoter (PclpP-111; Silhavy and Maliga, 1998a). Nonetheless, transcription of plastidial genes and operons by multiple promoters seems to be a rather common feature.

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For example, the psbD-psbC operon is transcribed from up to three different PEP promoters (Figure 8.4; Yao et al., 1989; Berends Sexton et al., 1990; Christopher et al., 1992; Wada et al., 1994; To et al., 1996; Hoffer and Christopher, 1997) and the tobacco rpl32 gene from two promoters far upstream of the coding region (NEP-Prpl32-1101, PEP-Prpl32-1030; Vera et al., 1996). While some genes are cotranscribed within an operon, they additionally possess an individual promoter upstream of their coding region (e.g., trnG; Meng et al., 1991; Kapoor et al., 1994; Liere and Link, 1994), or, vice versa, although transcribed by a strong individual promoter, they are cotranscribed with upstream genes (e.g., psbA; Nickelsen and Link, 1991; Liere et al., 1995). Although the role of most multiple promoters upstream of plastidial genes and operons is not fully understood, some are well characterized. While the blue-lightresponsive promoter (BRLP) of psbD-psbC is thought to differentially maintain the ability to resynthesize and replace damaged D2 and CP43 photosystem components in mature chloroplasts, mixed NEP and PEP promoters generally are believed to differentially express their cognate gene during plant development (reviewed in Liere and Maliga, 2001). NEP promoters are generally recognized in youngest and nongreen tissues early in plant development, while PEP takes over in maturating photosynthetically active chloroplasts (Bisanz-Seyer et al., 1989; Baumgartner et al., 1993; Hajdukiewicz et al., 1997; Kapoor et al., 1997; Emanuel et al., 2004). Consequently, both promoter types typically are found upstream of housekeeping genes which need to be transcribed during full plastidial development (Maliga, 1998). Recently, this simple model has been challenged by results from transcriptional reanalyses of tobacco rpo mutants lacking PEP (Krause et al., 2000; Legen et al., 2002). Large spurious transcripts initiated by NEP cover the entire plastome in these mutants, suggesting that besides selective promoter utilization, post-transcriptional processes also determine the transcript pattern of plastids. Further data derived from plastids in the developmental gradient in maize leaves suggest that although, as plastids mature, NEP may become less abundant, transcriptional activity by NEP increases while RNA stability declines. Hence, in a proposed model for maize plastidial biogenesis, NEP-controlled transcript accumulation changes little during plastidial development, while PEP-controlled transcript accumulation increases (Cahoon et al., 2004).

8.4.2 8.4.2.1

Transcription factors for selective promoter recognition Nuclear-encoded plastidial σ -factors

In eubacteria, speciﬁc transcription initiation requires a transcription factor (σ ), which is responsible for promoter recognition and contributes to DNA melting around the initiation site. Most eubacterial genomes contain genes for several σ -factors recognizing distinct promoters. Bacterial σ -factors have conserved functional regions and are grouped into two families, σ 70 and σ 54 (W¨osten, 1998; Ishihama, 2000). The σ 70 -factors are furthermore classiﬁed into primary (group 1, essential for cell growth), nonessential primary (group 2), and alternative σ -factors (group 3), responsible for recognition of certain promoters in response to

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environmental signals (Lonetto et al., 1992; Gruber and Bryant, 1997). Cyanobacteria, the ancestors of plastids, also have multiple σ -factors with distinct promoter speciﬁcity (Kaneko et al., 1996). Early on, biochemically puriﬁed σ -like activities in plant plastids were reported in Chlamydomonas (Surzycki and Shellenbarger, 1976), spinach (Lerbs et al., 1983), and mustard (B¨ulow and Link, 1988; Tiller and Link, 1993b). Furthermore, immunological evidence for σ -like factors was obtained in chloroplast RNA polymerase preparations of maize, rice, C. reinhardtii, and Cyanidium caldarium (Troxler et al., 1994). Moreover, multiple nuclear-encoded genes encoding eubacterial σ 70 -type factors were identiﬁed in the red algae Cyanidium caldarium (CcaA-C; Liu and Troxler, 1996; Tanaka et al., 1996) and Cyandioschyzon merolae (CmeSig1-4; Matsuzaki et al., 2004), suggesting specialized promoter recognition as in bacteria. Correspondingly, σ -factor families were identiﬁed in genomes of land plants such as Arabidopsis (AthSig1-6; Isono et al., 1997b; Tanaka et al., 1997; Fujiwara et al., 2000; Hakimi et al., 2000), mustard (SalSig1-3; Kestermann et al., 1998; Homann and Link, 2003), tobacco (NtaSigA1, -A2; Oikawa et al., 2000), rice (OsaSig1-4; Tozawa et al., 1998; Kasai et al., 2004), maize (ZmaSig1-5; Lahiri et al., 1999; Tan and Troxler, 1999; Lahiri and Allison, 2000), Physcomitrella patens (PpaSig1, -2, -5; Hara et al., 2001a,b; Ichikawa et al., 2004), as well as wheat (TaeSigA; Morikawa et al., 1999) and Sorghum (SbiSig1; Kroll et al., 1999). The N-terminal sequences of these σ -factors are typical for plastid-targeting transit peptides, which indeed have been demonstrated to confer plastidial targeting of GFP fusion proteins in vivo (Isono et al., 1997b; Tanaka et al., 1997; Kanamaru et al., 1999; Fujiwara et al., 2000; Lahiri and Allison, 2000; Oikawa et al., 2000; Hara et al., 2001a) or with radiolabeled proteins in vitro (Kestermann et al., 1998). Surprisingly, organellar targeting of some plant σ -factors was observed to exist not only into plastids but also into mitochondria. The AthSig5 transcripts are alternatively spliced within intron 1 establishing two initiation methionines (M1 and M2). Shorter peptides starting with M2 exclusively targeted GFP into plastids. However, GFP fusion proteins starting with M1 were localized into mitochondria. RNA analyses revealed that the longer (plastid) AthSig5 transcripts are exclusively located in ﬂowers, whereas the shorter (mitochondrial) transcripts were detectable in both ﬂower and leaf tissue (Yao et al., 2003). Furthermore, AthSig1::GFP fusion proteins also are colocalized into both plastids and mitochondria in tobacco protoplast import assays (H. Tandara and K. Liere, unpublished data). Similarly, dual targeting was shown for the maize ZmaSig2B protein by immunological and GFP fusion protein import studies. Interestingly, ZmaSig2B was biochemically copuriﬁed with RpoTm, the mitochondrial phage-type RNA polymerase (Beardslee et al., 2002), suggesting a possible role of these mitochondrial localized σ -factors in regulation of plant mitochondrial transcription. Historically, plastidial σ -factors were designated alphabetically or by numbers. Thus, in Arabidopsis, SigA, SigB, and SigC (Tanaka et al., 1997) were also named SIG2, SIG1, and SIG3 (Isono et al., 1997b), respectively. In an effort to unify the nomenclature, σ -factors sequences were subjected to phylogenetic analyses (http://sfns.u-shizuoka-ken.ac.jp/pctech; Shiina et al., 2005). Higher plant σ -factors

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belong to a monophyletic group. Although they are related to bacterial primary (group 1) and nonessential primary (group 2) σ 70 -factors, none ﬁt into alternative group 3 or are related to σ 54 -factors. Furthermore, the phylogenetic analyses revealed that plastidial σ -factors are split into at least ﬁve subgroups: Sig1, Sig2, Sig3, Sig5, and Sig6. Interestingly, only in Sig1 and Sig2 groups the monocot and dicot σ -factors are located on separate branches. Since most sequenced higher plant and moss genomes contain at least one gene for a Sig1-type σ -factor, and the Arabidopsis Sig1 homologs are highly expressed during chloroplast biogenesis, it is assumed that Sig1 represents the principal σ -factor in chloroplasts (Tanaka et al., 1997; Kestermann et al., 1998; Tozawa et al., 1998; Kanamaru et al., 1999; Morikawa et al., 1999). Sig2, Sig3, and Sig5 genes have been identiﬁed in various plant organisms, suggesting a correspondingly important role in plastidial transcription. Conversely, to date Sig4 has been identiﬁed only in Arabidopsis, and in comparison to the other σ -factors in light-grown plants its transcription is rather low (Tsunoyama et al., 2002). In addition, phylogenetic analysis suggests that the Sig2, Sig3, AthSig4, and Sig6 groups are related to Sig1 (Shiina et al., 2005), supported by the observation that intron sites of AthSig1, AthSig2, AthSig3, AthSig4, and AthSig6 are identical (Fujiwara et al., 2000). This suggests that these σ -factors may have originated from gene duplication event of one or more ancestral genes. The Sig5 group, however, only partially seems to be related to the bacterial alternative σ -factors (Tsunoyama et al., 2002; Shiina et al., 2005). Eubacterial σ 70 -factors contain four conserved domains (1–4) involved in binding the core RNA polymerase (Subdomain 2.1 and domain 3), hydrophobic core formation (Subdomain 2.2), DNA melting (Subdomain 2.3), recognition of the −10 promoter motif (Subdomain 2.4), and recognition of the −35 promoter motif (Subdomains 4.1 and 4.2; W¨osten, 1998; Paget and Helmann, 2003). Since these domains are also present in all known plastidial σ -factors, it is to be expected that they are responsible for transcription from σ 70 -type promoters in plastids. However, structural analysis seems not to provide answers if the role of the different plastidial σ -factors is to selectively modify promoter activity and if they possess distinct or overlapping promoter speciﬁcities. Based on the phylogenetic analyses, one might presume that both might be true, and that plastidial σ -factors group into general σ -factors involved in transcription of standard σ 70 -type promoters and specialized σ -factors responsible for recognition of exceptional promoters in response to developmental and/or environmental cues.

8.4.2.2

Role of σ -factor diversity in transcriptional regulation

In order to address this question (see Table 8.1 summarizing putative roles of σ -factors), several groups carried out in vitro reconstitution and transcription experiments using recombinant σ -factors, which furthermore demonstrated that indeed plant σ -factor genes encode functional plastidial σ -factors (Kestermann et al., 1998; Hakimi et al., 2000; Beardslee et al., 2002; Homann and Link, 2003; Privat et al., 2003). The mustard SalSig1, SalSig2, and SalSig3 σ -factors indeed conferred distinctive binding speciﬁcity of the E. coli core RNA polymerase for certain tested

ndhF psbD

General

Sig4 Sig5

Sig6

psbD BLRP

General

Sig3

Others AGF

General, preference for some tRNA promoters

General

PEP-regulating factors σ -factors Sig1

Sig2

Target

Binds to AAG box; transcription enhancer

Light-independent early primary/alternative σ -factor (?)

Light-independent early primary/alternative σ -factor (?) σ -Factor in plant stress response (?) σ -Factor in plant stress response (?) and regulating psbD BLRP via blue-/UVA-light

Primary/alternative σ -factor (?)

Alternative σ -factor, may possibly need activating factor(s)

Function

Transcription factors and regulators in higher plants

Protein

Table 8.1

Wheat

Barley

Maize

Arabidopsis

At2g36990

At5g13730 At5g24120

At3g53920

At1g08540

Mustard Arabidopsis

Mustard Arabidopsis Mustard Arabidopsis Arabidopsis

At1g64860

Gene

Arabidopsis

Plant

(continued )

Kim and Mullet, 1995 Nakahira et al., 1998

Hakimi et al., 2000 Privat et al., 2003 Kestermann et al., 1998 Homann and Link, 2003 Hakimi et al., 2000 Hanaoka et al., 2003 Kanamaru et al., 2001 Privat et al., 2003 Shirano et al., 2000 Tsunoyama et al., 2002 Homann and Link, 2003 Privat et al., 2003 Homann and Link, 2003 Favory et al., 2005 Nagashima et al., 2004a Tsunoyama et al., 2004 Tsunoyama et al., 2002 Ishizaki et al., 2005 Lahiri and Allison, 2000

Reference

rrn16(P1)

psaA psaA rbcL

CDF2-A

Region U-building protein Region D-building protein RLBP SibI T3K9.5 cpCK2 (PTK)

Interaction with a NEP-2 transcription activity? DNA-building; transcription regulation Inactivates NEP activity by binding to RpoTp

Interaction with CDF2?; transcription regulation

DNA building; transcription regulation DNA building; transcription regulation DNA building; transcription regulation AthSig1-building protein AthSig1-building protein

DNA building; transcription repression

Binds to AAG box; transcription enhancer part of AGF Binds to PGT box DNA building; transcription regulation

Function

Note: The question mark signiﬁes a proposed function rather than a proven one.

tRNAGlu

CDF-2B

rrn16

psbD BLRP rbcL

PGTF CDF1

NEP-regulating factors RPL4

psbD BLRP

Target

Transcription factors and regulators in higher plants (Continued)

PTF1

Protein

Table 8.1

Arabidopsis

Spinach

Spinach

Mustard

Spinach Spinach Tobacco Arabidopsis Arabidopsis Arabidopsis

Barley Pea Maize Spinach

Arabidopsis

Plant

trnE (ArthCt097)

X93160 (gi2792019)

At3g56710 At2g41180 At5g67380

At3g02150

Gene

Hanaoka et al., 2005

Bligny et al., 2000

Trifa et al., 1998

Baeza et al., 1991 Bligny et al., 2000 Cheng et al., 1997a Cheng et al., 1997a Kim et al., 2002 Morikawa et al., 2002 Morikawa et al., 2002 Baginsky and Gruissem, 2002 Baginsky et al., 1997 Ogrzewalla et al., 2002

Kim and Mullet, 1995 Lam et al., 1988

Baba et al., 2001

Reference

TRANSCRIPTION OF PLASTID GENES

201

promoters. While the psbA promoter was recognized by all three σ -factors, only SalSig1 and SalSig2 recognized the rbcL promoter. However, trnK, trnQ, rps16, and rrn16(PEP-P1) promoters were rather recognized by SalSig1 and SalSig3, but less efﬁciently by SalSig2 (Homann and Link, 2003). In Arabidopsis, similar experiments suggested that rather AthSig2 and AthSig3 confer speciﬁc recognition of the rbcL and psbA promoters than AthSig1, which recognized these promoters less efﬁciently (Hakimi et al., 2000; Privat et al., 2003). Given that both reconstitution systems consisted of plant σ -factors and the E. coli core RNA polymerase, the observed discrepancies in promoter recognition may be due to the heterologous transcription system with hindered abilities to identify species and/or PEP-speciﬁc regulatory elements on cis- and trans-factor level. Further efforts to address speciﬁc functionality of plant σ -factors in regulation of plastidial gene expression utilized characterization of their expression proﬁles. Consistent with a prominent role of PEP in leaves, most plastidial σ -factors are expressed in a light-dependent manner in green tissue but are silent in nonphotosynthetic roots (Isono et al., 1997b; Tanaka et al., 1997; Fujiwara et al., 2000; Oikawa et al., 2000). Moreover, expression of plastidial σ -factors seems to be differentially regulated during early Arabidopsis development. AthSig2, AthSig3, AthSig4, and AthSig6 but not AthSig1 and AthSig5 transcripts accumulate in 4-day-old seedlings (Ishizaki et al., 2005), while in 8-day-old seedlings transcript levels increase for all σ -factors (Nagashima et al., 2004a). Additionally, expression of Sig2 transcripts prior to Sig1 in developing leaves was reported for both Arabidopsis and rice, suggesting an early function of Sig2 in seedling development (Kanamaru et al., 1999; Kasai et al., 2004). Interestingly, unlike AthSig1 and AthSig2, AthSig3 protein accumulates in seeds and during early germination, which suggests regulation by post-transcriptional processes (Privat et al., 2003). A similar expression pattern was observed for the mustard SalSig3 factor, which accumulates rather in the dark- than in light-grown seedlings (Homann and Link, 2003). Hence, Sig3 may play a distinctive role in regulation of gene expression in etio- and/or proplastids. Similarly, ZmaSig6 was also detected in root, leaf base, and etiolated leaf tissue in maize (Lahiri and Allison, 2000). Therefore, it might be possible that Sig3 and Sig6 represent light-independent, early σ -factors regulating plastid gene expression during seedling growth and development. Contrarily, AthSig5 is expressed later in plant development, and furthermore, its RNA expression is redox-controlled downregulated (Fey et al., 2005) and rapidly induced by blue but not red light, which coincides with the blue-light-activated expression of psbD (Tsunoyama et al., 2002, 2004). In addition, to date AthSig5 is the only plant σ -factor activated by various stress cues (Nagashima et al., 2004b). Expression of some plastid genes in higher plants seems to be regulated by circadian rhythms (Nakahira et al., 1998). It is expected that this timing of plastid gene expression is controlled by nuclear factors, amid σ -factors being good candidates. Indeed, TaeSig1, NtaSig1, AthSig1, AthSig2, and PpaSig5 transcripts were shown to exhibit circadian or diurnal expression patterns (Kanamaru et al., 1999; Morikawa et al., 1999; Oikawa et al., 2000; Ichikawa et al., 2004). A recent approach to investigate gene function in plants is employment of knockout mutants or antisense lines. If plastids contain a primary σ -factor similar to most eubacteria, one would assume that inactivation of this gene would result in a drastic,

202

REGULATION OF TRANSCRIPTION IN PLANTS

most likely albino phenotype, by causing defects in PEP-dependent transcription of photosynthesis-related genes. However, examination of various Arabidopsis mutants of AthSig1, AthSig2, AthSig3, AthSig4, AthSig5, and AthSig6 did not reveal such a phenotype (Shirano et al., 2000; Kanamaru et al., 2001; Hanaoka et al., 2003; Privat et al., 2003; Nagashima et al., 2004b; Tsunoyama et al., 2004; Favory et al., 2005; Ishizaki et al., 2005). Still, a major breakthrough in revealing transcription speciﬁcity by σ -factors came by characterization of these plants. Cotyledons of AthSig6 knockout mutants displayed a transient pale green phenotype during early plant development, combined with a delay in light-dependent chloroplast development (Ishizaki et al., 2005). During this developmental stage the transcript pattern was found to be similar to that of rpo mutants, since transcript levels of most PEPdependent genes for photosynthesis components, rRNAs, and some tRNAs were decreased. Since the maize homolog ZmSig6 protein is expressed exclusively in tissue containing immature plastids (Lahiri and Allison, 2000), it was proposed that (Ath)Sig6 might be a general σ -factor serving PEP in an early, initial developmental stage. Nonetheless, given that after 8 days the mutant phenotype is restored to wild type it is plausible that other σ -factor(s) are able to take over AthSig6 function later in seedling development and plant growth (Shiina et al., 2005). Similarly, AthSig2 mutants displayed a pale green phenotype accompanied by reduced accumulation of plastid-encoded photosynthesis genes (Shirano et al., 2000; Kanamaru et al., 2001; Privat et al., 2003). Yet, accumulation of most of the photosynthesis gene transcripts was not reduced (Nagashima et al., 2004a). Interestingly, although it was previously shown that Sig2 is able to confer promoter speciﬁcity for psbA and rbcL promoters in vitro in Arabidopsis (Privat et al., 2003) and mustard (Homann and Link, 2003), several PEP-transcribed tRNAs including trnDGUC, trnE-UUC, trnM-CAU, and trnV-UAC were prominently reduced in AthSig2 knockout mutants (Kanamaru et al., 2001; Hanaoka et al., 2003) and antisense plants (Privat et al., 2003). Furthermore, overexpression of AthSig2 enhanced the transcription of trnE-trnD (Tsunoyama et al., 2004). Reduction of the photosynthesis-related components is suggested to be caused by defects in chlorophyll biosynthesis and plastid translation due to the decrease of trnE, an initiator of δ-aminolevulinic acid (ALA), and consequently chlorophyll synthesis. Hence Sig2 may have a primary role in driving transcription of certain plastid tRNAs, although it cannot be excluded that Sig2 is able to recognize other PEP promoters as suggested for psbA, psbD, and rbcL (Kanamaru et al., 2001; Hanaoka et al., 2003; Tsunoyama et al., 2004). Recently, characterization of an AthSig4 knockout mutant revealed a speciﬁc reduction in transcription of the plastid ndhF gene, resulting in a strong downregulation of the plastid NADH-speciﬁc dehydrogenase (NDH) activity (Favory et al., 2005). Therefore, ndhF expression and thus NDH activity seems to be regulated on transcriptional level, controlled by speciﬁc σ -factor AthSig4. Interestingly, regulation of NDH activity is involved in plant stress response (Casano et al., 2001) and leaf senescence (Zapata et al., 2005). Whether AthSig4 expression is modulated by such environmental or developmental parameters remains to be investigated. Some plastid genes are transcribed from promoters with unique architecture, e.g., the psbD BLRP, activated by blue and UVA-light (see Section 8.4.3). As shown by

TRANSCRIPTION OF PLASTID GENES

203

analyses of transcription in light-treated plants (Tsunoyama et al., 2002; Nagashima et al., 2004b), AthSig5 knockout plants, and overexpression studies (Nagashima et al., 2004b; Tsunoyama et al., 2004), AthSig5, a phylogenetically distinct σ -factor, is regulated by blue light and activates psbD BLRP transcription. Interestingly, analysis of a further AthSig5 knockout mutant showed embryo lethality (Yao et al., 2003). However, it is not understood yet why the different AthSig5 mutants exhibit these diverse phenotypes. PEP activity depends on the developmental stage of the plastids: it is downregulated in etioplasts and is active in chloroplasts (Rapp et al., 1992; DuBell and Mullet, 1995). Furthermore, rates of PEP transcription are higher in the light than in the dark (Shiina et al., 1998). Changes in PEP transcription activity were in part explained by changes in the phosphorylation state of σ -factors. Phosphorylation of σ -factors and the PEP enzyme itself has been shown to be an important regulatory event in chloroplast transcription (Tiller and Link, 1993a; Baginsky et al., 1997; Christopher et al., 1997). In mustard, a CK2-type kinase has been identiﬁed to be part of the chloroplast PEP-A complex (Ogrzewalla et al., 2002). This plastid transcription kinase activity, termed cpCK2, is able to phosphorylate biochemically puriﬁed sigma-like factors (SLFs) as well as subunits of the PEP-A complex. cpCK2 was proposed to be part of the signaling pathway controlling PEP activity, based on the observation that cpCK2 itself is differentially regulated by phosphorylation and redox state (Baginsky et al., 1999). The modiﬁcations of phosphorylation and SH-group redox state were shown to work antagonistically. A nonphosphorylated cpCK2 appears to be more active, but is inhibited by treatment with reduced glutathione (GSH), and vice versa, a phosphorylated nonactive enzyme could be reactivated by adding GSH. In vivo observations that cpCK2 isolated from plants grown under moderate light conditions effectively phosphorylated the associated PEP-A, while this was not observed with cpCK2 from plants subjected to 3 h of high light, corroborated these ﬁndings (Baena-Gonzalez et al., 2001). Therefore, light-dependent reduction of GSH would inactivate cpCK2, and dephosphorylation of PEP under high-light conditions would enhance PEP-dependent transcription. It remains unknown whether cpCK2 also regulated via extraplastidic signal chains mediated by phyto- and/or cryptochromes. Since cpCK2 orthologs have been identiﬁed in various plant species (Loschelder et al., 2004), it might well be that this kinase has an evolutionary conserved role in plastid redox-sensitive signal transduction. In bacteria, σ -factor activity is controlled by anti-σ factors (Ishihama, 2000). Plastid σ -factor AthSig1 associated proteins with plastid localization were identiﬁed in Arabidopsis (SibI and T3K9.5; Morikawa et al., 2002). They are not related to any proteins of known function and are light dependent, developmental, and tissuespeciﬁcally expressed, and thus may be involved in regulation of AthSig1 activity.

8.4.2.3

NEP transcription factors

As to the NEP subunit composition, to date one can only speculate based on information on the related mitochondrial RNA polymerases. Mitochondrial transcription complexes from humans, mice, Xenopus laevis, and yeast consist of a minimum of two components: the catalytic core enzyme (mtRPO, ∼120–150 kDa), and

204

REGULATION OF TRANSCRIPTION IN PLANTS

a speciﬁcity factor, which confers promoter recognition (mtTFB, ∼40–45 kDa). Despite poor overall sequence similarity, it recently has been shown that mtTFB factors belong to a family of RNA methyltransferases (Falkenberg et al., 2002; McCulloch et al., 2002; Rantanen et al., 2003; Seidel-Rogol et al., 2003). An additional component, which binds the DNA further upstream, enhances mitochondrial transcription in vitro (mtTFA, 20–25 kDa). This DNA-binding protein belongs to the HMG (high mobility group) family and may also facilitate the interaction with other trans-acting factors (reviewed in Jaehning, 1993; Shadel and Clayton, 1993; Tracy and Stern, 1995; Hess and B¨orner, 1999). To date, no mtTFA or mtTFB homologs have been isolated from plant mitochondria or plastids, and the presence of such proteins in plant organelles is unclear. A factor that is discussed to be involved in NEP transcription (summarized in Table 8.1) is the plastidial ribosomal protein L4 (RPL4; encoded by the nuclear Rpl4 gene). A role for RPL4 in transcription was proposed, as it copuriﬁes with the T7-like transcription complex in spinach (Trifa et al., 1998). The ribosomal protein L4 was shown to have extraribosomal functions in transcriptional regulation in prokaryotes (Zengel et al., 1980). The spinach and Arabidopsis Rpl4 genes have acquired a remarkable 3 extension during evolutionary transfer to the nuclear genome, which resembles highly acidic C-terminal ends of some transcription factors. A function for this protein in NEP or PEP transcription, however, has yet to be demonstrated. CDF2-B, a DNA-binding factor activity biochemically isolated from spinach chloroplast, has been reported to stimulate transcription of the rrn operon Pc promoter by a NEP activity yet to be characterized (Bligny et al., 2000). Besides, some nucleus-encoded σ -factors generally imported into plastids were found to additionally localize into mitochondria, suggesting an additional role in regulating transcription by phage-type RNA polymerases (H. Tandara and K. Liere, unpublished data; Beardslee et al., 2002; Yao et al., 2003). Yet, experimental data to link the activity of the bacterial-type plastidial σ -factors to the phage-type enzymes in mitochondria or plastids has still to be shown.

8.4.3

Effects of environmental factors and crosstalk between plastids and nucleus

Plant development is highly inﬂuenced by environmental factors. Plastid gene expression was shown to differentially respond to environmental cues (Chory et al., 1995; Link, 1996; Goldschmidt-Clermont, 1998; Barkan and GoldschmidtClermont, 2000). Therefore, in the last decades cis- and trans-elements regulating differential gene expression in plastids were the center of attention (see Table 8.1 for summary). In addition to the core promoter region, regulatory sequence motifs upstream the −35 region were found in the promoters of rbcL and psbD-psbC. The rbcL gene encodes the large subunit of ribulose-1,5-bisphosphate carboxylase and is transcribed from a single PEP promoter with well-conserved −35 and −10 elements and canonical spacing by 18 nucleotides (Shinozaki and Sugiura, 1982; Mullet et al., 1985; Reinbothe et al., 1993; Isono et al., 1997a). The importance of both the −35 and −10 box spacing and sequence for rbcL promoter strength was

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conﬁrmed by in vitro studies (Gruissem and Zurawski, 1985; Hanley-Bowdoin et al., 1985). An upstream element, conserved between maize, pea, spinach, and tobacco, was proposed to function as a binding site for the chloroplast DNA-binding factor 1 (CDF1) in maize (Lam et al., 1988). Interestingly, a segment of CDF1, region II, is reminiscent of the AT-rich UP element, which stimulates transcription by a factor of 30 in E. coli (Ross et al., 1993). However, a study of transplastomic plants with chimeric PrbcL::uidA constructs demonstrated that the rbcL core promoter is sufﬁcient to obtain wild-type rates of transcription (Shiina et al., 1998). Unless the constructs contained the rbcL 5 UTR, transcription rates of rbcL were signiﬁcantly reduced in dark-adapted plants, resulting in lower steady-state uidA mRNA levels in the dark. Therefore, stabilization of the rbcL mRNA via its 5 UTR is compensating for reduced rates of transcription in the dark and leads to light-dependent transcript accumulation. Nonetheless, another DNA-binding protein RLBP (rbcL promoterbinding protein) binds speciﬁcally to the rbcL promoter core in tobacco (−3 to −32; Kim et al., 2002). Only detectable in light-grown seedlings, RLBP is suggested to play a role in light-dependent rbcL transcription. Contrary to most photosynthetic genes, the rate of transcription of psbD-psbC remains high in mature chloroplasts (Klein and Mullet, 1990; Baumgartner et al., 1993; DuBell and Mullet, 1995). Responsible is the activation of the BLRP (Sexton et al., 1990). The psbD BLRP promoter architecture of various species studied to date is similar (Figure 8.2; Christopher et al., 1992; Wada et al., 1994; Allison and Maliga, 1995; Kim and Mullet, 1995; To et al., 1996; Hoffer and Christopher, 1997; Kim et al., 1999b; Thum et al., 2001). The architecture of the psbD BLRP promoter, which has two conserved upstream elements (PGT box, AAG box) and poorly conserved and closely spaced −10/−35-elements (15 nucleotides instead of the usual 17–19), was studied in transplastomic tobacco in vivo (Allison and Maliga, 1995). Deletion of part of the PGT box reduced mRNA levels, while subsequent deletion of the AAG-box sequences further reduced transcript levels. Thus, sequences directly upstream of the psbD promoter core are accountable for a light-activated transcript accumulation in tobacco. In rice, wheat, and barley, transcription from the psbD promoter in vitro depends on the −10 but not on the −35 promoter element (To et al., 1996; Satoh et al., 1997; Nakahira et al., 1998; Kim et al., 1999b). The AAG box of the barley promoter was shown to be the binding site for a nuclear-encoded AAG-binding complex in vitro (AGF; Kim and Mullet, 1995). However, binding activity of AGF to the AAG box is not correlated with psbD BLRP transcription activity (Nakahira et al., 1998). One of the components of AGF in Arabidopsis was cloned and named plastid transcription factor 1 (PTF1; Baba et al., 2001). Studies in PTF1-deﬁcient mutants revealed that indeed PTF1 is rather responsible in general transcriptional enhancement than in light-dependent activation of psbD transcription. Correspondingly, the PGT box is the binding site for PGTF, the PGT-binding factor, the activity of which is regulated by an ADP-dependent kinase (Kim et al., 1999a). A model based on these in vitro experiments in barley explains that constitutive binding of AGF to the upstream AAG element assists promoter recognition by PEP. Light-dependent transcriptional activation is mediated by PGTF binding to the PGT box. In the dark, PGTF phosphorylation results in loss of afﬁnity for the

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PGT element, which is thought to hinder transcription. Although psbD promoter architecture is highly conserved, it is unlikely that PGT is required for light-dependent transcription in various other plants. As it was shown for rice (To et al., 1996), wheat (Satoh et al., 1997), and barley in vitro (Kim et al., 1999b), and in vivo in transplastomic tobacco (Thum et al., 2001), the PGF box is not required for light-dependent activation in these plants. Therefore, the role of PGT and PGTF remains largely unknown. Based on the data available, it was proposed that Sig5 might act as a mediator of blue-light signaling in activating psbD BLRP transcription in blue light (Tsunoyama et al., 2002, 2004; Nagashima et al., 2004b), whereas AGF enhances psbD BLRP transcription by constitutively binding to the AAG box (Shiina et al., 2005). The signal transduction pathway is assumed to involve reception of blue light by cryptochromes and phyA (Thum et al., 2001; Mochizuki et al., 2004), further mediation by a protein phosphatase PP7 (Moller et al., 2003), and subsequent induction of Sig5 expression (Mochizuki et al., 2004). Sig5 then is imported into plastids where it together with AGF (PTF1) initiates psbD transcription. Furthermore, psbD BLRP activity is also regulated in a developmental and tissue-speciﬁc manner, since the Arabidopsis DET1 gene product downregulates the activity of psbD BLRP in young seedlings (Christopher and Hoffer, 1998). Plastids are under environmental control as shown for their gene expression, e.g., psbD BLRP. However, most intense is the control by light of plastidial differentiation from proplastids to either etioplasts (dark) or chloroplasts (light). Analyses of photomorphogenic mutants established the existence of different pathways to communicate light perception to plastids in order to control their development (Leon et al., 1998; Rodermel, 2001; Gray et al., 2003; L´opez-Juez and Pyke, 2005). However, these analyses also showed that retrograde or ‘plastid signals’ are controlling nuclear gene expression, depending on the developmental status of the plastid (Figure 8.5; Rodermel, 2001; Gray, 2003; Gray et al., 2003; Brown et al., 2005). Although both plastidial transcription and translation are necessary for the production of a ‘plastid signal’, it is not an immediate translational product of a plastidial gene (Oelm¨uller et al., 1986; Lukens et al., 1987), but rather part(s) of signal transduction pathways. Light is used as not only an energy source for photosynthesis, but also an environmental signal to regulate plant biogenesis and environmental adaptation. Apart from blue/UVA-light, illumination has been early hypothesized to control plastid gene expression via the physiological status of the plastid, e.g., redox conditions (Link, 2003; Pfannschmidt and Liere, 2005). Redox control of plastidial gene expression is interpreted as a selection force throughout evolution to retaining their genomes (Allen, 1993). First conﬁrmation for such a redox control was obtained by demonstrating that light supported incorporation of radioactive-labeled NADH into the RNA fraction of lettuce plastids (Pearson et al., 1993). Plastidial gene expression is controlled by photosynthetic activity on different levels such as RNA maturation (Deshpande et al., 1997; Liere and Link, 1997; Salvador and Klein, 1999) and translation (Danon and Mayﬁeld, 1994; Bruick and Mayﬁeld, 1999; Trebitsh et al., 2000; Zhang et al., 2000), by photosynthetic activity. Effects on plastidial gene transcription then were demonstrated by growing plants under light conditions generating an imbalance in excitation energy distribution between the photosystems

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Figure 8.5 Speculative model of the role of nuclear-encoded phage-type RNA polymerases in regulation of plastidial gene expression. The nuclear-located RpoTp gene encodes a phage-type RNA polymerase, which is part of the NEP transcription activity. NEP transcribes and therefore may regulate expression of the plastidial rpoB operon encoding subunits of the plastid-encoded RNA polymerase (PEP). PEP transcribes components of the photosynthetic complexes (PSI, PSII), which regulate nuclear transcription by generating diverse ‘plastid signals’ (ROS, reactive oxygen species). PEP also transcribes trnE encoding trnAGlu (Hess et al., 1992; Walter et al., 1995), which is required for the synthesis of δ-aminolevulinic acid (ALA). ALA is a precursor of the chlorophyll and heme biosynthesis, which are thought to provide plastid signals inﬂuencing nuclear transcription. Furthermore, tRNAGlu is assumed to developmentally inhibit NEP transcription activity by binding to RpoTp (Hanaoka et al., 2005). In turn, transcription of plastid genes and consequently the developmental stage of the plastid regulate expression and activity of nuclear-encoded, plastid phage-type RNA polymerase (RpoTp; Emanuel et al., 2004). Thus, the regulated network of nuclear and plastidial transcription machineries may be a key element for a concerted expression of genes located within plastids and the nucleus of the plant cell.

(PSII- and PSI-light, 680 and 700 nm, respectively; Pfannschmidt et al., 1999a,b; Fey et al., 2005). Preferential excitation of PSII results in a reduction of the electron transport chain, while a preferential excitation of PSI results in its oxidation. A change in photosystem stoichiometry correlated with respective changes in the transcriptional rates and transcript amounts of the plastidial genes for the reaction center proteins of PSII and PSI, psbA and psaAB. Further experiments demonstrated that the transcriptional regulation was independent from cytosolic factors such as photoreceptors, but that the redox state of the plastoquinone pool (PQ) is the major determinant for the changes in gene expression. When the PQ pool is mainly reduced, transcription of the psaAB operon is promoted while in the opposite case psbA

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transcription is increased. Opposite regulation of these genes has been recently found also in pea (Tullberg et al., 2000), Chlamydobotrys stellata (Kovacs et al., 2000), and Synechocystis PCC 6803 (Li and Sherman, 2000; El Bissati and Kirilovsky, 2001) suggesting that this mechanism represents an evolutionary old regulation. These data provide a ﬁrst model on how plants adapt to light quality gradients occurring in natural environments under low light intensities. Signal transduction from the PQ pool toward the level of transcription is not clear yet. However, a long-term response possibly represents an extended branch of the short-term response (the state transition), which is also regulated by the redox state of the PQ pool (Allen and Forsberg, 2001; Pursiheimo et al., 2001). The PQ oxidation site at the cyt b6 f complex functions as a sensor for the PQ redox state during state transition (Vener et al., 1997; Zito et al., 1999). A small 9-kDa protein of PSII, TSP9, has been discussed to be a putative signal transducer towards transcription. The putative DNA-binding protein TSP9 is partially released from PSII upon PQ reduction in spinach (Carlberg et al., 2003; Zer and Ohad, 2003). Identiﬁcation of an additional protein of 31 kDa capable of sequence-speciﬁc binding between positions +64 to +83 (region D) of the light dependentpsaAB PEP promoter region (Chen et al., 1993, 1997a) suggests the existence of yet unidentiﬁed transcription factors that forward redox signals. Furthermore, the Arabidopsis high chlorophyll ﬂuorescence mutant hcf145 shows decreased mRNA stability and transcription of psaA (Lezhneva and Meurer, 2004). Thus, HCF145 might be involved in transcriptional regulation of the psaA operon. However, further analysis of this promoter has yet to be reported. Microarray analyses of the inﬂuence of light quality on the transcriptome to assess redox-regulated transcription of nuclear-encoded plastidial genes (Fey et al., 2005) revealed a regulatory impact on transcription of genes for PEP components: rpoB (plastid-encoded β-subunit), AthSig5 (nuclear-encoded σ -factor), and SibI (nuclear-encoded Sig1-binding protein; Morikawa et al., 2002). PEP therefore is not only responsible for the redox regulation at the psbA and psaAB promoters, but apparently is also regulated transcriptionally via redox control. Interestingly, rpoB is transcribed by a nuclear-encoded phage-type RNA polymerase (Figure 8.5, RpoTp; Liere et al., 2004), suggesting a redox regulation of this enzyme. Since this analyses did not indicate differences in the glutathione redox state, as suggested by the redox control of PEP mediated by glutathione (Baginsky et al., 1999), it seems likely that several distinct redox control pathways to control plastidial transcription exist (Link, 2003; Pfannschmidt and Liere, 2005), depending on environmental conditions such as responses to low or high light. Extensive further studies, however, are necessary to resolve this important question. The barley mutant albostrians, with alternating stripes of white and green tissue, contains no detectable ribosomes in plastids of white tissue cells (Siemenroth et al., 1981). Transcript levels of some photosynthesis-related plastidial and nuclear genes are reduced or missing suggesting the existence of ‘plastid signals’ controlling nuclear gene expression (Hess et al., 1993, 1994). However, similar to rpoB knockout tobacco plants (Hajdukiewicz et al., 1997), plastid transcription of certain genes is maintained by a nuclear-encoded transcription activity (NEP; Hess et al., 1993; H¨ubschmann and B¨orner, 1998). Recently, transcript levels of the nuclear-encoded

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RpoTp, which is likely to represent NEP activity, and its plastidial target genes were analyzed throughout the developmental gradient of albostrians leaves (Emanuel et al., 2004). The results revealed a signiﬁcant inﬂuence of the developmental stage of plastids on expression and activity of RpoTp, indicating a plastid-to-nucleus signaling to coordinate expression of plastidial and nuclear-encoded RNA polymerases as a prerequisite of a concerted gene expression in both plastids and nucleus (Figure 8.5). Recently, a regulatory role, which links chlorophyll synthesis and the developmental switch from nucleus-encoded RNA polymerases to the plastid-encoded bacterial-type enzyme, has been proposed for the plastid-encoded tRNAGlu in Arabidopsis (Hanaoka et al., 2005). tRNAGlu is not only required for translation, but also for synthesis of ALA, a precursor of chlorophyll (Sch¨on et al., 1986). The tRNA was speciﬁcally bound by recombinant RpoTp in gel mobility shift experiments. Additionally, transcription from a putative plastidial accD NEP promoter sequence was inhibited by addition of tRNAGlu to in vitro transcription reactions with proplastid extracts from Arabidopsis. Hence, the authors suggested tRNAGlu to developmentally inhibit transcription by RpoTp (Figure 8.5). In bacteria, one of the most important processes to regulate gene expression is the so-called ‘stringent control’ enabling adaptation to nutrient-limiting conditions (Cashel et al., 1996). The effector molecule is guanosine 5 -diphosphate 3 -diphosphate (ppGpp), which binds to the core RNA polymerase modifying its promoter speciﬁcity (Toulokhonov et al., 2001). Stress-induced synthesis is mediated by ppGpp synthetases, RelA and SpoT, homologs of which were found in C. reinhardtii (Kasai et al., 2002), Arabidopsis (van der Biezen et al., 2000), and tobacco (Givens et al., 2004). Plastidial targeting has been demonstrated for some of these RSH termed proteins, suggesting an implication in ppGpp signaling in plastids. Given that RSH expression and plastidial ppGpp levels are clearly elevated by light and various abiotic and biotic stress conditions and that PEP activity is inhibited by ppGpp in vitro (Givens et al., 2004; Takahashi et al., 2004), it is conceivable that PEP might indeed be under control of a bacterial-like stringent response mediated by ppGpp. Interestingly, stress signals speciﬁcally induce transcription initiation from the psbD BRLP conferred by a special σ -factor, Sig5 (Nagashima et al., 2004b; Tsunoyama et al., 2004). However, target genes that are regulated by a plastidial stringent control have yet to be identiﬁed, which will elucidate the molecular mechanisms of transcriptional responses to plant hormones and environmental stress situations.

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9 Control of ﬂowering time Steven van Nocker and Maria Julissa Ek-Ramos

9.1

Introduction

The developmental switch from vegetative to reproductive growth – also known as ﬂowering – is a critical transition in the life cycle of ﬂowering plants. This transition is developmentally delayed until the plant has reached a stage of growth sufﬁcient to support fruit and seed production. Superimposed on developmental regulation is the ability to delay or initiate ﬂowering in response to environmental cues, such as photoperiod and temperature, in order to take full advantage of a seasonal climate optimal for reproduction. The switch to ﬂowering involves the activation of a select set of key regulatory genes that initiate extensive changes in gene activity in the shoot apical meristem (Figure 9.1). Cumulative research has revealed that the molecular mechanisms of ﬂowering are vastly complex and touch on most of the known eukaryotic mechanism of transcriptional regulation. This review will focus on transcriptional aspects of the individual regulatory pathways that have been deﬁned to regulate ﬂowering in the reference plant Arabidopsis thaliana, as well as how these pathways are integrated to activate genes that force inﬂorescence fate on the shoot apical meristem.

9.2

Regulation of FLC expression through the ‘autonomous pathway’

Although plant MADS-box genes are probably best recognized for their role in establishing identity of ﬂoral organs, a small but growing subset of genes are now known to play central roles in determining the timing of ﬂowering. Among these is FLC, which acts as a strong suppressor of ﬂowering. In rapid cycling accessions of Arabidopsis such as Columbia (Col) or Landsberg erecta (Ler), early ﬂowering depends on the activity of a mechanism(s) called the autonomous pathway. This pathway involves a class of genes that act in concert to silence FLC. The identities of two of these, FVE and FLD, suggest that the encoded proteins participate in FLC silencing through direct modiﬁcation of chromatin. FVE is one of ﬁve Arabidopsis genes encoding small WD-repeat proteins homologous to yeast MSI1, mammalian RbAp46 and RbAp48, and ﬂy p55/NuRF-55 (Ausin et al., 2004). These proteins interact with histones and are components of the chromatin assembly factor CAF-1, which deposits histones onto newly replicated DNA (review in van Nocker, 2003). In higher eukaryotes, MSI1-like proteins are also found in various transcriptional corepressor complexes (e.g., SIN3, Mi2/NuRD, and ESC–E(z)) that also may contain histone deacetylases (HDAs) such as RPD3 or HDAC1 (Zhang

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Figure 9.1 Regulatory map of ﬂowering in Arabidopsis. Pathways by which photoperiod, cold, and GAs inﬂuence ﬂowering are shown. Genes acting in common mechanisms are grouped. FLC-like genes, SOC1, and FT/TSF act as regulatory hubs, culminating in activation of the meristem identity genes AP1 and CAL.

et al., 1997; 1998; Tie et al., 2001; Kuzmichev et al., 2002). It has been suggested that MSI1-like proteins mediate interactions between nascent chromatin and transcriptional repressor complexes, potentially to help establish repressive marks, including deacetylation of histones H3 and H4, on new chromatin. Consistent with this, loss of FLC silencing in an fve mutant is associated with hyperacetylation of histone H3 and H4 within FLC chromatin (Ausin et al., 2004). What might be the enzymatic activity responsible for carrying out deacetylation of FLC chromatin in wild-type plants? The Arabidopsis genome encodes for at least 16 canonical HDAs (Pandey et al., 2002). Although most have not been characterized, genetic disruption of at least the RPD3/HDAC1 class HDAs, HDA6 and HDA19 (also called RPD3a or HD1), confers delayed ﬂowering (Wu et al., 2000; Tian and Chen, 2001; Tian et al., 2003; Probst et al., 2004). Thus, HDA6 and HDA19 might participate cooperatively in repressing FLC, although this has yet to be demonstrated. FLD has an intriguing story. This protein is one of four relatively uncharacterized Arabidopsis homologs of human lysine-speciﬁc demethylase 1 (LSD1), a nuclear, FAD-dependent amine oxidase that targets histone lysines for demethylation (Shi et al., 2004). FLD and its Arabidopsis siblings show a domain structure conserved with LSD1, and, in addition to its FAD-binding and amino oxidase domains, contain a SWIRM (SWI3, RSC8, MOIRA) domain considered to mediate protein– protein interactions.

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LSD1 is found in HDA-associated corepressor complexes in mammalian cells (Tong et al., 1998; You et al., 2001; Shi et al., 2003), and can act as a transcriptional repressor when tethered to an artiﬁcial promoter in vivo (Shi et al., 2004). The repressive function of LSD1 is linked to its ability to demethylate lysine 4 of histone H3 (H3K4). Lysine residues can be mono-, di-, or trimethylated, and in yeast and higher eukaryotes where studied, trimethylation of H3K4 is prevalent on nucleosomes in actively transcribed genes, especially at promoters and 5 regions (Santos-Rosa et al., 2002; Guenther et al., 2005). This modiﬁcation becomes enriched in these regions through transcription-associated replacement of histone H3 with H3.3 (Mito et al., 2005) and the activity of speciﬁc histone methyltransferases (HMTs) such as Set1/COMPASS (budding yeast), Trx (ﬂy), or MLL (human), and is thought to promote continual transcriptional activity (Ringrose and Paro, 2004; Kouskouti and Talianidis, 2005). The mechanism of amine oxidation of methylated lysines used by LSD1 (and probably related proteins as well) requires a protonated nitrogen, and so this mechanism is compatible with demethylation only of mono- or dimethylated lysines (Shi et al., 2004). Theoretically, then, LSD1 should be incapable of silencing an actively transcribed gene. For FLD, this would be consistent with an apparent role in maintaining, but not initiating, silencing. One of many possible functions for FLD on FLC chromatin is the demethylation of mono- or dimethylated H3K4 spontaneously arising through low-level ‘background’ transcription, constitutive HMT activity, or replication-associated incorporation of methylated H3 variants. An interesting observation is that like FVE, FLD appears to be required for hypoacetylation of histone H4 in FLC chromatin (He et al., 2003). A likely explanation is that loss of either FLD or FVE is sufﬁcient to disrupt the activity of a HDA protein complex in which both proteins participate. Deletion of a limited region within the ﬁrst intron of FLC proximal to the promoter results in loss of silencing and hyperacetylation similar to that seen in fve and ﬂd mutants, suggesting that this region could be targeted by either or both proteins (He et al., 2003). Further characterization of FLD and other LSD1-like proteins in Arabidopsis is eagerly awaited and should provide unique insights into the autonomous mechanisms. An additional chromatin-related protein that probably participates in the autonomous mechanisms is REF6 (Noh et al., 2004), one of a small group of Arabidopsis proteins containing jumonji (jmjN and jmjC) domains. These domains were ﬁrst identiﬁed in an interesting mouse protein, JUMONJI (JMJ), and related proteins (Balciunas and Ronne, 2000). A mutation in JMJ leads to severe developmental pleiotropy associated with abnormal stem cell proliferation (Takeuchi et al., 1995; Motoyama et al., 1997; Lee et al., 2000a), and JMJ has been shown to interact with E2F-regulated promoter sequences and repress transcription in collaboration with the retinoblastoma (Rb) protein, implicating JMJ in chromatin-based repression (Jung et al., 2005). jmjN/jmjC proteins also typically contain any of an assortment of domains associated with transcription and chromatin (Balciunas and Ronne, 2000). The jmjN domain in JUMONJI is required for DNA-binding and transcriptional repressor activity (Kim et al., 2003). Based on predicted structural similarity with a class of zinc-binding metalloenzyme domains known as cupins,

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Clissold and Ponting (2001) proposed that the jmjC domain could function as a metalloenzyme, and, further, that jmjC proteins also containing the jmjN domain and/or other chromatin-associated domains might participate in transcriptional repression through modiﬁcation of chromatin or associated proteins, potentially through protein hydroxylation. It has recently been postulated that a jmjC protein from ﬁssion yeast, Epe1, which is required for conﬁning heterochromatin at silenced domains (Ayoub et al., 2003), might function as a histone demethylase through oxidative demethylation of methylated lysine residues (Trewick et al., 2005). Similarly, it is conceivable that REF6 targets H3K4, including its trimethylated form, in FLC chromatin for demethylation. Features of four other autonomous pathway proteins suggest a role for premRNA processing in FLC expression. FCA and FPA encode proteins containing potential RNA-binding RRM domains, and the FLK protein contains K-homology putative RNA-binding domains (Macknight et al., 1997; Schomburg et al., 2001; Lim et al., 2004; Mockler et al., 2004). FY encodes a WD-repeat protein orthologous to budding yeast Pfs2, a component of the pre-mRNA cleavage and polyadenylation factor (CPF) protein complex required for 3 -end processing of pre-mRNAs (Simpson et al., 2003). FCA negatively regulates its own expression by promoting selection of a polyadenylation site near the 5 end of the FCA transcriptional unit, resulting in a truncated and dysfunctional transcript (Quesada et al., 2003). FY interacts with FCA in vitro, and this interaction is thought to promote the accumulation of the truncated FCA RNA in vivo and also to be required for repression of FLC (Simpson et al., 2003). Because regulation of FLC by FCA, FY, FLK, and FPA probably involves mainly post-transcriptional events, and because the potential mechanisms of programmed RNA processing involving these genes have been discussed at length (Amasino, 2003; Simpson et al., 2004; Quesada et al., 2005), it will not be covered further here. However, it should be mentioned that although an obvious target of post-transcriptional regulation is FLC, there is currently no evidence to support this, and thus regulation of FLC by these genes may be indirect. Another autonomous pathway gene, LD, encodes a nuclear protein containing a diverged homeodomain and a carboxyl-terminal region enriched in glutamine residues (Lee et al., 1994). Although these features suggest that LD could act as a transcriptional activator, potential targets have not yet been identiﬁed. Although originally considered to be devoted to nonenvironmental inputs and the regulation of FLC, it is now becoming clear that the ‘autonomous pathway’ moderates the effects of ambient temperatures on ﬂowering. Like many plants, most Arabidopsis accessions ﬂower appreciably later (i.e., producing more vegetative nodes) when grown at lowered ambient temperatures, such as 16◦ C. The earlier ﬂowering associated with increasing growth temperatures was found to be mediated by FVE and FCA, but surprisingly, was not associated with decreased FLC RNA abundance (Blazquez et al., 2003). Thus, FVE and FCA (and not unlikely, other autonomous pathway components as well) have a role in thermoregulation of ﬂowering time that is distinct from their repression of FLC. An additional indication that the autonomous mechanisms have more expansive functions was revealed by the observation that FY is an essential gene in Arabidopsis, with hypomorphic fy alleles

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affecting FLC expression and ﬂowering time relatively speciﬁcally (Henderson et al., 2005). FLC is subject to positive regulation as well as negative, and several ﬂoweringtime genes are known that act as strong activators of FLC. Probably the best known of these is FRIGIDA (FRI). FRI has received much attention, because allelic variation at FRI is a major determinant of the ﬂowering habit (i.e., annual vs. winter annual) among natural Arabidopsis accessions (Lee et al., 1993; Johanson et al., 2000). Most of the rapid cycling accessions of Arabidopsis used in laboratory work, such as Col or Ler, do not express FLC to appreciable levels because they carry loss-of-function mutations in FRI (Johanson et al., 2000). The predicted FRI protein is not conserved through evolution and does not exhibit strong homology with any other protein of known function, but exhibits coiled-coil domains, suggesting that it interacts with protein partner(s) (Johanson et al., 2000). FRI is a member of a small gene family in Arabidopsis, and at least two others in this family have been implicated in ﬂowering repression through upregulation of FLC (Michaels et al., 2004). The late ﬂowering conferred by FRI in wild-type plants reveals that activation of FLC by FRI is epistatic to the suppression of FLC by autonomous pathway genes; in the ‘standard’, rapid cycling Col-0 ecotype of Arabidopsis lacking FRI activity, loss of autonomous pathway gene function restores FLC expression and late ﬂowering (Michaels and Amasino, 1999, 2001). This is consistent with a mechanism whereby FRI limits the activity of autonomous mechanisms, possibly through the negative regulation of one or more components.

9.3

Chromatin-related pleiotropic regulators of FLC

In addition to FRI, an emerging number of activators of FLC are becoming characterized, and most appear to be related in some way to chromatin dynamics. Unlike FRI, in most cases reported, these act pleiotropically to affect other aspects of growth and development, suggesting that the factors are not speciﬁc regulators of FLC. One example of such a factor is PIE1, the closest relative among a large family of Arabidopsis proteins to budding yeast Swr1 (Noh and Amasino, 2003). Swr1 is a Swi2/Snf2-related ATPase required for incorporation of the H2A variant, Htz1 (conserved as H2A.Z in plants and higher eukaryotes), into chromatin (Krogan et al., 2003; Kobor et al., 2004; Mizuguchi et al., 2004). In vitro studies have implicated H2A.Z in destabilizing interaction between chromatin ﬁbers in highly condensed chromatin and promoting formation of 30-nm chromatin ﬁbers (Fan et al., 2002). This activity might promote a conformation that allows access to gene regulatory regions by DNA-binding transcription factors and other regulatory proteins while simultaneously precluding efﬁcient transcriptional initiation and elongation by RNA polymerase II (Pol II). Indeed, along with the observations that Htz1 occupies yeast promoter regions and becomes depleted from open reading frames upon transcriptional activation (Farris et al., 2005), these observations suggest that Htz1/H2A.Z (and by association, perhaps also Swr1) is involved in poising genes within the chromatin fabric for transcriptional activation (Fan et al., 2002). Although its

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biochemical activity has yet to be demonstrated, PIE1 shares several important features with Swr1, including the SNF2-homologous region, a HELICc domain found in an assortment of helicases and related proteins, a SANT domain implicated in DNA binding, and the SANT-associated HSA domain found in numerous DNA-binding proteins including helicases. Swr1 acts in concert with numerous other proteins in a chromatin-remodeling complex, SWR1c (Kobor et al., 2004; Mizuguchi et al., 2004), and given that many of these are also conserved (Kobor et al., 2004) it would not be surprising if the respective plant genes also are required for FLC transcription and functionally interact with PIE1. Indeed, it has recently been demonstrated that the Arabidopsis counterpart of the SWR1c actin-related protein Arp6 is required for full expression of FLC, and its mutation results in developmental pleiotropy similar to that seen in pie1 mutants (Choi et al., 2005; Deal et al., 2005). The biochemical function of Arp6 is similarly unknown, but the plant ARP6 protein is observed in foci at the nuclear periphery (Choi et al., 2005). This interesting and seemingly unusual property and the requirement for ARP6 in FLC activation are evocative of the observed physical association of GAL chromatin with nuclear pore complex proteins upon activation (Casolari et al., 2004; Misteli, 2005), potentially representing a more universal strategy of gene regulation (Casolari et al., 2005), and suggest that association with the nuclear envelope might be involved in FLC regulation. A potentially related mechanism that promotes FLC expression involves ESD4, one of three Arabidopsis proteins closely related to a SUMO protease from budding yeast called Ulp1. SUMO, a small ubiquitin-related protein, is post-translationally ligated to numerous cellular proteins including an assortment of nuclear factors related to transcription and chromatin structure (Gill, 2004). Similar to the nonproteolytic functions of ubiquitination, SUMOylation alters localization and/or activity of target proteins (Hilgarth et al., 2004), and SUMO-speciﬁc proteases such as Ulp1 participate in processingof immature SUMO and removal of SUMO from protein targets. ESD4 likely acts as a bona ﬁde SUMO-speciﬁc protease, because esd4 mutants show a striking accumulation of SUMO–protein conjugates (Murtas et al., 2003). In relation to transcription, SUMOylation is generally regarded as a repressive mechanism. Perhaps the best characterized targets of SUMOylation are transcription factors such as Sp3, Elk-1, c-Myb, and c-Jun (Verger et al., 2003). In the majority of cases studied, modiﬁcation of these proteins by SUMO is associated with decreased activation potential (Gill, 2004). SUMOylation has also been associated with reinforcing gene repression; the human Polycomb group (PcG; see below) repressor Pc2 is a SUMO ligase that targets the transcriptional corepressor CtBP (Kagey et al., 2003). In addition, SUMOylated histone H4 has been connected with transcription repression associated with recruitment of HDAs (Shiio and Eisenman, 2003). Interestingly, at least in the case of Sp3, repression is associated with sequestration of the transcription factor to the nuclear periphery (Ross et al., 2002). Ulp1 is localized to the nuclear periphery and has been shown to be afﬁxed to nuclear pores (Takahashi et al., 2000; Panse et al., 2003). ESD4 also is localized to the nuclear periphery (Murtas et al., 2003), and it is tempting to speculate that here it cooperates

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with ARP6. Further research into the phenomenon of subnuclear spatial regulation of transcription therefore should provide new insights into potential mechanisms of FLC regulation. Zhang et al. (2003) carried out a genetic screen for loss of FLC expression in a winter-annual genotype that led to the identiﬁcation of at least 20 distinct loci required for appreciable FLC expression, with 7 of these, designated the VERNALIZATION INDEPENDENCE (VIP) loci, deﬁning a single epistatic group. Based on their identical developmental pleiotropy, and the high degree of overlap of transcriptional proﬁles between at least the vip5 and vip6 mutants, these loci likely deﬁne a class of genes with identical function (Zhang and van Nocker, 2002; Zhang et al., 2003; Oh et al., 2004). Loss of these genes leads to silencing not only of FLC but also of the additional ﬁve members of the FLC gene family, MADS AFFECTING FLOWERING (MAF) 1–5 (He et al., 2004; Oh et al., 2004), all of which have the capacity to act as ﬂoral repressors (see below) (Ratcliffe et al., 2001, 2003; Scortecci et al., 2001). Four of the VIP genes (VIP4, VIP5, VIP6 (also called ELF8), and ELF7 (formerly VIP2)) encode homologs of distinct subunits of a transcriptional regulator from budding yeast called Paf1C (He et al., 2004; Oh et al., 2004). In yeast, Paf1C subunits associate with the initiating and elongating forms of Pol II (Mueller and Jaehning, 2002), and are bound within 5 regions and open reading frames of various genes (Krogan et al., 2002; Simic et al., 2003). Paf1C acts in transcriptional activation through assisting in ubiquitination of the carboxyl-terminal domain of histone H2B by the ubiquitin conjugating/ligase proteins Rad6/Bre1 (Henry et al., 2003; Ng et al., 2003a; Wood et al., 2003). At least in yeast, H2B ubiquitination is a prerequisite for establishment of methylation of histone H3 at lysines 4 and 79 by the HMTs Set1/COMPASS and Dot1, respectively, within genes (Wood et al., 2003), and Paf1C is required for association of these methyltransferases with Pol II. Trimethylation of H3K4 is uniquely associated with transcriptional activity (Hampsey and Reinberg, 2003), and the association between elongating Pol II and Set1/COMPASS, mediated by Paf1C, has been proposed as a mechanism to perpetuate the active state of genes (Ng et al., 2003b). This may involve recruitment by trimethylated H3K4 of chromatin-remodeling coactivators such as Isw1 (Santos-Rosa et al., 2003) or, in ﬂies, Brahma (Beisel et al., 2002). The plant counterpart of this mechanism may function in a similar manner to maintain the activation of FLC in winter-annual accessions. However, there is yet only scant evidence that the VIP complex has a role similar to its yeast counterpart. The VIP proteins do interact in vivo, and are found in the nucleus in a ∼0.5-mDa complex (Oh et al., 2004; our unpublished results). However, this complex also includes VIP3, a small WD-repeat protein that is conserved in higher eukaryotes but has no clear homology with any yeast protein (Zhang et al., 2003; Oh et al., 2004). Also, unlike yeast strains deleted for components of Paf1C, Arabidopsis vip mutants did not exhibit detectable ‘global’ defects in methylation at H3K4 or H3K79 when assayed on a bulk chromatin and total plant tissue basis (Oh et al., 2004). VIP3, VIP6/ELF8, and ELF7 are required for detectable levels of trimethylation of H3K4 within the FLC transcriptional unit (He et al., 2004; our unpublished results).

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However, it remains unclear if this reﬂects a direct inﬂuence of VIP activity. Loss of H3K4 methylation was also observed in FLC silenced in wild-type, vernalized plants (Bastow et al., 2004), suggesting that this might simply represent an indirect outcome of FLC silencing. What might carry out activating histone methylations at FLC? Mutations in the EFS gene, which encodes one of several Arabidopsis Set1/Trx-like HMTs, confer early ﬂowering (Soppe et al., 1999), and this is associated with a loss of FLC expression and H3K4 trimethylation within FLC chromatin, implicating this gene as a candidate (Soppe et al., 1999; Kim et al., 2005).

9.4

Vernalization-associated repression of FLC

In many plants, including winter-annual-habit accessions of Arabidopsis, the vegetative phase can be signiﬁcantly abbreviated by growth at very low temperatures, a phenomenon known as vernalization. In the last few years, several key studies have illuminated the involvement of chromatin dynamics, transcriptional silencing, and epigenetic mechanisms in the vernalization response in Arabidopsis. The molecular mechanism of vernalization involves the downregulation of FLC and at least a subset of the ﬁve paralogous MAF genes (Michaels and Amasino, 1999; Sheldon et al., 1999; Ratcliffe et al., 2001, 2003). Studies have focused on FLC, probably because of the obvious role of this gene in repressing ﬂowering in winter-annual accessions. Genetic screens for loss of vernalization sensitivity have identiﬁed several loci, and the molecular identities of three of these – namely VRN1, VRN2, and VIN3 – have been reported (Gendall et al., 2001; Levy et al., 2002; Sung and Amasino, 2004). The VRN1 protein contains B3-type DNA-binding domains at its carboxyl and amino termini; this is a plant-speciﬁc class of DNA-binding domain found in several transcription factors such as VP1 and ABI3 (Levy et al., 2002). VRN2 is one of three proteins in Arabidopsis related to the ﬂy PcG protein Suppressor of zeste 12 (Su(z)12) (Gendall et al., 2001). PcG is a class of proteins initially identiﬁed through a series of genetic screens for ectopic formation of sex combs. These proteins repress a subset of genes, including the homeotic hox genes, outside of appropriate expression domains, at least partly through maintenance of transcriptional-repressive chromatin modiﬁcations including methylation of lysines 9 and 27 of histone H3 (Czermin et al., 2002; Kuzmichev et al., 2002; Muller et al., 2002). Several of the PcG proteins are conserved among higher eukaryotes, including components of the HMT complex ESC–E(z) (also called PRC2). Among other subunits, this complex in ﬂies contains Su(z)12, the SET-domain protein enhancer of zeste (E(z)), and the WD-repeat proteins extra sex combs (Esc) and p55/NuRF-55. Whereas E(z) provides the catalytic core of the enzyme, Su(z)12 and NuRF-55 are required for interaction with nucleosomes (Nekrasov et al., 2005). VRN2 and other Su(z)12-related proteins contain two structural features of note (Birve et al., 2001). The ﬁrst is a predicted C2H2 zinc ﬁnger of the class known to mediate sequence-speciﬁc DNA binding. Potentially, this mediates binding to DNA

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in vivo, as mutations expected to disrupt the zinc ﬁnger of Su(z)12 abrogate its biological activity without affecting assembly of the associated ESC–E(z) complex, or its in vitro HMT activity. (Ketel et al., 2005). The second feature is a strongly conserved, ∼80-amino-acid region that has been termed the VEFS (for VRN2EMF2-FIS2-Su(z)12 box). Although this region of Su(z)12 is required for integrity of the ESC–E(z) complex, speciﬁc mutations in the VEFS box disrupt in vitro HMT activity without affecting complex formation (Ketel et al., 2005), suggesting a role beyond protein–protein interaction. VRN1 and VRN2 repress FLC in a manner characteristic of PcG mechanisms. In both vrn1 and vrn2 mutants, FLC RNA is downregulated during an extended cold treatment, similar to wild-type plants, but becomes strongly derepressed during subsequent growth at warmer temperatures (Gendall et al., 2001; Levy et al., 2002). Therefore, these proteins are required only for maintenance of FLC repression, and not for its initial silencing. At least VRN2 also has a promotive role in ﬂowering in nonvernalized plants, potentially as a suppressor of FLC outside of its typical expression domains (Gendall et al., 2001). In addition to the homology between the VRN2 and Su(z)12 proteins, molecular evidence suggests that VRN2 (and VRN1) might participate in an ESC–E(z)-like HMT. Like ESC–E(z), the activity of VRN2 and VRN1 is associated with methylation of H3K9 and H3K27. This occurs within promoter and intronic regions of FLC formerly demonstrated to contain cis-elements required for maintenance of repression (Sheldon et al., 2002). VRN1 is presumed to work downstream of VRN2 to assist in methylation of H3K9, because H3K27 methylation within FLC is still observed in a vrn1 mutant (Bastow et al., 2004). What might be the catalytic core of this methyltransferase? Based on the homologous components seen in ESC–E(z) complexes in ﬂies and humans, VRN2 probably interacts with one or more E(z)related proteins in plants. Good candidates are the E(z) homologs CURLY LEAF (CLF) and/or SWINGER (SWN), both of which physically interact with VRN2 in yeast (Chanvivattana et al., 2004). The VIN3 protein contains an internal motif resembling a PHD (plant homeodomain)-type zinc ﬁnger, common in proteins that participate in chromatin regulation (Aasland et al., 1995). In contrast to VRN1 and VRN2, VIN3 is required for the initial silencing of FLC during cold (Sung and Amasino, 2004). VIN3 RNA accumulates during extended cold exposure with kinetics similar to those seen for loss of FLC RNA expression, suggesting direct regulation. VIN3 activity is also associated with deacetylation of histone H3 within FLC promoter and intronic regions (Sung and Amasino, 2004). The mechanisms involved in upregulation of VIN3 RNA during cold, and VIN3 targeting of FLC for repression, are intriguing, as VIN3 appears to be the most ‘upstream’ component of the vernalization mechanism identiﬁed so far. Although the importance of the PHD domain in VIN3 has not been addressed, and these domains have traditionally been perceived as mediating protein–protein interactions, it is interesting that PHD ﬁngers of several animal proteins have been shown to bind phospholipids, and at least in one case phospholipid binding was required for chromatin association and activity (Gozani et al., 2003). The involvement of

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phospholipid signaling in plant stress responses is becoming increasingly documented (van Leeuwen et al., 2004), and it is conceivable that VIN3 represents a target. Indeed, ectopic expression of VIN3 in transgenic plants under nonvernalizing conditions is insufﬁcient to promote ﬂowering, suggesting that vernalizationassociated accumulation of VIN3 is not alone a regulatory step, but that VIN3 function requires the participation of other cold-associated mechanisms (Sung and Amasino, 2004). VIN3, VRN1, and VRN2 likely function as general regulators of the vernalization response rather than FLC-speciﬁc factors; vernalized vin3, vrn1, or vrn2 mutants ﬂower as late as nonvernalized plants, and loss of VIN3 decreases vernalization sensitivity even in an ﬂc mutant (Gendall et al., 2001; Levy et al., 2002; Sung and Amasino, 2004). Obvious additional targets are the MAF genes, although this has yet to be demonstrated. Vernalization-associated downregulation of FLC and maintenance of its repression provides an attractive model to study the sequence of events associated with epigenetic gene silencing. An interesting and unexplored question is the means by which PcG silencing overcomes the reinforced transcriptional activity potentially set up by the Paf1C-like (VIP group)/Trx-like (EFS) mechanisms. A possible scenario can be constructed based on cumulative studies of antagonism between PcG and Trx mechanisms, in animals, which suggest that PcG mechanisms target a subset of genes for repression opportunistically in response to transcriptional inactivity (Klymenko and Muller, 2004). Upon cessation of Pol II activity, transcriptionalpromotive epigenetic marks on FLC chromatin, including trimethylation of H3K4 and acetylation of H3/H4, could be erased, either actively by enzymatic mechanisms (see above) and/or by replication-independent histone exchange, or through dilution by nascent histones over the course of several cell divisions. FLC chromatin would then be a suitable substrate for H3K9/K27 methylation mediated by VRN2 and VRN1. This scenario is consistent with studies in ﬁssion yeast and animals, revealing that acetylation of H3K9 precludes its methylation, and that H3K9 methylation also requires deacetylation of additional lysine residues in the H3 amino terminus (Rea et al., 2000; Nakayama et al., 2001). Given the observed interaction between HDAs and ESC–E(z) (Tie et al., 2001), it may follow that HDAs recruited to FLC, potentially by VIN3, assist in recruiting the PcG machinery. Although information in plants is limited, studies in animals and ﬁssion yeast suggest that methylation at H3K9 within euchromatic regions can promote the formation of localized heterochromatin and long-term gene silencing, suggesting a precedence for the stable repression of FLC in vernalized plants. This may involve LIKE HETEROCHROMATIN PROTEIN 1 (LHP1), also known as TERMINAL FLOWER 2 (TFL2), the Arabidopsis homolog of HP1 proteins (Gaudin et al., 2001; Takada and Goto, 2003). HP1 proteins can bind methylated H3K9 through a chromodomain, and are common protein constituents of heterochromatin (Bannister et al., 2001). Human Su(z)12 interacts with HP1 (Yamamoto et al., 2004), and it has been suggested that these interactions could be a mechanism for spreading of heterochromatin into adjacent euchromatic regions, a well-recognized phenomenon

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in ﬂies termed position-effect variegation (Elgin, 1996; Yamamoto et al., 2004). It is tempting to speculate that such a mechanism could reproduce epigenetic silencing marks on nascent histone octamers following DNA replication, using the persisting octamers as a template. Although LHP1/TFL2 acts in ﬂowering (see below), a potential role in vernalization-associated FLC silencing has not been explored. A fascinating but relatively unexplored question is the relationships between the autonomous and vernalization pathways. Although both target FLC, there is yet no indication that the pathways utilize common components. The autonomous pathway mutants that have been characterized so far are responsive to vernalization, suggesting that the respective proteins do not play a crucial role in initiating or maintaining FLC repression associated with vernalization. Silencing of FLC in the rapid cycling accession Ler, which is dependent on activity of the autonomous mechanisms, does not obviously involve H3K9/H3K27 methylation (Bastow et al., 2004), suggesting that PcG repression is not relevant to autonomous pathway functions. However, FVE-related proteins (i.e., MSI1 homologs) participate in ESC–E(z) in humans and ﬂies (Kuzmichev et al., 2002; Muller et al., 2002), and so Arabidopsis MSI1-like proteins might be expected to cooperate with VRN2. Additionally, biochemical evidence (described above) suggests that both mechanisms utilize a HDA, probably of the RPD class. In this respect, exploration of potential roles of additional members of the MSI1 and RPD gene families in vernalization should be informative.

9.5

Transcriptional repression of ﬂowering by FLC

A major downstream target of FLC is another MADS-box gene, SOC1 (formerly also known as AGL20) (Lee et al., 2000b; Samach et al., 2000). FLC represses SOC1, and probably does so directly. In vitro, FLC binds to a segment of DNA from the SOC1 promoter containing a CArG box (the known binding site of other MADS-box factors) (Hepworth et al., 2002). This is likely to be relevant in vivo, because deletion of this promoter region abrogated much of the repressive effect of FLC on SOC1 expression (Hepworth et al., 2002). SOC1 is also targeted by other ﬂowering pathways (see below) and has been termed a ‘ﬂowering integrator’ gene. Other targets of FLC are the FT and TSF genes. In genotypes that express high levels of FLC due to disruption in the autonomous pathway or presence of active FRI alleles, FT and TSF RNA levels were reduced; in addition, the delayed ﬂowering of these genotypes is mostly suppressed by constitutive transgenic expression of FT and TSF (Samach et al., 2000; Hepworth et al., 2002; Michaels et al., 2005; Yamaguchi et al., 2005). FT and TSF play an additional, and probably more important, role in photoperiodic induction of ﬂowering, and are discussed in more detail below. MADS-box proteins including FLC are expected to interact with their binding sites as homo- or heterodimers or tetramers, and also to interact with other transcription-related proteins. Surprisingly, in light of the fact that so many studies have targeted FLC, binding partners of FLC are yet unknown, and this clearly is an attractive area for further research.

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Transcriptional regulation in the photoperiodic induction of ﬂowering

The promotion of ﬂowering by long-day photoperiods in Arabidopsis is mediated through what is probably the best known transcriptional regulator of ﬂowering, CONSTANS (CO) (Putterill et al., 1995). CO is one of numerous plant genes that are regulated by an endogenous (circadian) clock (Suarez-Lopez et al., 2001). Cyclic transcription of CO is regulated partly by the F-box protein FKF1, through its interaction with and destabilization of CDF1, a Dof-zinc-ﬁnger family transcription factor that binds to the CO proximal promoter to repress CO expression (Imaizumi et al., 2005). It has been proposed that gradual accumulation of FKF1 throughout the day progressively eliminates promoter-bound CDF1, derepressing CO in the afternoon (Imaizumi et al., 2005). When high levels of CO RNA and protein are reached during the light period, as in the evening hours in inductive, long-day photoperiods, CO is able to efﬁciently activate downstream ﬂowering genes (below). The molecular mechanisms involved in circadian clock function upstream of CO expression, and the role of light in these mechanisms, have been the subject of numerous excellent reviews (Hayama and Coupland, 2003; Salome and McClung, 2004; Searle and Coupland, 2004) and will not be discussed in detail here. CO is a nuclear protein containing B-boxes, the conserved, ∼40-amino-acid zinc-ﬁnger motifs that are found in numerous transcription factors. B-boxes have been best characterized in animal proteins as protein interaction domains, and have not been demonstrated to participate in DNA binding (Borden, 1998). The carboxyl terminus of CO contains a CCT (CONSTANS, CO-like, TOC1) motif, a ∼43-aminoacid module that is enriched in basic amino acids. This domain is found also in a small number of Arabidopsis proteins including other CONSTANS-related proteins (see below), the PSEUDO-RESPONSE REGULATORS (APRRs) including the endogenous clock component TOC1, and in a few GATA-type presumed transcription factors. It has been proposed to participate in nuclear localization and/or protein interactions (Strayer et al., 2000). CO is one of at least 17 members of a group of related genes in Arabidopsis called CONSTANS-LIKE (COL). The encoded proteins are predicted to contain B-box zinc ﬁngers and often also carboxyl-terminal CCT domains. Where studied, the COL genes do not have an obvious role in ﬂowering (Ledger et al., 2001). A possible exception is COL9; constitutive overexpression of COL9 in transgenic plants delayed ﬂowering, and late ﬂowering could be abrogated by parallel overexpression of CO (Cheng and Wang, 2005). Also, COL9 overexpression did not affect the circadian phase or period of any clock-regulated gene tested, including CO, but did affect the amplitude of CO oscillations (Cheng and Wang, 2005). Therefore, COL9 may participate in ﬂowering regulation through CO, but downstream or independently of the circadian clock. Samach et al. (2000) identiﬁed genes that are likely to be direct targets of CO, using a constitutively expressed fusion of CO to the glucocorticoid receptor. This fusion protein accumulates in the cytosol and can translocate into the nucleus in the presence of a steroid hormone such as dexamethasone (DEX). When DEX is

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applied together with the translational inhibitor cycloheximide (CYC), the fusion protein activates only its direct transcriptional targets. Early targets of CO that were identiﬁed through this approach included the FT gene (Samach et al., 2000). Wigge et al. (2005) similarly searched for early targets of CO, using transcriptional proﬁling to identify genes that were activated soon after a transition to an inductive photoperiod and dependently on CO expression. This approach also identiﬁed FT as an early target of CO. Under long-day conditions, the diurnal expression pattern of FT RNA roughly corresponds with that of CO RNA (Suarez-Lopez et al., 2001). FT showed little or no transcriptional response to lengthened photoperiods in a co mutant, suggesting a lack of even partially redundant pathways of activation (Wigge et al., 2005). The close functional relationship between CO and FT was also revealed by the substantially similar transcriptional proﬁles seen in co and ft mutants (Schmid et al., 2003). However, CO expression is capable of promoting ﬂowering to a small extent even in an ft mutant, suggesting that CO targets additional ﬂowering gene(s) (An et al., 2004). Indeed, Yamaguchi et al. (2005) found that the FT paralog TWIN SISTER OF FT (TSF) was induced quickly in response to CO activation. In addition, like FT, TSF exhibited increased expression in response to extended photoperiods, was required for appropriate timing of ﬂowering under these conditions, and accelerated ﬂowering when expressed ectopically (Michaels et al., 2005; Yamaguchi et al., 2005). Also similar to FT, rapid activation of TSF by CO was seen even in the presence of CYC. This suggests that TSF promotes ﬂowering as a direct target of CO, partially redundant with FT. However, loss of TSF has a much lesser effect on ﬂowering, probably at least partly due to its more limited expression pattern (Yamaguchi et al., 2005). Both genes are expressed in vascular (phloem) tissues, but in distinct parts of the plant, with FT expression seen in cotyledons and leaf blades and TSF expression seen mainly in the hypocotyl and petiole (Yamaguchi et al., 2005). Coregulation of FT and TSF genes probably is not surprising, as these proteins are closely related (Kobayashi et al., 1999). Another member of the FT/TSF gene family, TERMINAL FLOWER 1 (TFL1), is upregulated in the center of the shoot apex during the ﬂoral transition, and responds quickly to CO activation (Simon et al., 1996), and thus represents an additional potential target of CO.

9.7

Activation of SOC1 by CO

The SOC1 gene, described above as a downstream target of FLC, was identiﬁed as a mutation capable of suppressing much of the ﬂowering-promotive effect of overexpression of CO (Onouchi et al., 2000), and also by Samach et al. (2000) as an early transcriptional target of CO. Activation of SOC1 by CO in the system used by Samach et al. (2000) was insensitive to CYC, and so is probably mediated directly. The transcriptional basis of this activation was addressed in a series of experiments utilizing gel-shift assays and expression of promoter truncations in transgenic plants (Hepworth et al., 2002). Deletion of a limited region of the SOC1 promoter abrogated most of the activation of SOC1 by CO, suggesting that CO

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targets this region. However, recombinant CO apparently does not bind to SOC1 promoter DNA, at least in vitro (Hepworth et al., 2002). This is consistent with the observation that the CO protein does not exhibit any known DNA-binding domains (see above), and suggests that CO should cooperate with additional, DNA binding factors to activate SOC1. In contrast to FT, which shows absolute dependency on CO, SOC1 could be induced by a switch to inductive photoperiods even in a co mutant (Wigge et al., 2005), an effect potentially mediated through gibberellins (see below). An interesting question is the mechanism of coregulation of SOC1 by CO and FLC. SOC1 is expressed most strongly in leaves, but is detected in leaf primordia and the shoot apex of photoperiod-induced plants (Samach et al., 2000; Wigge et al., 2005). Expression of FLC is preferential for apical regions including the shoot apex, but also is seen in leaves (Michaels and Amasino, 1999); so, it is unclear where the relevant integration of FLC and CO signaling takes place. The CO-targeted promoter region identiﬁed by Hepworth et al. (2002) is distinct from that containing the CArG box demonstrated to bind FLC (above), and so ﬂowering inputs from FLC and CO are mediated independently at the SOC1 promoter. High levels of FLC blocks transcriptional activation of SOC1 by CO, and it was hypothesized that promoterbound FLC might assemble a repressive protein complex (Hepworth et al., 2002). In addition to its apparent direct activation by CO, SOC1 also appears to be activated through FT and TSF. Although SOC1 clearly can be induced by long days in the absence of FT or TSF, SOC1 RNA is decreased in an ft mutant (Lee et al., 2000b; Schmid et al., 2003; Yamaguchi et al., 2005) and increased in 35S::TSF and 35S::FT plants (Michaels et al., 2005; Moon et al., 2005; Yamaguchi et al., 2005). This positions SOC1 in the ﬂowering regulatory pathway ‘downstream’ from FT and TSF. An additional and very interesting regulatory output of the photoperiodic pathway mediated through CO/FT is the upregulation of a gene encoding a precursor of a microRNA, mir172 (Schmid et al., 2003). mir172 targets a set of previously uncharacterized, APETALA2 (AP2)-like ﬂowering repressors, including ¨ TOE1, TOE2, SCHLAFMUTZE, and SCHNARCHZAPFEN, for translational and post-transcriptional downregulation (Aukerman and Sakai, 2003; Schmid et al., 2003). In maize, mir172 is also implicated in regulating ﬂowering time through downregulation of the AP2-like gene glossy 15 (gl15) (Lauter et al., 2005), suggesting a conserved and important role in ﬂowering.

9.8

Chromatin-related mechanisms of photoperiod pathway regulation

Chromatin-based mechanisms of transcription are also important for photoperiodic induction of ﬂowering. FT is repressed by mechanisms involving the chromatinrelated factors, EARLY BOLTING IN SHORT DAYS (EBS) and LHP1/TFL2 (described above) (Kotake et al., 2003; Pi˜neiro et al., 2003; Takada and Goto, 2003). FT RNA accumulates to higher levels in ebs mutants throughout the diurnal cycle, and this is especially evident in the dark phase when plants are grown in a short-day

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(8 h light/16 h dark) photoperiod (Pi˜neiro et al., 2003). Interestingly, the phase or amplitude of CO RNA cycling was apparently unaffected in ebs mutants. In addition, CO was not required for substantial accumulation of FT RNA in an ebs mutant. Although a mechanism to explain these observations has yet to be proposed, this implicates EBS in repression of FT expression independently of or downstream from CO, particularly during the dark phase (Pi˜neiro et al., 2003). An additional target of EBS is TSF (Yamaguchi et al., 2005). EBS RNA is prevalent in shoot and ﬂoral apices, and in young leaf and ﬂower primordia, especially in outer cell layers (Pi˜neiro et al., 2003). The observation that EBS RNA is expressed constitutively with respect to the ﬂoral transition suggests that EBS does not have a regulatory role in ﬂowering. In addition, the developmental pleiotropy seen in ebs mutants (Gomez-Mena et al., 2001), which is not observed in transgenic plants overexpressing FT or TSF, suggests that its role is not conﬁned to regulation of these genes. Based on epistatic interactions and phenotypic similarity with mutants defective in gibberellic acid (GA) signaling, Gomez-Mena et al. (2001) suggested that EBS might play a role in the induction of ﬂowering by GAs. However, to date, there is no clear evidence that GAs directly participate in regulation of FT (see below) and so this potential role remains uncertain. Unlike many other chromatin-related proteins that participate in ﬂowering time, loss of EBS expression had no discernible effect on expression of FLC (Pi˜neiro et al., 2003). EBS encodes a nuclear protein that contains a so-called bromoadjacent homology (BAH) region. Although its function is unknown, the BAH region is seen in numerous proteins with chromatin-related activities, including yeast RSC1 and RSC2 subunits of the ATP-dependent chromatin-remodeling factor RSC, the conserved cytosine methyltransferases, and, in plants, the chromodomain DNA methyltransferases (chromomethylases). Most of these proteins contain several other conserved chromatin-related domains. However, EBS is a relatively small protein and does not contain any other recognizable features except for a PHD-type Zn ﬁnger. As the PHD ﬁnger is supposed to mediate protein–protein interactions, EBS may operate as part of a larger protein complex and contribute a BAH domain for this protein. In fact, overexpression of EBS in Arabidopsis leads to phenotypic defects similar to those seen in ebs loss-of-function mutants, and one explanation for this is a dominant negative effect of enhanced gene dosage on activity of a potential protein complex (Pi˜neiro et al., 2003). EBS is related to two additional proteins in Arabidopsis with similar domain structure; one of these, termed SHORT LIFE (SHL), is a nuclear protein required for normal ﬂowering time (Mussig et al., 2000). However, unlike EBS, SHL probably normally acts to promote ﬂowering, as reduced SHL activity due to antisense expression resulted in delayed ﬂowering, and ﬂowering was accelerated when SHL was ectopically expressed to high levels (Mussig et al., 2000). Although the position of SHL in ﬂowering pathways has not been genetically deﬁned, delayed ﬂowering of SHL-antisense plants is associated with repression of SOC1 (Mussig et al., 2003), suggesting that SHL targets SOC1 or its upstream regulators. In mutants defective for the LHP1/TFL2 gene, FT is expressed prematurely to higher levels, and ectopically, suggesting that LHP1/TFL2 moderates the proper

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spatial and temporal activation of FT (Takada and Goto, 2003). Repression of FT by LHP1/TFL2 and its activation by CO are likely mediated through separate pathways, because FT expression is still responsive to daylength or ectopic CO expression in plants lacking lhp1/tﬂ2 activity, and ectopic expression of FT associated with loss of LHP1/TFL2 is seen even in a co mutant (Takada and Goto, 2003). Interestingly, LHP1/TFL2 does not seem to participate in repression of TSF (Yamaguchi et al., 2005). LHP1/TFL2 is also important for silencing a variety of additional genes important for plant development (Nakahigashi et al., 2005). Although HP1 outside of plants has been best characterized as a constituent of constitutive heterochromatin, it also has known functions within euchromatin, including assisting Rb in silencing of E2F-regulated cell cycle genes (Nielsen et al., 2001), suggesting a precedent for the direct involvement of LHP1/TFL2 in euchromatic gene silencing. Two additional transcriptional components that participate in photoperiodic ﬂowering are the MADS-box genes, SHORT VEGETATIVE PHASE (SVP) and MAF1 (also called FLM). Mutation in either gene causes early ﬂowering in noninductive photoperiods, and both can confer delayed ﬂowering when constitutively expressed (Hartmann et al., 2000; Ratcliffe et al., 2001; Scortecci et al., 2001). These proteins may work closely together, because a svp/maf1 double mutant did not exhibit earlier ﬂowering relative to either single mutant, and SVP is required for the late ﬂowering conferred by constitutive expression of MAF1/FLM (Scortecci et al., 2003). The precise roles of these factors in ﬂowering should become clear through analysis of their transcriptional relationships with other photoperiodic pathway genes and ﬂowering integrator genes. It is worthwhile to point out that in spite of the close paralogous relationship between FLC and MAF1/FLM, these genes show clear differences in regulation and function. For example, FLC expression is regulated strongly by autonomous mechanisms genes or FRI (above), but is relatively insensitive to activity of genes that participate in photoperiodic ﬂowering (Sheldon et al., 1999), whereas the autonomous mechanisms or FRI do not seem to be signiﬁcant regulators of MAF1/FLM (Ratcliffe et al., 2001; Scortecci et al., 2001). Thus, these proteins have been recruited for very different ﬂowering roles. The four remaining members of the MAF clade have not been extensively characterized, although it is known that all have the capacity to act as ﬂoral repressors (Ratcliffe et al., 2003).

9.9

Transcriptional activation of AP1 by FT and FD

CO regulatory sequences mediate expression that is predominately localized to vascular (phloem) tissues of cotyledons and leaves (Takada and Goto, 2003). Because change in fate of primordia is effected at the apex, CO must provide a mobile signal to initiate this change. It now appears that FT is an important factor in this phenomenon. Grafting and targeted expression studies revealed that CO promotes ﬂowering by activating FT expression in phloem companion cells (An et al., 2004). Huang et al. (2005) used a heterologous, heat-inducible promoter to show that FT

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RNA produced transiently in the leaves was able to move into the shoot apex. Thus, FT may comprise this mobile ﬂowering signal. Two recent studies showed that the transcription factor FD plays a central role in the promotion of ﬂowering by FT in the shoot apex (Abe et al., 2005; Wigge et al., 2005). FD is a member of the bZIP family, which includes at least 75 members in Arabidopsis (Jakoby et al., 2002). Mutation in FD strongly suppressed early ﬂowering conferred by constitutive, high-level expression of FT (Abe et al., 2005; Wigge et al., 2005). This suggested that FT works with or through FD to promote ﬂowering. By contrast, the fd mutation only slightly affected precocious ﬂowering in transgenic plants constitutively expressing SOC1 or LFY (Abe et al., 2005), suggesting a special relationship between FT and FD. FD appears to be constitutively expressed in the apex, and FT and FD proteins were shown to interact in the nucleus to promote transcription of the meristem identity gene, APETALA1 (AP1) (Abe et al., 2005; Wigge et al., 2005). This activation appears to be independent of other regional factors, because ectopic expression of FD in regions of seedlings that express FT (vasculature of cotyledons) is sufﬁcient to drive expression of an AP1 reporter gene (Abe et al., 2005). A region of the AP1 promoter previously demonstrated to direct authentic expression (Hempel et al., 1997) contains several of the ACGT-core sequence motifs that bind plant bZIP factors (Foster et al., 1994; Wigge et al., 2005) and these may be directly targeted by FD. FD contains a potential phosphorylation site on its amino terminus that is required for binding to FT and for activity, although it remains to be determined if this residue is phosphorylated in vivo (Abe et al., 2005). As a bZIP factor, FD is expected to work as a dimer, and indeed FD is also able to interact in yeast cells both with itself and, intriguingly, with a paralogous bZIP protein (Abe et al., 2005). The mechanistic role that FT plays in activation of AP1 is a largely unresolved question. Although LFY also targets AP1, FT and FD probably act independently of LFY, because mutations in FT and LFY, or FD and LFY, have a synergistic effect on ﬂowering when combined. Other targets of FT that may require FD are the MADS-box gene FRUITFULL (FUL) and the AP1 paralog CAULIFLOWER (CAL) (Ferrandiz et al., 2000; Teper-Bamnolker and Samach, 2005). An interesting observation is that in the inducible system used by Huang et al. (2005), transgenic expression of FT in leaves was associated not only with the accumulation of the transgenic transcript in the apex, but also with the induction of endogenous FT both in the leaves and in the shoot apex, suggesting that FT participates in a positive autoregulatory feedback loop. This appeared to be robust, as endogenous FT RNA was produced for at least 3 days after activation in plants maintained in noninductive conditions (Huang et al., 2005). This mechanism may explain the ability of some plants, including Arabidopsis, to initiate and maintain ﬂowering in response to even a transient inductive signal. The mechanism of this positive autoregulation is an interesting and open question. FT may activate its own promoter directly, or this may occur through activation of downstream targets such as SOC1. SOC1 is the only one among the known targets of FT to be appreciably expressed in leaves where autoinduction can occur (Huang et al., 2005). In any

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case, given its lack of apparent DNA-binding motifs and dependence on FD in the apex, FT should collaborate with a leaf-expressed transcription factor to carry this out.

9.10

Transcriptional mechanisms in the promotion of ﬂowering by GAs

As in many plants, GAs play a major role in ﬂowering in Arabidopsis. Arabidopsis plants grown in noninductive short days eventually do undergo the ﬂowering transition, and under these conditions ﬂowering is absolutely dependent on GA signaling (Wilson et al., 1992). LFY is a central component in GA-promoted ﬂowering. In noninductive photoperiods, LFY promoter activity and RNA expression show a gradual increase over time in the primordia emerging from the shoot apex, and this is dependent on GAs (Bl´azquez et al., 1998). GA promotion of LFY transcription is dependent on a GAresponse cis-element (GARE) in the LFY promoter (Bl´azquez et al., 1998; Bl´azquez and Weigel, 2000). This DNA binds the Myb-like protein AtMYB33 in vitro (Gocal et al., 2001), suggesting that GAs regulate LFY through AtMYB33. AtMYB33 is one of a small subset of Arabidopsis Myb proteins, designated the GAMYBs, which are known to participate in GA signaling (Gocal et al., 2001). Interestingly, AtMYB33 accumulates in the shoot apex of plants transferred from short to long days, an effect potentially driven by increased GA concentration (Gocal et al., 2001). This suggests that GAs should also contribute to promoting ﬂowering under long days, and is consistent with observations that a GA biosynthetic mutant ﬂowers slightly later than wild-type plants under long days (Wilson et al., 1992). Similar to the AP2-like ﬂowering repressors (above), AtMYB33 is posttranscriptionally downregulated by a microRNA, in this case miR159 (Achard et al., 2004). miR159 accumulates in response to GA, and so this mechanism might moderate the GA-promotive effects of AtMYB33. Both miR159 and its target sequences within GAMYB-like RNAs are evolutionarily conserved, suggesting that microRNA-mediated downregulation of these GAMYBs is of fundamental importance (Achard et al., 2004). GA signaling is believed to involve the downregulation, through ubiquitin/26S proteasome-dependent proteolysis, of members of the DELLA family of nuclear repressors and subsequent derepression of GA-promoted genes (review in Sun and Gubler, 2004). There are ﬁve DELLA proteins encoded by the Arabidopsis genome, and these proteins have partially overlapping roles in various GA-dependent processes. Combined loss of function of two of these, GAI and RGA, rescued the late-ﬂowering defect of a strong ga1 mutation (Dill and Sun, 2001), suggesting that these proteins mediate most of the ﬂowering-promotive effect of GAs in Arabidopsis. The SOC1 gene also has been shown to participate in GA-mediated activation of LFY and ﬂowering in short days (Borner et al., 2000; Moon et al., 2003a), and SOC1 RNA expression is upregulated in response to GAs (Moon et al., 2003a). Because

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GAs do not seem to strongly regulate expression of known upstream regulators of SOC1, including FT or FLC (Moon et al., 2003a), this activation may be fairly direct. However, GARE-like cis-elements in the SOC1 promoter that might mediate induction by GAs have not been reported. GA-mediated promotion of SOC1 expression is considered to be independent of miR159/MYB33, because late ﬂowering associated with overexpression of miR159 (and consequently, decreased MYB33 RNA) was not associated with decreased SOC1 transcript levels (Achard et al., 2004). The identiﬁcation of GA-signaling components upstream of SOC1 therefore is an interesting and unresolved matter. Although LFY is obviously a central component in the GA-ﬂowering pathway, GAs also promote ﬂowering by regulating genes that are downstream, or act independently, from LFY, as shown by the ability of a ga1 mutation to partially suppress the early ﬂowering conferred by ectopic expression of LFY (Bl´azquez et al., 1998). This may be due at least in part to an LFY-independent activity of GA in promoting expression of ﬂoral homeotic genes such as PI, AP3, and AG (Yu et al., 2004).

9.11

PcG-mediated repression of ﬂoral homeotic genes

In addition to the maintenance of FLC silencing in vernalized plants (above), PcGlike mechanisms in Arabidopsis inhibit ﬂowering by repressing ﬂoral homeotic genes outside of their appropriate expression domains. This activity is probably best illustrated by the EMF1 and EMF2 genes, which have similar function and encode a putative transcriptional regulator and Su(z)12 homolog, respectively (Aubert et al., 2001; Yoshida et al., 2001). In strong emf1 or emf2 mutants, the vegetative phase is largely bypassed and ﬂowers form embryonically or during seedling development (Sung et al., 1992; Yang et al., 1995). Consistent with this phenotype, loss of at least EMF1 has been shown to result in derepression of genes acting in ﬂoral development, including AG, AP1, AP3, and PI, in vegetative tissues (Chen et al., 1997; Moon et al., 2003b). Early ﬂowering associated with misexpression of ﬂoral homeotic genes was also observed in plants lacking activity of both CLF and SWN (Goodrich et al., 1997; Chanvivattana et al., 2004), and in mutants and transgenic plants cosuppressed for the ESC homolog FERTILIZATION-INDEPENDENT ENDOSPERM (FIE) (Kinoshita et al., 2001; Katz et al., 2004). Interestingly, at least in the emf1 mutant, ectopic expression of homeotic genes was not accompanied by substantial derepression of associated upstream regulators such as CO, FT, SOC1, or LFY (Moon et al., 2003b). This, along with the observation that loss of CO, SOC1, or LFY cannot rescue the emf1 phenotype (Moon et al., 2003b), suggests that EMF1 represses ﬂoral homeotic genes independently of ﬂowering-time or ﬂowering integrator genes. Thus, the early ﬂowering observed in this class of mutants probably results from a bypass of normal ﬂowering-timing mechanisms and the direct action of meristem identity and ﬂoral organ identity genes on the shoot apex. In wild-type plants, ﬂowering may involve antagonism of PcG repression by ﬂowering-time and ﬂowering integrator genes, and the mechanism involved is an interesting question.

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Summary and prospects

The substantial amount of accumulated information related to transcriptional pathways involved in ﬂowering in Arabidopsis has originated almost exclusively in phenotypic screens and genetic analyses. Thus, our knowledge of transcriptional regulation of ﬂowering timing is ‘gene rich’ but ‘mechanism poor’. Although the identiﬁcation of new ﬂowering genes will continue to have a strong impact, the most signiﬁcant advances will likely be based on emerging molecular and biochemical techniques. For example, the availability of genomic tiling microarrays covering essentially the entire Arabidopsis genome should allow rapid identiﬁcation of sites bound by transcription- and chromatin-related factors and elucidation of the transcriptional networks in which they participate. The development of efﬁcient, plantcompatible systems for puriﬁcation of protein complexes based on afﬁnity tags, an approach that has been very proﬁtable in studies of transcriptional mechanisms in yeast and animals, should further accelerate the pace of discovery. Substantial effort is now being directed into the use of Arabidopsis as a blueprint for understanding ﬂowering mechanisms in economically important crops such as rice, wheat, and maize. In general, such studies have revealed that many genes inﬂuencing ﬂowering in Arabidopsis have been conserved through evolution, but that these genes sometimes are used in ﬂowering in apparently novel ways (Hayama and Coupland, 2004; Marx, 2004). Thus, although continued studies in Arabidopsis obviously have merit, the ability to eventually control ﬂowering in a sophisticated manner and in a range of species will necessitate the development of alternative ﬂowering models. Novel ﬁndings are especially likely to await in the characterization of ﬂowering mechanisms in perennial and woody plants.

Acknowledgments The authors acknowledge the contributions of many investigators that were not cited due to space limitations. This work was supported by funding from the U.S. Department of Agriculture (National Research Initiative Competitive Grant Program, No. 2003-35304-13299) and the U.S. National Science Foundation (MCB-0445867) to S.V.N.

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10 Combinatorial control of ﬂoral organ identity by MADS-domain transcription factors G¨unter Theißen and Rainer Melzer

10.1

Introduction

The involvement of multiprotein complexes that bind DNA in a sequence-speciﬁc manner and either repress or activate transcription is a recurring theme in studies of eukaryotic gene regulation (Wolberger, 1998). Concerning plants, MIKC-type MADS-domain proteins involved in ﬂower development are a good case in point. The transcription factor complexes that specify ﬂoral organ identity have been comparatively well characterized during recent years. In this chapter, we focus on the major model system, thale cress Arabidopsis thaliana (henceforth termed Arabidopsis), with side views on other plants only when necessary for a general understanding.

10.2

ABC: early genetic models of ﬂoral organ identity

The distinct identities of the different ﬂoral organs confer ﬂowers their unique appearance. A typical ﬂower of a eudicot, which is the largest group of ﬂowering plants (angiosperms), consists of four different organ classes arranged in four whorls at the tip of a ﬂoral shoot. The ﬁrst, outermost whorl often consists of green, leaflike sepals. The second whorl is composed of usually colored and showy petals. The third whorl contains the stamens, i.e., the male reproductive organs, which produce the pollen. Finally, the fourth, innermost whorl contains the carpels, i.e., the female reproductive organs, which are often fused and inside which the ovules and seeds develop. Although the appearance of sepals, petals, stamens, and carpels may differ dramatically at maturity, each ﬂoral organ starts its development as a little bulge on a tiny clump of undifferentiated cells called ‘ﬂoral meristem’. Thus, each cell in the developing ﬂoral organ primordia must somehow ‘learn’ its position within the ﬂower, and differentiate accordingly into a cell type that is appropriate for the speciﬁc organ. Almost two decades ago the ﬁrst genetic model was suggested to explain how homeotic selector genes specify organ identity during ﬂower development (Haughn and Somerville, 1988). This ‘early ABC model’ was based on the study of homeotic mutants in which the identity of ﬂoral organs is changed. In Arabidopsis such mutants come in three classes: A, B, and C (Figure 10.1). Ideal class A mutants have carpels in the ﬁrst whorl instead of sepals, and stamens in the second whorl instead of petals.

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Figure 10.1 Floral homeotic mutants and the ABCDE model of ﬂoral organ identity of Arabidopsis. The photographs show ﬂower phenotypes of loss-of-function mutants of ﬂoral homeotic genes. ap1-1 is a class A mutant affected in the APETALA1 (AP1) gene that has sepals transformed into carpelloid organs and petals transformed into stamenoid organs. ap3-3 and pi-1 are class B mutants affected in the APETALA3 (AP3) and PISTILLATA (PI) genes, respectively, which have petals transformed into sepaloid organs and stamens transformed into carpelloid organs. ag-1 is a class C mutant that has stamens transformed into petaloid organs; carpels are replaced by another mutant ﬂower due to the loss of determinate growth of the ﬂoral shoot, and so the number of ﬂoral organs is vastly increased in these ‘ﬁlled ﬂowers’. stk shp1 shp2 is a class D triple mutant in the genes SEEDSTICK (STK), SHATTERPROOF1 (SHP1), and SHATTERPROOF2 (SHP2), in which ovules are transformed into carpelloid or vegetative leaf-like organs. sep1 sep2 sep3 sep4 is a class E quadruple mutant affected in the genes SEPALLATA1 (SEP1), SEPALLATA2 (SEP2), SEPALLATA3 (SEP3), and SEPALLATA4 (SEP4), in which all ﬂoral organs develop like vegetative leaves and the number of ﬂoral organs is vastly increased due to a loss of determinate growth of the ﬂoral shoot. The graphic shows the ABCDE model of ﬂower organ identity, which is based on the mutant phenotypes shown in the photographs. Corresponding to the ﬁve classes of mutants ﬁve classes of homeotic genes are postulated, with class A + E genes specifying sepals in whorl 1 of the ﬂower; the combined activities of A + B + E specify petals in whorl 2; B + C + E specify stamens in whorl 3; C + E specify carpels in whorl 4; D + E specify ovules that develop within carpels. The activities A and C are mutually antagonistic: A prevents the activity of C in whorls 1 and 2, and C prevents the activity of A in whorls 3 and 4. (Photographs of ap1-1, ap3-3, pi-1, and ag-1 are reproduced from Riechmann and Meyerowitz (1997) with kind permission by Walter de Gruyter and the authors, stk shp1 shp2 (modiﬁed) is from Pinyopich et al. (2003) with kind permission from Macmillan Publishers Ltd, and sep1 sep2 sep3 sep4 is from Ditta et al. (2004) with kind permission from Elsevier.)

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Class B mutants have sepals rather than petals in the second whorl, and carpels rather than stamens in the third whorl. Class C mutants have petals instead of stamens in the third whorl, and sepals rather than carpels in the fourth whorl. In addition, the ﬂowers of these mutants grow indeterminately, i.e., there is continued production of mutant ﬂoral organs inside the fourth whorl. The phenotype of class A, B, and C mutants suggested that development of the ﬂower is sculpted by homeotic selector genes, aptly termed ‘ﬂoral organ identity genes’, whose expression gives the different ﬂoral organs their unique identity. Homeotic selector genes can be considered as acting as major developmental switches that activate the entire genetic program required for the development of a particular organ, and repress genes whose activity would be unnecessary or even detrimental for organ development. The early ABC model proposed that the state of expression (‘on’ or ‘off’) of three different genes a, b, and c speciﬁes the identity of the four different ﬂoral organs. (Haughn and Somerville, 1988). The proposed states of expression of genes a, b, c in the different ﬂoral organs are ‘on, off, off’ (sepals), ‘on, on, off’ (petals), ‘off, on, on’ (stamens), and ‘off, off, on’ (carpels). If a, b, and c gene expression is off, leaves develop. (Haughn and Somerville, 1988). Not much later, a more elaborate and now widely known model, termed ‘classical ABC model’ here and elsewhere (Theißen, 2001), was proposed to explain how homeotic genes control ﬂoral organ identity (Figure 10.1) (Coen and Meyerowitz, 1991). Similar to the early ABC model, the classical ABC model maintains that organ identity in each whorl is determined by a unique combination of three organ identity gene activities, called A, B, and C. Expression of A alone speciﬁes sepal formation. The combination AB speciﬁes the development of petals, and the combination BC speciﬁes the formation of stamens. Expression of C alone determines the development of carpels. In contrast to the early ABC model, however, there can be more than one gene behind the different gene activities (‘ﬂoral homeotic functions’) A, B, and C. Moreover, in order to explain the three classes of ﬂoral homeotic mutants, the classical ABC model proposes that the A- and C-function genes negatively regulate each other; that is, the C-function becomes expressed throughout the ﬂower when the A-function is mutated, and vice versa (for reviews of the ABC model, see Weigel and Meyerowitz, 1994; Theißen, 2001). Arabidopsis genes providing the three homeotic activities A, B, and C are known. The A-function is contributed by two different genes, APETALA1 (AP1) and APETALA2 (AP2), the B-function also by two genes, APETALA3 (AP3) and PISTILLATA (PI), and the C-function by just one gene, AGAMOUS (AG). Molecular cloning of these genes revealed that they all encode putative transcription factors (Yanofsky et al., 1990; Jack et al., 1992; Mandel et al., 1992; Goto and Meyerowitz, 1994; Jofuku et al., 1994; for a review, see Weigel and Meyerowitz, 1994; Theißen, 2001). Thus, the products of the ABC genes probably all control the transcription of other genes (‘target genes’) whose products are directly or indirectly involved in the formation or function of ﬂoral organs. Except for AP2, all ABC genes belong to a special class of genes that is restricted to green plants, termed ‘MIKC-type MADS-box genes’ (M¨unster et al., 1997; Kaufmann et al., 2005b). These are named so because they encode MADS-domain transcription factors with a characteristic

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structural organization, including, from N- to C-terminus, a MADS (M-), intervening (I-), keratin-like (K-), and C-terminal (C-) domain (Theißen et al., 1996; Kaufmann et al., 2005b). The name-giving MADS domain is by far the most highly conserved region of all kinds of MADS-domain proteins. The MADS domain is the major determinant of DNA binding, but it also performs functions in dimerization of MADS-domain proteins and in accessory factor binding. MADS-domain proteins bind to DNA sites based on the consensus sequence 5 -CC(A/T)6 GG-3 , termed a ‘CArG box’ (for ‘CC-A rich-GG’). The I-domain, located directly downstream of the MADS domain, is quite variable in length and only relatively weakly conserved. It may constitute a key molecular determinant for the selective formation of DNA-binding dimers, at least in some MIKC-type proteins. The K-domain is characterized by a conserved, regular spacing of hydrophobic residues, which is proposed to allow for the formation of an amphipathic helix. It is assumed that such an amphipathic helix interacts with that of another K-domain containing protein to promote protein dimerization or multimeric complex formation. The most variable region is the C-domain at the C-terminal end of the MADS-domain proteins. In some MADSdomain proteins it is involved in transcriptional activation, or in the formation of multimeric complexes (structural and phylogenetic aspects of MIKC-type proteins have been reviewed in detail by Kaufmann et al., 2005b).

10.3

From the ABC to the ABCDE model

Despite its explanatory power, e.g., in correctly predicting the phenotype of most double and triple mutants of ﬂoral homeotic genes, the ABC model has two important shortcomings: mutant and transgenic studies indicated that the ABC genes are required, but not sufﬁcient, for the speciﬁcation of ﬂoral organ identity. Moreover, the ABC model could not explain as to how the ﬂoral homeotic genes interact at the molecular level to specify ﬂoral organ identity. The ﬁrst shortcoming could be overcome by the identiﬁcation of additional ﬂoral homeotic functions and led to an extension of the ABC into an ABCDE model. Elimination of the second shortcoming required a switch from considerations at gene level to the level of the encoded proteins, and led to the ‘ﬂoral quartet model’. The ﬂoral homeotic functions A, B, and C could be identiﬁed by conventional ‘forward’ genetics, because some single mutants revealed complete loss-of-function phenotypes (Figure 10.1). However, additional homeotic functions had escaped forward genetics approaches due to the functional redundancy of the underlying, closely related genes. Their identiﬁcation hence required the generation of multiple mutants via ‘reverse genetics’ generating single mutants followed by crossing. Based on studies in petunia (Petunia hybrida), the ABC model was ﬁrst extended to an ‘ABCD model’ by addition of a D-function specifying ovule identity (Angenent and Colombo, 1996). In Arabidopsis, the class D genes are represented by AGAMOUS (which was introduced as a class C gene already), and three additional genes closely related to AG, namely SEEDSTICK (STK; formerly known as AGL11),

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SHATTERPROOF1 (SHP1; formerly known as AGL1), and SHATTERPROOF2 (SHP2; formerly known as AGL5) (Favaro et al., 2003; Pinyopich et al., 2003). stk shp1 shp2 triple mutants, for example, are characterized by conversion of ovules into carpel-like or leaf-like structures (Figure 10.1) (Pinyopich et al., 2003). Knocking out another class of MIKC-type MADS-box genes, termed SEPALLATA-like genes (also known as AGL2-like genes), revealed yet another class of ﬂoral homeotic function (Pelaz et al., 2000; Ditta et al., 2004). As class E it has been added to the ABCD model, yielding the ‘ABCDE model’ (Figure 10.1) (Theißen, 2001; for reviews on the diversity of ABCDE functions in different plants, see Ferrario et al., 2004; Krizek and Fletcher, 2005). While single and double mutants of SEPALLATA1 (SEP1, formerly known as AGL2), SEPALLATA2 (SEP2; formerly known as AGL4), SEPALLATA3 (SEP3; formerly known as AGL9), or SEPALLATA4 (SEP4; formerly known as AGL3) have only very weak mutant phenotypes, if any, in sep1 sep2 sep3 triple mutants the organs in all whorls of the ﬂower develop into sepals, and ﬂower development becomes indeterminate (Pelaz et al., 2000); in sep1 sep2 sep3 sep4 quadruple mutants vegetative leaves rather than sepals develop in all whorls of indeterminate ﬂowers (Figure 10.1) (Ditta et al., 2004). The sep1 sep2 sep3 triple mutant phenotype is strikingly similar to that of a class B and C double mutant, i.e., ap3 ag or pi ag, indicating that the ﬂoral homeotic B- and C-functions do not work in the sep triple mutant. Also, the sep1 sep2 sep3 sep4 quadruple mutant phenotype is very similar to a class A, B, C triple mutant, indicating that the ﬂoral homeotic A-, B-, and C-functions do not work in the sep quadruple mutant. However, the SEP genes are still expressed in B and C lossof-function mutants (see, e.g., Flanagan and Ma, 1994), and the initial expression patterns of B and C class genes are not altered in the sep1 sep2 sep3 triple mutant (Pelaz et al., 2000). This suggested that the SEP genes, rather than acting upstream or downstream of the ﬂoral homeotic genes, constitute a novel class of redundant ﬂoral organ identity genes. Obviously, different combinations or dosages of SEP, i.e., class E genes, in addition to the ABC genes, are required for the speciﬁcation of all types of ﬂoral organs. The ABCDE model maintains that class A + E genes are required to specify sepals, A + B + E petals, B + C + E stamens, C + E carpels, and D + E ovules (Figure 10.1) (Theißen, 2001; Ditta et al., 2004). Like the ABC model, the ABCDE model mainly relies on genetic data. This raises the question that by which molecular mechanism do the different ﬂoral homeotic genes interact, such that, e.g., A + B + E gives petals and B + C + E stamens (Figure 10.1)?

10.4

Elective afﬁnities of homeotic proteins: the ﬂoral quartet model

MADS-domain proteins bind to DNA in a sequence-speciﬁc way only as dimers. It was thus tempting to explain the interaction of ﬂoral homeotic genes by dimerization of their gene products. This soon failed, however, because the formation of DNAbinding dimers, as revealed by electrophoretic mobility shift assays and the yeast two-hybrid system, shows a high degree of partner speciﬁcity (Riechmann et al., 1996; Fan et al., 1997). For example, the class B proteins AP3 and PI can bind to

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DNA only as obligatory AP3–PI heterodimers, but DNA-binding dimers with other MIKC-type proteins have not been observed (Riechmann et al., 1996). So how, for example, do class B genes (AP3 and PI) interact with the C gene (AG) to control stamen identity, if B + C (AP3–AG or PI–AG) DNA-binding dimers cannot be formed? An obvious solution would be that B and C proteins (AP3–PI and AG–AG dimers) bind separately to different cis-regulatory elements in the promoters of the same target genes that are activated or repressed during stamen formation. Alternatively, class B and class C proteins could have distinct sets of target genes involved in stamen formation, so that the combinatorial interaction of the homeotic genes would be mechanistically realized only at the level of target genes, or even more downstream in the gene cascades involved. A new perspective was provided when Egea-Cortines et al. (1999) reported that DEFICIENS (DEF), GLOBOSA (GLO), and SQUAMOSA (SQUA) from snapdragon (Antirrhinum majus) form multimeric complexes in electrophoretic mobility shift assays and yeast three-hybrid analyses. Evidence was provided that the multimeric complex has a higher DNA-binding afﬁnity than the individual dimers. The authors suggested a model according to which the protein complex is actually a protein tetramer, composed of a DEF–GLO heterodimer and a SQUA–SQUA homodimer, in which the DEF–GLO and SQUA–SQUA dimers recognize different CArG boxes (Egea-Cortines et al., 1999). Based on double mutant analysis originally thought just to be required for the establishment of the whorled phyllotaxis of ﬂoral organ arrangement in Antirrhinum (Egea-Cortines et al., 1999), the formation of higher order complexes was soon realized to be a more general principle of ﬂoral homeotic proteins. DEF, GLO, and SQUA are putative orthologs of AP3, PI, and AP1, respectively (Becker and Theißen, 2003), suggesting that multimeric complexes might also be formed by the respective Arabidopsis proteins. It was known before that class C proteins such as PLE from Antirrhinum and AG form DNA-binding dimers with AGL2-like (SEP) proteins (Davies et al., 1996; Huang et al., 1996), suggesting that the ﬂoral homeotic C-function in Arabidopsis may require interaction between AG and SEP proteins. So when Pelaz et al. (2000) reported that not only the ABC, but also the SEP genes are required for the formation of petals, stamens, and carpels, all these ﬁndings were combined in the ﬂoral quartet model (Theißen, 2001). It suggests that tetrameric complexes of ﬂoral homeotic proteins including SEP proteins rather than individual dimers control ﬂoral organ identity. According to the original ‘quartet model’, there is at least one unique quaternary complex for each type of ﬂoral organ (Theißen, 2001) (Figure 10.2). These quaternary protein complexes might exert their function as transcription factors by binding to CArG boxes in the promoters of target genes, which they either activate or repress as appropriate for the development of the identities of the different ﬂoral organs (Theißen, 2001). In these complexes, the AP1 or SEP proteins may provide the transcription activation domain, while the other proteins might be more important for organ speciﬁcity of gene regulation. It has been proposed that two protein dimers of each tetramer recognize two different DNA CArG boxes, which might be brought into close vicinity by bending the DNA between the CArG boxes (Egea-Cortines et al., 1999; Theißen, 2001; Theißen and

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Figure 10.2 An extended and updated version of the ﬂoral quartet model of Arabidopsis. The model suggests that different combinations of MIKC-type MADS-domain proteins determine the identity of the different ﬂoral organs, or of substructures (the endothelium is the inner tissue layer in the inner integument of ovules, and ovules are parts of carpels). The combinatorial protein complexes represent transcription factors that exert their function by speciﬁcally binding to the promoters of target genes, which they either activate or repress as appropriate for the development of the identities of the different ﬂoral organs or substructures. Binding is assumed to occur to pairs of DNA sequence elements termed CArG boxes, which are brought in close vicinity by DNA bending. The molecular mechanism by which the basal transcriptional apparatus is affected by ﬂoral quartets is unknown. (Abbreviations of protein names: ABS, Arabidopsis Bsister ; for all other names, see corresponding gene names in Figure 10.1.)

Saedler, 2001), so the quartet (or tetramer) is actually a dimer of dimers (which might give a clue as to how it originated during evolution). Shortly after development of the ﬂoral quartet model, Honma and Goto (2001) indeed demonstrated by yeast three-hybrid and four-hybrid analyses the formation of the complexes postulated for stamens and petals, namely AP3/PI/AG/SEP and AP3/PI/AP1 (or SEP), respectively. Even more intriguingly, it was shown that ectopic coexpression of class A/E + B genes AP1 + AP3 + PI or SEP3 + AP3 + PI in transgenic Arabidopsis plants leads, simply put, to a developmental conversion of vegetative leaves into petaloid organs (Honma and Goto, 2001; Pelaz et al., 2001); more accurately phrased, ectopic expression of the mentioned genes leads to a reprogramming of supposed-to-be leaf primordia in a way that they develop into petaloid organs. AP1 and SEP3 can substitute each other, which probably reﬂects their close evolutionary relationship (Becker and Theißen, 2003) and hence partial redundancy. Again simply put, the coexpression of the class B + C + E genes AP3 + PI + AG + SEP3 converts vegetative leaves into stamenoid organs (Honma and Goto,

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2001). These data not only add genetic support for the ﬂoral quartet model but also demonstrate that less than a handful of proteins are not only necessary, but also sufﬁcient to superimpose petal and stamen identity upon a vegetative developmental program.

10.5

Beyond the ﬂoral quartets sensu stricto: multimeric complexes of other MIKC-type proteins

The ﬂoral quartet model describes the interaction of the ﬂoral homeotic proteins at the molecular level. However, the ﬂoral homeotic proteins are only a minor fraction of the large family of MIKC-type MADS-domain proteins, comprising 39 members in Arabidopsis alone (Becker and Theißen, 2003). Therefore, the question arises as to whether multimerization is restricted to the ﬂoral homeotic proteins of eudicots (an extreme hypothesis) or is a common feature of all MIKC-type proteins in all kinds of land plants and charophyte green algae (another extreme hypothesis) (Kaufmann et al., 2005b). There is indeed evidence that higher order complexes are also important for ovule development (Figure 10.2). The class D proteins from Arabidopsis formed multimeric complexes together with the SEP3 protein when tested in yeast threehybrid assays (Favaro et al., 2003). In addition, partial loss of SEP-gene activity leads to similar defects in ovule development as observed in stk shp1 shp2 triple mutants (Favaro et al., 2003). Moreover, another subfamily of MIKC-type MADS-domain proteins has been shown to be important for some aspects of ovule development as well. Members of this Bsister -subfamily, the putative sister clade of the class B genes, show femalespeciﬁc expression in all species examined so far (Becker et al., 2002). In accordance with this, loss-of-function mutants of the Arabidopsis Bsister gene (ABS) show defects in the development of the innermost layer of the integument of the ovule, the endothelium (Nesi et al., 2002; Kaufmann et al., 2005a). Fitting well to these genetic data, the class D proteins SHP1, SHP2, and STK all form a multimeric complex together with ABS mediated by SEP3, suggesting that endothelium development is controlled by a multimeric complex composed of the respective proteins (Figure 10.2) (Kaufmann et al., 2005a). This demonstrates that higher complex formation is not restricted to ﬂoral homeotic proteins, but applies also to MIKC-type MADS-domain proteins that work ‘downstream’ of the homeotic proteins in the gene hierarchy that controls ﬂower development (Kaufmann et al., 2005a). Although these data help us already to get a deeper understanding of the molecular mechanisms underlying ﬂower development, we are just beginning to elucidate the complex network of multimerization among MIKC-type proteins. It has been suggested recently that different MADS-domain protein complexes are formed in a temporal order of availability, adding another level of complexity to the regionspeciﬁc complex formation (Castillejo et al., 2005). If this holds true, it has important evolutionary implications, as it suggests a mechanism by which the present-day regulatory cascade could have originated. For example, AG and SEP are hypothesized

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to act together to specify carpel identity. Moreover, the expression of the respective genes is maintained through autoregulatory feedback loops (G´omez-Mena et al., 2005). One target gene of the complex is thought to be SHP2 (Savidge et al., 1995; Castillejo et al., 2005). On the other hand, SHP2 and SEP are supposed to act together to confer ovule identity (Favaro et al., 2003). As AG and the SHP genes originated by gene duplication, one could imagine that this ancient duplication followed by the loss of the autoregulatory capability of SHP2 created the present-day cascade. Even less explored is the interaction behavior of MADS-domain proteins expressed in reproductive parts of the plant. However, it is quite reasonable to assume that what is true for organ identity proteins is also true for other angiosperm MIKCtype MADS-domain proteins.

10.6

Outlook: the devil is always in the details – what we still don’t know about ﬂoral quartets

Like the ABCDE model, the ﬂoral quartet model speciﬁes not only which genetic components are required, but also which are sufﬁcient to specify ﬂoral organ identity. In contrast to the ABCDE model, however, the ﬂoral quartet model also demonstrates how the combinatorial interaction of these components works mechanistically. Therefore, it soon became the standard model for work on ﬂoral homeotic genes far beyond Arabidopsis (see, e.g., Jack, 2001; Winter et al., 2002; Ferrario et al., 2003; Lee et al., 2003; Ferrario et al., 2004; Shchennikova et al., 2004). Not few consider the ﬂoral quartet model now as (largely) accepted by the scientiﬁc community (see, e.g., Krizek and Fletcher, 2005; Robles and Pelaz, 2005). Our parental pride notwithstanding, however, we want to draw attention to the fact that the empirical basis of the ﬂoral quartet model is still quite weak; few successful direct experimental tests beyond studying protein–protein interactions in vitro and in yeast, employing electrophoretic mobility shift assays and yeast three-hybrid analyses, have been carried out. Whether multimeric complexes of ﬂoral homeotic proteins really regulate gene expression in the nuclei of plant cells, we just do not know. To become experimentally tractable, the problem should be subdivided into two major questions: 1. Do ﬂoral quartets or similar complexes really exist in planta? One of the most intriguing questions is as to which extent the interactions observed in yeast n-hybrid and gel retardation studies also exist in the living plant cell. Using fusions of MADS-domain proteins and yellow ﬂuorescent protein (YFP) or cyan ﬂuorescent protein (CFP), Immink et al. (2002) were able to demonstrate dimerization of MADS-domain transcription factors in plant protoplasts. The method being used is based on the ﬂuorescence resonance energy transfer (FRET) occurring when YFP and CFP are in close vicinity to each other. Recently, this experimental strategy was extended to provide circumstantial evidence for higher order complex formation (Nougalli-Tonaco et al., 2006). In the novel assay, a third, unlabeled interaction partner was coexpressed with two others that dimerize only weakly. As the unlabeled

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protein interacts more strongly with both of the labeled proteins, a titration effect, i.e., very weak or no interaction, should be observed between the labeled proteins if only dimerization occurs. However, Nougalli-Tonaco et al. (2006) observed a strong FRET signal when these three proteins were coexpressed; the most plausible explanation for this observation is the formation of a higher order complex as predicted by the ﬂoral quartet model. These studies provide an excellent starting point for analyzing interactions of MADS-domain proteins in the plant. Expressing the ﬂoral homeotic proteins fused to CFP and YFP under the control of their natural promoter will reveal which complexes are formed in a ﬂoral context. It should also be mentioned that another noninvasive technique, bimolecular ﬂuorescence complementation (BiFC), has been used to test protein interactions in plant cells (Bracha-Drori et al., 2004). This system is based on the observation that a split YFP, fused to two different proteins, regains its ﬂuorescence activity if the proteins tested interact with each other. However, it remains to be determined whether BiFC is useful for studying the interaction of MADS-domain proteins. Another question that could be answered making use of GFP and its derivates is whether the ‘ﬂoral quartet’ is indeed a quartet (i.e., a tetramer). Using virus particles containing a known number of GFP molecules as an internal standard, the number of proteins in cellular structures has been determined (Dundr et al., 2002). If this method is also applicable to MADS-domain proteins, the stochiometric compostion of the complexes might be accessible. 2. What is the exact composition of multimeric complexes? Although the quartet model explains the available data in the most plausible way, it cannot explain all the phenomena observed. Questions that remain open are, for example, how target gene speciﬁcity is achieved or how only one multimer can specify a complex ﬂoral organ with its many different cell types. One possible answer, although not the only one, is that the ﬂoral quartets act together with other factors to regulate region-speciﬁc gene expression and target gene speciﬁcity. Several screens using the yeast two-hybrid system have been carried out, employing either one or several MIKC-type MADSdomain proteins as a bait (for examples see Davies et al., 1996; Honma and Goto, 2001). However, few convincing non-MADS interaction partners have been identiﬁed so far. This might reﬂect the fact that there are no such interaction partners, or, alternatively, that other methods need to be employed to isolate them. In the past years, tandem afﬁnity puriﬁcation (tap) (Rigaut et al., 1999) turned out to be a powerful technique to isolate protein complexes directly from their ‘natural cellular environment’. Using this method, tagged proteins can be stably expressed in the organism of interest. The tag design allows two different puriﬁcation steps, yielding complexes of high purity. The big advantage of this method is its unbiased approach that aims to isolate the ‘real’ interaction partners of a protein of interest. Tandem afﬁnity puriﬁcation has been successfully used to isolate protein complexes from yeast and mammalian cells (reviewed in Gingras et al., 2005). Special tap tags for isolation of plant protein complexes have been published (Rohila et al., 2004; Rubio et al., 2005), and the near future will hopefully show whether this technique is also useful to tackle the in vivo complex formation of MADS-domain transcription factors. A number of other questions also remain: Which target genes do ﬂoral quartets control, and how is target gene speciﬁcity achieved? Little is known to answer the

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ﬁrst question, and almost nothing to answer the second one (see, e.g., Sablowski and Meyerowitz, 1998; G´omez-Mena et al., 2005; Melzer et al., in press). How do the MIKC-type protein complexes bind to DNA, and how is transcription affected, e.g., how do they interact with RNA polymerase II and general transcription factors? How conserved are multimeric complexes of MIKC-type proteins in evolution, and to what extent did gene duplications within the MADS-box gene family contribute to the origin of these complexes? What are the implications of complex formation for the coevolution of MADS-box genes? Only time – ﬁlled with hard work – will tell.

10.7

Summary

To explain how the different ﬂoral organs adopt their unique identities during ﬂower development, combinatorial interactions between ﬁve classes of ﬂoral homeotic genes, termed A, B, C, D, and E, have been proposed, with A + E specifying sepals, A + B + E petals, B + C + E stamens, C + E carpels, and D + E ovules. The capacity of MIKC-type MADS-domain proteins to form multimeric complexes provides a molecular basis for the combinatorial interactions of the class A, B, C, D, and E genes, which (almost) all encode MIKC-type proteins. According to the ﬂoral quartet model, the identity of the different types of ﬂoral organs is speciﬁed by tetrameric complexes of MIKC-type proteins (ﬂoral quartets). These protein complexes are hypothesized to bind to two cis-regulatory DNA sequence elements in the promoter regions of their target genes, which are brought into close vicinity by DNA bending. The ﬂoral quartets represent transcription factors that regulate all those target genes whose differential gene expression is required and sufﬁcient for the speciﬁcation of the identity of the different ﬂoral organs (sepals, petals, stamens, and carpels), or substructures (ovules, endothelium of the inner integument of ovules). An important goal of future research will be to deﬁne the exact structures of all the transcription factor complexes that work as major developmental switches during the plant life cycle.

Acknowledgments The authors thank Klaus D. Grasser for his kind invitation to contribute to this book. A fellowship to R.M. by the Studienstiftung des deutschen Volkes is greatly acknowledged.

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11 Networks of transcriptional regulation underlying plant defense responses toward phytopathogens Imre E. Somssich

11.1

Introduction

Plants are constantly exposed to thousands of potentially harmful air-, water- and soil-borne pathogens within their environment. From an evolutionary standpoint, the survival of individual plant species can only be reasonably ensured provided they have the capacity to develop surveillance mechanisms and signaling networks allowing them to perceive and respond appropriately to such dangers. Conversely, pathogen survival is equally dependent on the ability of microbial pests to avoid, overcome, or partly subdue such plant defenses, thereby allowing them to gain access to their hosts and successfully complete their life cycles. This coevolutionary ‘tug-of-war’ is certainly a key driving force resulting, on the one hand, in continuous diversiﬁcation and reﬁnement of host defense systems, and on the other hand, in alterations of the countermeasures employed by pathogens to undermine detection or overcome newly devised defense barriers. Molecular and genetic studies, in particular with the model system Arabidopsis thaliana, have revealed that higher plants have evolved highly sophisticated surveillance mechanisms and signaling networks to initiate effective defense responses (Belkhadir et al., 2004; Jones and Takemoto, 2004). Considering the large diversity of potential pathogens, their distinct modes of infection, and their varying lifestyles, it is obvious that plants must have gained the ability to recognize and restrict invasions occurring in diverse organs, tissue, cell types, and in intra- and intercellular compartments. From our current understanding, plants appear to possess several layers of defenses to cope with these problems (Thordal-Christensen, 2003; Mysore and Ryu, 2004). The most common form of plant resistance toward phytopathogenic organisms is termed nonhost or species-level resistance (N¨urnberger and Brunner, 2002). Apart from preformed physical and chemical barriers, this kind of basic resistance involves the ability of the plant to recognize various surface or secreted molecules of diverse pathogens (also designated PAMPs for Pathogen-Associated Molecular Patterns), and also molecules of the plant itself that are released during microbial infection. This recognition process subsequently triggers an efﬁcient and multicomponent defense response. Nonhost resistance has several remarkable similarities to the mammalian innate immunity response and hence is generally referred to as plant innate immunity (Jones and Takemoto, 2004; Zipfel and Felix,

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2005). A second very effective form of resistance is termed R-gene mediated or gene-for-gene-type resistance. In this case, speciﬁc defense responses are triggered only if there is an allele-speciﬁc genetic interaction between a major host resistance gene (R-gene) and a pathogen avirulence (avr) gene (Belkhadir et al., 2004; Skamnioti and Ridout, 2005). Although we do not yet fully understand all of the features associated with these two types of resistances, it is becoming quite apparent that there is substantial overlap in the signaling networks employed by the two, and that in both cases transcriptional activation of defense genes plays a pivotal role (Nimchuk et al., 2003; Eulgem, 2005). Stimulation of defense responses is not only locally restricted to the site of infection but also occurs in distal areas of the plant, a reaction termed systemic acquired resistance (SAR) (Durrant and Dong, 2004). Activation of the SAR pathway confers immunity throughout the plant toward a broad range of microorganisms. Over the past few years, huge progress has been made in deﬁning key upstream components and early signaling events vital for establishing plant resistance. However, although the plant cell nucleus represents a major target of different defense signal transduction pathways, our understanding of the terminal signaling stages is extremely rudimentary. We know very little about the biochemical signals and how they are relayed and linked to nuclear components and speciﬁc transcription factors (TFs). Equally fragmentary are our insights into the intricate transcriptional machinery responsible for executing proper temporal and spatial control of defense gene expression. In this review, I will present an update of our current state of knowledge on the key mechanisms and individual constituents involved in the transcriptional regulatory network governing the expression of the defense transcriptome.

11.2

Defense transcriptome

Intensive physiological, biochemical, molecular, and genetic studies over the past two decades using a number of plant pathosystems have revealed that plants respond to pathogen challenge by drastically reprogramming overall cellular metabolism. All nonessential cellular activities appear to be arrested or downregulated, probably to redirect substrates and energy to the de novo synthesis of a complex spectrum of defense-related metabolites (Somssich and Hahlbrock, 1998; Hahlbrock et al., 2003). This major redirection of cell metabolism is a consequence of extensive transcriptional reprogramming resulting in the altered expression of numerous genes coding for diverse products derived from both primary and secondary metabolism (Batz et al., 1998; Rushton and Somssich, 1999; Durrant et al., 2000). These earlier observations have been substantiated and extended by the development of large-scale gene expression proﬁling techniques (Scheideler et al., 2002) and the intensive use of the fully sequenced model plants Arabidopsis thaliana and rice for plant–pathogen interaction studies. Microrarray analyses have revealed massive transcriptional reprogramming, affecting up to 20% of the entire Arabidopsis genome, following challenge by diverse pathogens or by pathogen-mimicking stimuli (Nimchuk et al.,

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2003; Katagiri, 2004). The Arabidopsis defense transcriptome comprises genes with known functions related, among others, to signaling, transport, transcription, and primary and secondary metabolism. A similarly complex expression pattern was observed by comprehensive transcript proﬁling of pathogen-mediated host defense responses in rice and tomato (Chu et al., 2004; Gibly et al., 2004). The ability to monitor the expression of thousands of genes simultaneously under different defenserelated treatments and in a spatial and temporal manner has enabled us to detect novel genes associated with defense and to identify coregulated genes (regulons). Additionally, valuable information on the links between defense and other plant responses has been gained from such global analyses. For instance, previous genetic studies have indicated substantial crosstalk between defense and senescence and between different defense-signaling pathways (Obreg´on et al., 2001; Glazebrook, 2005). Indeed, microarray studies have revealed signiﬁcant overlap in the genes activated upon pathogen challenge and during leaf senescence (Buchanan-Wollaston et al., 2003), as well as by treatments with salicylic acid (SA) and jasmonic acid (JA), molecules that trigger two distinct defense pathways originally thought to act antagonistically (Bostock, 2005). Extensive overlap in the genes associated with defense, wounding, and other stresses have also been observed (Durrant et al., 2000; Cheong et al., 2002). One vital piece of information gained from such studies is that the expression patterns associated with compatible (the plant is susceptible) and incompatible (the plant is resistant) plant–microbe interactions can be strikingly similar, but both the speed and the amplitude of expression are often greater during the R-genedependent resistance response (Nimchuk et al., 2003; Katagiri, 2004). Thus, the temporal aspect of the host response may be a key determinant in deciding whether the plant or the pathogen wins the battle.

11.3

Regulatory sequences mediating defense gene expression

Expression of any given gene is primarily determined by the interaction of different TFs and cofactors acting at speciﬁc DNA sites within its regulatory regions. Other processes that involve interactions with other proteins and signaling cascades in turn regulate the TFs. Several distinct cis-acting DNA elements have been pinpointed in the promoters of defense-associated plant genes that mediate pathogen-dependent expression (Table 11.1) (Eulgem, 2005). Expression of PR1 in Arabidopsis is strongly upregulated during pathogen infection or upon chemical treatments known to activate the SA-dependent defense-signaling pathway. Functional dissection of its promoter revealed the importance of two positive regulatory elements, the activator sequence-1-like (as-1) element and an undeﬁned sequence, 5 -AGGACTTTTC-3 , and one negative regulatory element containing a W RKYbinding site (W-box) (Lebel et al., 1998) (Table 11.1). In parsley, several genes responding rapidly and transiently to pathogen stimuli were identiﬁed (Somssich and Hahlbrock, 1998). Detailed functional dissection of their promoters using a protoplast system for transient expression revealed the presence of several cis-acting

TRANSCRIPTIONAL REGULATION UNDERLYING PLANT DEFENSE Table 11.1

269

Regulatory DNA sequences mediating defense gene expression

DNA element

TF class

Reference

TGACGTCA (as1-like) AGGACTTTTC TTGACC/T (W-box) TTCAAACA (D-box) GCCACCA (S-box) AGCCGCC (GCC box) AGACCGCC (JERE box) GTCAAAAA/T (PB box) CTGAAGAAGAA (TL1)

TGA factor (bZIP) ? WRKY factor ? ? ERF factor (AP2 class) ORCA (AP2 class) Whirly factor ?

Jakoby et al. (2002) Lebel et al. (1998) Eulgem et al. (2000) Rushton et al. (2002) Kirsch et al. (2001) Gutterson and Reuber (2004) Memelink et al. (2001) Desveaux et al. (2005) Wang et al. (2005)

‘?’ indicates interacting factor is unknown.

DNA elements that were both necessary and sufﬁcient (can act independently) to mediate elicitor-dependent responsiveness of the respective gene (Rushton et al., 1996; Kirsch et al., 2000, 2001). Positive elements uncovered in this system included the D-box, S-box, and W-box (Table 11.1). All of these individual elements alone were also capable of driving strong pathogen-dependent expression of a reporter gene in transgenic Arabidopsis plants (Rushton et al., 2002). The GCC element and variations such as the JERE box were found in numerous plant defense gene promoters that are activated via the JA- or ethylene-signaling pathways (Memelink et al., 2001; Gutterson and Reuber, 2004). Two additional DNA elements shown to be important in the activation of defense genes included the PB box, that was originally found in the potato PR-10a gene promoter but is also present in other plant defense gene promoters (Desveaux et al., 2004), and the TLI element present in the promoters of several Arabidopsis genes encoding endoplasmic-reticulum-resident proteins (Wang et al., 2005). Recently, differential expression of the rice R-gene Xa27 was shown to determine resistance toward the bacterium Xanthomonas oryzae (Gu et al., 2005). Intriguingly, the promoter sequences of the Xa27 alleles present in the resistant and susceptible rice cultivars are nearly identical except for the presence of an additional 10-bp sequence at –1400 bp and a 25-bp duplication at –97 bp in the susceptible allele. Infection by the bacterium carrying the corresponding avrXa27 avirulence gene selectively induced expression of the resistant allele, indicating that speciﬁcity resided within the Xa27 promoter (Gu et al., 2005). The availability of fully sequenced genomes and the use of microarrays to monitor the expression of thousands of genes under a variety of conditions have provided a rich resource for the in silico detection of regulatory DNA elements. Bioinformatics methods are being developed with the ultimate aim of producing comprehensive maps of the regulatory networks within respective organisms (Rombauts et al., 2003; Wasserman and Sandelin, 2004). Despite the development of numerous algorithms, detection of key cis-regulatory elements remains an enormous challenge. Nevertheless, computational analyses have already provided us with some important clues concerning regulatory elements involved in defense gene activation. Applying

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clustering methods, several groups identiﬁed the W-box element as a commonly occurring motif within the promoters of coregulated defense-response genes (Maleck et al., 2000; Petersen et al., 2000; Navarro et al., 2004; Andreasson et al., 2005). In the studies performed by Petersen et al. (2000) a second conserved motif, similar to the 5 -AGGACTTTTC-3 element found in the Arabidopsis PR1 promoter, was also found. The potential power of computational biology was exempliﬁed by the recent work of Wang et al. (2005). Microarray experiments designed to search for downstream target genes coordinately regulated by the nuclear-localized protein NPR1, a key regulator of SAR (Durrant and Dong, 2004), revealed a set of genes coding for secretion-related products. Analysis of the promoters of 13 of these genes revealed the presence of a common novel element designated TL1 (Table 11.1). Transgenic Arabidopsis plants harboring expression constructs driven by the TL1 or mutated TL1 elements subsequently conﬁrmed the importance of this motif in mediating SA-induced expression (Wang et al., 2005).

11.4

Transcription factors involved in defense gene regulation

The drastic transcriptional reprogramming associated with the plant defense response requires the interaction of speciﬁc TFs with DNA, with other TFs, and with diverse nuclear proteins including coactivators/-repressors or components of the general transcriptional machinery. Currently, we have just begun to identify members of several TF families that selectively modulate defense gene expression. Such studies are complicated by the fact that in the majority of cases, TFs belong to large gene families and that functional redundancy often masks the contribution of individual members. Nevertheless, it is becoming obvious that TGA proteins of the bZIP family (Jakoby et al., 2002), ethylene-response factors (ERFs) of the AP2 ¨ class of TFs (Gutterson and Reuber, 2004), and WRKY TFs (Ulker and Somssich, 2004) are key players (Table 11.2). Several lines of evidence support the involvement of TGA factors in SAR and in the direct regulation of PR1, a prominent SA-inducible Arabidopsis marker gene. Previous work showed that NPR1 interacts in vitro and in vivo with selected TGA factors leading to enhanced binding of these factors to the as-1 site within the PR1 promoter (Durrant and Dong, 2004; Fobert and Despres, 2005). SA- and NPR1dependent in vivo recruitment of TGA2 and TGA3 to the PR1 promoter was also demonstrated using chromatin immunoprecipitation (ChIP) (Johnson et al., 2003). Moreover, genetic studies using tga2, tga5, and tga6 mutant Arabidopsis lines revealed the existence of functional redundancy between these factors and also illustrated their essential roles in SAR (Zhang et al., 2003). Interestingly, overexpression of TGA5 conferred resistance in Arabidopsis to an oomycete pathogen, but this was independent of SA and NPR1 (Kim and Delaney, 2002), indicating that TGA factors can effect other plant resistance mechanisms. In rice, ectopic expression of a dominant-negative variant of rTGA2.1, or silencing of the corresponding endogenous gene, both resulted in plants showing elevated transcript levels of defense marker genes and increased tolerance toward a bacterial pathogen, consistent with a negative function of the wild-type gene in defense (Fitzgerald et al., 2005).

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Table 11.2 Plant transcription factors implicated in regulating defense responses toward phytopathogens TF class

Name/synonyms

Origin

References (and citations within)

AP2/EREBP

ERF1 AtERF1 AtERF2 AtERF4 AtERF13 CaPF1 pCaERFLP1 NbCD1

Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Hot pepper Hot pepper Nicotiana benthamiana Periwinkel Periwinkel Rice Tobacco Tobacco Tobacco Tomato Tomato Tomato Tomato Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Tobacco Tobacco Rice Arabidopsis Arabidopsis Periwinkel Tobacco Tomato Tomato Arabidopsis Arabidopsis Potato Arabidopsis Potato Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Barley

Berrocal-Lobo and Solano (2002) Gutterson and Reuber (2004) Gutterson and Reuber (2004) Yang et al. (2005) Gutterson and Reuber (2004) Li et al. (2004) Lee et al. (2004b) Nasir et al. (2005)

bHLH/MYC BZIP

MYB

NAC

Whirly WRKY

ORCA2 ORCA3 OsEREBP1 NtERF5 Tsi1 OPB1 Pti4 Pti5 Pti6 TSRF1 AtMYC2/JAI1/JIN1 TGA2 TGA3 TGA4 TGA5 TGA6 TGA2.1 TGA2.2 RTGA2 AtMYB30 BOS1/AtMYB108 CrBPF-1 myb1 JAMYC2 JAMYC10 ATAF2 TIP StNAC AtWhy1 PBF-2/StWhy1 AtWRKY6 AtWRKY18 AtWRKY22 AtWRKY25 AtWRKY29 AtWRKY33 AtWRKY70 RRS1/AtWRKY52 HvWRKY38/TDF N9-10

Memelink et al. (2001) Memelink et al. (2001) Zhou et al. (1997) Fischer and Dr¨oge-Laser (2004) Park et al. (2001) Guo et al. (2004) Zhou et al. (1997) Zhou et al. (1997) Zhou et al. (1997) Zhang et al. (2004) Lorenzo et al. (2004) Durrant and Dong (2004) Durrant and Dong (2004) Durrant and Dong (2004) Durrant and Dong (2004) Durrant and Dong (2004) Durrant and Dong (2004) Durrant and Dong (2004) Fitzgerald et al. (2005) Vailleau et al. (2002) Mengiste et al. (2003) Memelink et al. (2001) Eulgem (2005) Lorenzo and Solano (2005) Lorenzo and Solano (2005) Delessert et al. (2005) Olsen et al. (2005) Olsen et al. (2005) Desveaux et al. (2005) Desveaux et al. (2005) ¨ Ulker and Somssich (2004) ¨ Ulker and Somssich (2004) Asai et al. (2002) Andreasson et al. (2005) Asai et al. (2002) Andreasson et al. (2005) Li et al. (2004) Deslandes et al. (2002) Eckey et al. (2004)

(Continued)

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Table 11.2 Plant transcription factors implicated in regulating defense responses toward phytopathogens (Continued) TF class

Name/synonyms

Origin

References (and citations within)

PcWRKY1 PcWRKY2 PcWRKY3 PcWRKY4 PcWRKY5 NbWRKY1

Parsley Parsley Parsley Parsley Parsley Nicotiana benthamiana Nicotiana benthamiana Nicotiana benthamiana Tobacco Tobacco Tobacco Tobacco Tobacco Tobacco Tobacco Tobacco Hot pepper

Eulgem et al. (2000) Eulgem et al. (2000) Eulgem et al. (2000) Eulgem et al. (2000) Eulgem et al. (2000) Liu et al. (2004)

NbWRKY2 NbWRKY3

Z-C2H2

WRKY1 NtWIZZ tWRKY1 tWRKY3/NtDBP3 tWRKY4 NtWRKY3 NtEIG-D48/NtSubD48 TIZZ CaZFP1

Liu et al. (2004) Liu et al. (2004) Menke et al. (2005) Eulgem et al. (2000) Eulgem et al. (2000) Eulgem et al. (2000) Eulgem et al. (2000) ¨ Ulker and Somssich (2004) ¨ Ulker and Somssich (2004) ¨ Ulker and Somssich (2004) Kim et al. (2004)

Regulatory nuclear proteins involved in plant defense with no known DNA-binding capabilities HDA19 IQD1 MKS1 NPR1/NIM1 NIMIN1/2/3 NPR4 SN1 NH1 NRR GmCaM-4 GmCaM-5

Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Rice Rice Soybean Soybean

Zhou et al. (2005) Levy et al. (2005) Andreasson et al. (2005) Durrant and Dong (2004) Weigel et al. (2005) Lorenzo and Solano (2005) Durrant and Dong (2004) Chern et al. (2005) Chern et al. (2005) Park et al. (2004) Park et al. (2004)

The best examined case for the involvement of ERF/AP2-type TFs in disease resistance is Pti4 from tomato. Pti4 was isolated along with two other ERF proteins by their ability to interact with Pto, a protein kinase encoded by a major R-gene conferring resistance to bacterial speck disease (Zhou et al., 1997). Pti4 was shown to be speciﬁcally phosphorylated by Pto and thereby to increase its binding afﬁnity to the GCC boxes present in several defense gene promoters (Gu et al., 2000). Expression of several ERF genes was shown to be induced by ethylene or JA treatments and by pathogen infections (Gutterson and Reuber, 2004). Ectopic expression of Arabidopsis ERF1 or the tomato Pti4 in Arabidopsis, as well as the tomato ERF gene TSRF1 in both tomato and tobacco plants, resulted in improved resistance toward several tested pathogens (Berrocal-Lobo and Solano, 2002; Gu et al., 2002; Zhang et al., 2004). For tobacco NtERF5, overexpression had no effect on infections

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273

with the bacterial pathogen Pseudomonas syringae (P. syringae) but signiﬁcantly enhanced resistance toward Tobacco Mosaic Virus (Fischer and Dr¨oge-Laser, 2004). The ERF genes Tsi1 and OPBP1 from tobacco and CaPF1 and pCaERFLP1 from pepper are induced by biotic and abiotic stresses (Park et al., 2001; Guo et al., 2004; Lee et al., 2004b; Yi et al., 2004). All four TFs showed in vitro binding to the GCC box, and with the exception of OPBP1, also to the drought-, cold-, and osmoticresponse DNA element 5 -A/GCCGACAT-3 , designated DRE/CRT, known to be bound by a subset of the ERF/AP2 family (Shinozaki et al., 2003). Thus, a dual function of these TFs in response to various stresses could be expected. Indeed, Tsi1 overexpression in transgenic tobacco and pepper plants, and OPBP1 in tobacco, enhanced resistance to multiple tested phytopathogens and also resulted in salt-tolerant plants (Park et al., 2001; Guo et al., 2004). Similarly, high constitutive expression of pCaERFLP1 in tobacco rendered plants resistant to P. syringae infection and more tolerant to high salinity (Lee et al., 2004b). Transgenic Arabidopsis plants ectopically expressing CaPF1 showed enhanced resistance to P. syringae infection, but in this case the plants displayed tolerance against freezing temperatures (Yi et al., 2004). Consistent with a dual role, both CaPF1 and pCaERFLP1 transgenic plants had elevated transcript levels of pathogen- and stress-response genes containing either GCC or DRE/CRT boxes in their promoters. Most of the characterized ERF factors function as transcriptional activators. Recently however, ERF members capable of actively repressing transcription have also been reported (Yang et al., 2005). For one, NbCD1, a negative regulatory function associated with nonhost resistance and pathogen-triggered cell death, was identiﬁed (Nasir et al., 2005). Although experiments based exclusively on overproduction of TFs must be dealt with caution, the results outlined above are consistent with an important contribution of ERFs to plant defense. Less well studied is another group of AP2-type TFs, designated Octadecanoid-Responsive Catharanthus-APETALA2-domain proteins (ORCAs), which activate some JA-responsive genes involved in alkaloid metabolism via binding to Jasmonate- and Elicitor-Responsive Element (JERE) promoter sites (Memelink et al., 2001). Several members of the zinc-ﬁnger-type WRKY TFs have been implicated in defense-related plant responses. WRKY-binding sites (W-boxes) are often found enriched in promoters of coregulated defense genes. Moreover, in Arabidopsis, expression of over 70% of the entire WRKY gene family is strongly affected by ¨ various stresses, particularly by pathogen-related stimuli (Ulker and Somssich, 2004). In Arabidopsis, AtWRKY22 and AtWRKY29 were found to be involved in a PAMP-mediated defense-signaling pathway, and transient overexpression of AtWRKY29 conferred resistance to an otherwise virulent bacterial pathogen (Asai et al., 2002). Likewise, overexpression of AtWRKY70 in Arabidopsis plants resulted in enhanced resistance to two tested virulent bacteria (Li et al., 2004). In tobacco, virus-induced gene silencing of three WRKY genes (NtWRKY1–3) compromised N -gene-mediated resistance toward Tobacco Mosaic Virus (Liu et al., 2004). ChIP analyses in parsley revealed elicitor-dependent and transient in vivo binding of a WRKY factor (PcWRKY1) to the promoters of PcWRKY1 and PcPR1-1, two

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strongly pathogen-responsive genes (Turck et al., 2004). The Arabidopsis major R-gene, RRS1, which confers resistance to bacterial wilt, represents a novel type of WRKY gene. This gene, also designated AtWRKY52, codes for a protein containing structural features of NBS-LRR-type R-gene products and a C-terminal WRKY domain (Deslandes et al., 2002). RRS1/AtWRKY52 appears to be translocated to the plant cell nucleus together with the bacterial avr product PopP2, but it is currently unclear whether it regulates transcription of target genes (Deslandes et al., 2003). Another class of TFs found in diverse plants are the Whirly TFs (Why) (Desveaux et al., 2005). These preferentially bind to the single-stranded form of their respective PBF-2 binding DNA element (PB box). Elicitor-dependent in vivo binding activity of StWhy1 to the promoter of the pathogen-response gene PR-10a was demonstrated by ChIP experiments in potato. Furthermore, missense mutants of AtWhy1 in Arabidopsis showed enhanced susceptibility toward oomycete infections, suggesting a key role of the factor in plant defense (Desveaux et al., 2005). Members of several other classes of TF genes were found to be rapidly induced upon pathogen attack in global expression data (Chen et al., 2002) or from individual studies, indicating their potential in regulating the defense transcriptome (Table 11.2). Nonetheless, our knowledge on these factors is rather limited. However, a clear link has been established between two Arabidopsis MYB family members, AtMYB30 and BOS1, and plant defense. AtMYB30 appears to act as a positive regulator of the hypersensitive (HR) cell death program induced in response to pathogen challenge (Vailleau et al., 2002). Overexpression of AtMYB30 in Arabidopsis and tobacco led to enhanced HR cell death and increased resistance to different bacterial pathogens, whereas suppression of AtMYB30 expression had converse effects. In the case of BOS1, loss-of-function mutants displayed enhanced disease symptoms toward both biotrophic and necrotrophic pathogens (Mengiste et al., 2003). Expression of BOS1 is induced upon pathogen treatment via the JA-signaling pathway and BOS1 itself appears to regulate the expression of a subset of JA-responsive genes. One Arabidopsis member of the bHLH family, AtMYC2/JAI1/JIN1, was shown to have dual functions, acting as a positive regulator of abiotic stress signaling and as a negative regulator of the JA and ethylene defense pathways (Anderson et al., 2004; Lorenzo et al., 2004). Interestingly, AtMYC2/JAI1/JIN1 was shown to repress JA-mediated genes related to pathogen defense, but to activate genes involved in JA-mediated responses to wounding (Lorenzo et al., 2004). Mutants of AtMYC2/JAI1/JIN1 showed enhanced JA- and ethylene-dependent resistance to three different necrotrophic fungal pathogens. Ectopic expression of Arabidopsis ATAF2, a NAC-domain TF family member (Olsen et al., 2005), resulted in repression of several defense marker genes and in heightened susceptibility toward the soil-borne fungal pathogen Fusarium oxysporum (Delessert et al., 2005). Conversely, ATAF2 knockout plants exhibited elevated transcript levels of these genes, consistent with a repressor function of this TF in the defense response. Finally, overexpression of a pepper Cys2 /His2 -type zinc-ﬁnger TF, CAZFP1, in Arabidopsis, led to enhanced resistance of the plants to a bacterial pathogen (Kim et al., 2004).

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11.5

275

Transcriptional networks

Understanding how the transcriptional regulatory network is linked to the various defense-signaling cascades governing cellular responses is of utmost importance. We need to know how the signal is transduced to the DNA-binding transcriptional regulators and to deﬁne the intermediate nuclear interactions that are essential for proper control of defense gene expression. Recently, downstream components of distinct MAP kinase signaling pathways involved in plant defense have been uncovered (Pedley and Martin, 2005). In rice, a MAP kinase designated BWMK1 was discovered, whose activity was rapidly induced by pathogen-mimicking signals (Cheong et al., 2003). BWMK1 localizes exclusively to the cell nucleus, and can phosphorylate the AP2-type TF OsEREBP1 in vitro, thereby increasing the binding afﬁnity of this factor to GCC-box-containing DNA sequences. This is reminiscent of the already mentioned interaction of the Pto4 kinase with ERF factors in tomato (Zhou et al., 1997). In Arabidopsis, the MAP kinase 4 mutant, mpk4, exhibited constitutive SAR and resistance to virulent pathogens (Petersen et al., 2000). MPK4 interacts with MKS1, a nuclear-localized protein of unknown function, which can bind two WRKY TFs, namely AtWRKY25 and AtWRKY33 (Andreasson et al., 2005). MPK4 is capable of phosphorylating both MKS1 and the WRKY factors, and it is hypothesized that MKS1 acts as a coupling protein affecting the activities of the TFs in MPK4-mediated signaling. WRKY factors have also been implicated as downstream components in a deﬁned PAMP-mediated MAP kinase defensesignaling cascade in Arabidopsis (Asai et al., 2002). In this case, a signal triggered by the interaction of a bacterial ﬂagellin with the FLS2 receptor was transduced via MEKK1, MKK4/MKK5, and MPK3/MPK6, leading to gene activation of AtWRKY22 and AtWRKY29. However, it remains unclear what the direct nuclear partner(s) of MPK3/MPK6 signaling are. Similarly, in parsley, a PAMP-mediated MAP kinase cascade involving PcMKK5 and PcMPK3/PcMPK6 was found, and PcMPK3/PcMPK6 activities were observed in the nucleus upon stimulation, indicating that they exert their functions within this compartment (Lee et al., 2004a). In this system, two subsequent early nuclear steps were shown to be regulated by WRKY TFs (Eulgem et al., 1999). However, a direct link to the MAP kinases has not yet been established. Recently, the tobacco WRKY1 was shown to be directly phosphorylated by the MAP kinase SIPK and to mediate HR-like cell death (Menke et al., 2005). Currently, the best elucidated signaling cascade leading to defense gene activation is the SAR pathway (Durrant and Dong, 2004; Fobert and Despres, 2005). In Arabidopsis, pathogen infection leads to elevated levels of the endogenous signal molecule SA. This increase in SA alters the redox state of the cell allowing NPR1, which is sequestered in an inactive oligomeric form in the cytoplasm, to be reduced to its monomeric active state and thus to be translocated to the nucleus. Within the nucleus, NPR1 physically interacts with TGA factors such as TGA1 or TGA4 and thereby stimulates their binding to as-1 promoter sites within a set of immediateearly response type PR genes. This interaction requires not only the reduced state of NPR1, but also the SA-dependent reduction of two key cysteine residues within both TGA1 and TGA4 (Despr´es et al., 2003). NPR1 however does not appear to be part of

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the TGA complex once it is associated with DNA (Despr´es et al., 2003). Apart from this, NPR1 also directly regulates another set of immediate-early SAR-response genes containing TL1 elements within their promoters (Wang et al., 2005). Since NPR1 shows no obvious DNA-binding activity and TGA factors do not bind to TL1 elements, activation of this set of genes requires interaction of NPR1 with other so far unknown TF(s). Potential candidates for such factors are the NIMIN1/2/3 proteins, small nuclear-localized acidic proteins that have been shown to interact with NPR1 (Weigel et al., 2005). However, there is no evidence suggesting that these proteins can bind TL1 sites or even DNA. Interestingly, NPR1 itself appears to be transcriptionally controlled by WRKY factors, as W-box mutations within the NPR1 promoter strongly compromised its expression (Yu et al., 2001). The role of redox control in regulating other transcriptional processes implicated in plant defense may be more signiﬁcant than previously anticipated. Microbial infections often trigger a rapid production of reactive oxygen intermediates (ROI) as signaling molecules in the host (Mittler et al., 2004). Increased ROI generation/signaling can modulate defense gene expression but the level of ROI must be kept in check due to their cellular toxicity. This is achieved by major ROI-scavenging enzymes and also by oxidoreductases such as thioredoxin and glutaredoxins, which are responsible for controlling and maintaining cellular redox homeostasis. Oxidoreductases are capable of modifying TFs, thereby directly affecting gene expression patterns (Tron et al., 2002). In this respect, it is interesting to note that activation of the oxidative stress and pathogen-responsive Arabidopsis thioredoxin h5 gene appears to be mediated by W-box promoter elements, and that plants ectopically overexpressing AtWRKY6 showed upregulated expression of this gene (Laloi et al., 2004). A number of other Arabidopsis nuclear-localized components have been partly characterized that seem to play important, albeit ill-deﬁned, roles in the plant defense response. One gene designated SNI1 was uncovered in a mutant screen in search of suppressors of npr1. sni1 mutants restore SA responsiveness of PR genes and pathogen resistance in the npr1 background. SNI1 is localized to the nucleus but appears to lack DNA-binding activity and may act as a repressor of a general transcriptional function common between yeast and plants (Durrant and Dong, 2004). The AtWRKY70 TF has been reported to play a crucial regulatory role at the convergence point of the SA- and JA-signaling pathways, positively regulating SAresponse genes and negatively regulating JA-response genes (Li et al., 2004). A gene designated IQD1 was detected in a screen of T-DNA activation-tagged lines (Levy et al., 2005). Upregulation of IQD1 stimulated glucosinolate accumulation, a small and diverse class of defense-associated secondary metabolites, and also reduced insect herbivory. IQD1 is a nuclear-localized basic protein of 50.5 kDa containing several functional calmodulin-binding sites but appears to lack any DNA- or RNAbinding motifs. Finally, plants overexpressing HDA19 encoding a histone deacetylase had decreased histone acetylation levels, showed increased expression of the ERF1 TF gene, and were more resistant to the necrotroph Alternaria brassicicola (Zhou et al., 2005). In contrast, downregulation of HDA19 resulted in plants being more sensitive to this pathogen. In rice, a small nuclear-localized proline-rich protein, designated NRR, was identiﬁed by its ability to interact with NPR1 as well as with the rice NPR1 homolog

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NH1 (Chern et al., 2005). NRR shares limited similarity to the Arabidopsis NIMIN2 and tobacco G8-1 proteins. Constitutive overexpression of NRR in rice suppressed defense responses and resistance to the bacterial pathogen Xanthomonas oryzae implying a negative function of NRR in plant defense. Silencing of NRR expression did not affect the response of plants toward this pathogen, suggesting that other rice proteins may play redundant roles to NRR.

11.6

Defense gene suppression by pathogens

How many of the vast number of host genes that are altered in their expression during a plant–pathogen interaction are actually involved in plant defense is difﬁcult to say. What has become evident however is that some of these host genes, designated susceptibility genes, are actually targets of the pathogen, thereby enabling them to overcome certain resistance barriers (Abramovitch and Martin, 2004; Nomura et al., 2005). This is probably part of the ongoing coevolutionary tug-of-war for survival between plants and microbes. Indeed, global expression studies with Arabidopsis have revealed that bacterial pathogens deliver numerous effector molecules (products of the avr genes) into the host that act to suppress the expression of defense genes triggered by the PAMP surveillance system of the plant (Mudgett, 2005; N¨urnberger and Lipka, 2005). Similarly, microarray analyses revealed that infections by a virulent powdery mildew fungus either suppressed or failed to activate the JA/ethylene defense-signaling pathways (Zimmerli et al., 2004). Ectopic activation of the JA/ethylene pathway resulted in protection against this powdery mildew as well as against a virulent oomycete, indicating that avoidance/suppression of such defenses is required for successful pathogen colonization. One well-established case is the Arabidopsis NHO1 gene coding for a glycerol kinase required for resistance to nonhost P. syringae strains and also to the fungal pathogen Botrytis cinerea (Kang et al., 2003). Expression of this gene is strongly induced by nonhost bacterial strains but actively suppressed by virulent strains targeting the JA-dependent pathway (Li et al., 2005). Ectopic expression of NHO1 led to increased plant resistance to a virulent strain, further supporting its involvement in plant defense. Another example of the suppression of defense genes comes from ﬁndings that coronatine, a phytotoxin produced by several pathovars of P. syringae, completely mimics the plant signal molecule methyl jasmonate (MeJA). Plant resistance toward bacteria such as Pseudomonas is established by activation of the SA defense pathway. Coronatine, acting as MeJA, activates the JA defense pathway and thereby suppresses the SA pathway required to restrict growth of these bacteria (Nomura et al., 2005).

11.7

Summary and outlook

We have made substantial progress in understanding the importance of transcription in activating plant defense responses against phytopathogens. Equally evident however is that we are just at the beginning of our efforts to uncover and dissect the complex and highly interconnected defense transcriptional network. For example,

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only recently have we begun to realize that abiotic stress signaling controlled by the key hormone abscisic acid is also interwoven into this network (Mauch-Mani and Mauch, 2005). Abscisic acid signaling is generally considered to negatively regulate disease resistance, and thus the spectrum of defense genes and/or the transcriptional regulators involved may be quite different. Eukaryotic gene promoters are made up of a composite of cis-regulatory DNA elements capable of being bound by different classes of TFs, which are themselves, embedded in larger regulatory complexes. Often, both the amplitude and the duration of transcription will be determined by speciﬁc TF interactions as well as by discrete transient TF associations/dissociations at a given promoter. Recent advances in molecular and computational biology are opening the way for us to begin constructing and validating transcriptional regulatory networks (Barabasi and Oltvai, 2004; Blais and Dynlacht, 2005). Thanks to the availability of fully sequenced plant genomes, we can now deduce the complete set of TFs within these species. Highthroughput approaches to identify all potential TF–TF interactions have been established (Immink and Angenent, 2002) and should provide valuable clues concerning candidate interactors. Gene expression proﬁling supplemented with data derived from the use of the large collections of available insertional Arabidopsis TF mutants will help to pinpoint distinct sets of coregulated TFs and downstream defense genes. It is foreseeable that such studies will be complemented by the genome-wide application of the ChIP technique (ChIP-chip, STAGE) to determine the entire spectrum of in vivo TF target genes (Gao et al., 2004; Hanlon and Lieb, 2004; Kim et al., 2005). Using bioinformatics tools to merge the data of these several sources, we can start to create an extensive map of the transcriptional network deﬁning the plant defense response. There are, however, several additional levels of regulation that need to be considered. Protein–protein and protein–DNA interactions can be highly dynamic, making deﬁnition of the entire transcription network a daunting endeavor. TFs and associated components can undergo various modiﬁcations including phosphorylation (Holmberg et al., 2002), acetylation (Sng et al., 2004), ubiquitination (Conaway et al., 2002), and sumoylation (Miura et al., 2005). Such alterations may profoundly alter TF functions. There is also an emerging recognition that chromatin structure can act both locally and globally to regulate gene expression (Felsenfeld and Groudine, 2003). For instance, modiﬁcations of chromatin proteins such as histone H3 can directly affect expression at speciﬁc promoter sites through their interaction with TFs. In particular, intracellular signaling through MAP kinase cascades can directly act to modify chromatin proteins (Clayton and Mahadevan, 2003; de Nadal et al., 2004). Considering the extensive involvement of MAP kinases in plant defense (Nakagami et al., 2005), we can expect that defense gene expression will in part be regulated by such chromatin modiﬁcations. Beyond this, an increasing body of evidence indicates that nuclear architecture is linked to the organization and sorting of regulatory information, thereby representing another level of complexity that needs to be taken into consideration (Stein et al., 2003). Finally, newly uncovered transcriptional regulatory mechanisms involving small RNAs (Willmann and Poethig, 2005) must also be taken into account.

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In summary, although the key mechanisms and individual constituents of the defense transcriptome network are becoming apparent, our understanding is still inadequate to explain the elaborate molecular apparatus that allows regulatory discrimination and selective trafﬁcking of proteins to translate into speciﬁc transcriptional outputs. In particular, there is a need to capture, purify, and characterize the highly dynamic, multimeric transcriptional complexes at distinct promoter sites following signaling through deﬁned defense pathways. Furthermore, we need to know the biochemical basis of how the convergence of synergistic and antagonistic signals at a given promoter is resolved. Improvements in computational biology and in rapidly evolving ultrasensitive high-throughput methodologies, as illustrated by protein mass spectrometry, will certainly facilitate our basic understanding of the transcriptional regulatory defense network. Beyond this however, we will need to delineate the topology and dynamics of this gene network in order to fully grasp the biological complexity governing plant defense responses.

Acknowledgments I am grateful to Drs George Coupland and Richard O’Connell (MPIZ K¨oln) for critical reading of the manuscript. I apologize to all my colleagues whose original publications I failed to cite due to space limitations.

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12 Temperature-regulated gene expression Friedrich Sch¨ofﬂ and Tressa Jacob Panikulangara

12.1 12.1.1

Heat stress Introduction

Temperature extremes impose variable stress severity depending on the rate of temperature change, the duration of the stress, and the intensity. The optimal/ambient growth temperatures and the heat stress temperatures vary with different plant species, as they are evolutionarily adapted to different climatic conditions. Basal levels of thermotolerance are indicated by a survival of nonacclimated plants to heat stress temperatures to up to 10–15◦ C above the optimal growth temperatures: for example, the normothermic conditions of Arabidopsis, tomato, and soybean are 25, 28, and 22◦ C respectively; the maximal heat stress temperatures range from 37 to 41◦ C. Treatments at higher temperatures would be lethal for nonacclimated plants but can be survived if plants are conditioned by a previous sublethal heat treatment. This acquisition of enhanced levels of thermotolerance or heat acclimation correlates at the molecular level with a transient reprogramming of gene expression. The expression of heat-shock proteins (HSPs) is a signature of the heat-shock response. It is well established that the same conditions that induce HSPs also cause heat inactivation and denaturation of cellular enzymes/proteins and that the HSPs act as molecular chaperons, assisting the refolding of denatured proteins (for review, see Sch¨ofﬂ et al., 1999). In all species studied, heat stress results in the production of HSPs, which have been classiﬁed into a number of families based on their molecular mass (HSP100, HSP90, HSP70, HSP60, and small (s) HSP), most of which have chaperon function (for review, see Jaenicke and Creighton, 1993; Boston et al., 1996). Plants are unique in the number and complexity of sHSP that they produce upon heat stress; no isoforms are expressed in vegetative tissue under nonstress conditions (for review, see Jakob and Buchner, 1994; Sch¨ofﬂ et al., 1998).

12.1.2

Heat stress sensing and signaling

Despite the ubiquitous nature of the heat-shock response, little is known how plants sense heat stress or about the signaling pathways resulting in heat-shock gene expression. In all organisms the heat-shock response is primarily regulated at the transcriptional level by heat-shock transcription factors (HSFs), which are activated by stress for a speciﬁc binding to heat-shock promoter elements (HSEs). Compared to cold stress the mechanisms of stress sensing and signaling in response to heat stress are poorly understood, although, hormonal, calcium, and redox signals have been

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implicated (Foyer et al., 1997; Clarke et al., 2000; Larkindale and Knight, 2002). However, there is no evidence for an involvement of membrane-bound receptors. The HSFs are considered as the central components for sensing and regulation of the heat-shock response. Plant HSFs belong to a multigene family comprising constitutive and stress-inducible members. The existence of heat-inducible HSFs suggests multistep mechanisms in target gene expression. The ‘chaperon titration’ model (Figure 12.1), adopted from animal and mammalian systems (Sch¨ofﬂ et al., 1998), integrates the different phenomena and known molecular components, which are involved in the regulation of HSF activity. Crucial to this model is a stress-induced imbalance between available chaperons and the load of denatured proteins. HSP-like chaperons are present in limited amounts under nonstress conditions but HSPs become major components after stress. The model proposes that under nonstress conditions HSF is already present but in an inactive HSF–HSP-chaperon-complex. Heat stress or certain other environmental stresses cause denaturation of cellular proteins, hence causing a higher demand of chaperon-refolding capacity. A competition for chaperons by denatured proteins leads to withdrawal of HSPs from HSF-chaperon-complexes, which is prerequisite for the formation of active HSF oligomers (Sch¨ofﬂ et al., 1998). This transition from monomeric (repressed) to trimeric (activated) state of HSF is the ﬁrst step in HSF activation. Activated HSF can bind to the HSE of target genes and stimulate their transcription. The subsequent accumulation of HSPs, the major products of the heat-shock response, meet the increased demand for chaperon capacity, and excess of HSPs would cause a feedback regulation by interacting with HSF, resulting in the formation of an inactive HSF-chaperon-complex. This model is in accordance with the transient nature of the heat-shock response. HSF modiﬁcations like phosphorylation or redox reactions (Reindl and Sch¨ofﬂ, 1997; Ahn and Thiele, 2003) may be involved in regulating HSF activity but have not been much studied in plants.

12.1.3

Heat stress transcription factors: structure and function

HSFs are the central regulators of the heat-shock response. Plant HSFs display a modular structure with a highly conserved N-terminal DNA-binding domain (DBD), which is characterized by a central helix-turn-helix motif, an adjacent bipartite oligomerization domain (HR-A/B) containing hydrophobic heptad repeats for HSF trimerization via the formation of a triple-stranded α-helical coiled coil, nuclear localization (NLS) and nuclear export (NES) sequences, and a C-terminal activator domain (CTAD) containing aromatic, hydrophobic, and acidic amino acids, the socalled AHA motifs (Nover et al., 1996, 2001). These structural characteristics are important for stress-dependent activation that converts the inactive HSF monomers to trimers, which bind after NLS to conserved heat-shock promoter elements (HSE consensus: -CAA- -TTC-) followed by transcriptional activation of the respective target genes (Wu, 1995). Contrasting other organisms, plants exhibit a multiplicity of heat stress transcription factors. Six HSF cDNA clones have been isolated from soybean (CzarneckaVerner et al., 1995), and in Arabidopsis thaliana, 21 different HSF genes have been

Figure 12.1 Levels of heat stress regulation. Octagonal boxes represent HSF transcription factors (classes A and B), open bars promoter-binding elements of genes, and ovals HSP (heat-shock proteins, chaperons).

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identiﬁed by cloning (Sch¨ofﬂ and Pr¨andl, 1999) and data mining of genomic sequences (Nover et al., 2001). More than 17 HSFs have been identiﬁed in tomato expressed sequence tag (ESTs) (Scharf et al., 1990; Nover et al., 2001) and up to 30 representatives were identiﬁed in the rice genome. Based on sequence relationship, plant HSFs are assigned to three classes A, B, and C (Nover et al., 1996, 2001). The structure of class A and C HSFs differs from that of class B by an insertion of 21 or 7 amino acids, respectively, separating hydrophobic regions HR-A and -B. Another structural difference between class A and class B HSFs is the absence of AHA motifs in their CTAD, which have appeared to be crucial for activator function of class A HSF (D¨oring et al., 2000). This lack of AHA motifs of class A HSF correlates with an inability for transcriptional activation of heat-shock promoter reporter genes in tobacco protoplasts (Czarnecka-Verner et al., 1997, 2000), and a class B HSF failed to rescue the yeast Hsf1 mutation (Boscheinen et al., 1997). By contrast, overexpression of class A HSFs in transgenic plants (Lee et al., 1995; Pr¨andl et al., 1998; Li et al., 2003) resulted in the expression of heat-shock promoterdriven stress and reporter genes. These structural and functional differences led to the hypothesis that class A HSFs represent the true transcriptional activators and class B HSFs are inert or repressor HSFs (Czarnecka-Verner et al., 1997, 2000). A peculiarity exclusive to plants is the ﬁnding that the expression of several members of the HSF family requires a heat stress for their own expression, suggesting a multistep mechanism of HSF involvement in the heat-shock response (Nover et al., 1996). The relatively high numbers of class A HSFs (there are 15 members in Arabidopsis) suggests that functional diversiﬁcation and/or genetic redundancy have evolved in plants.

12.1.4

Class A HSF: immediate early regulators of the heat-shock response

Arabidopsis class A HSFs have the capacity to act as positive regulators of heat-shock gene expression, originally implicated by transgenic overexpression of AtHsfA1a constructs (previously designated Hsf1, in Wunderlich et al., 2003; Lohmann et al., 2004) or AtHsfA1b (previously designated Hsf3, in Pr¨andl et al., 1998; Panchuck et al., 2002; Lohmann et al., 2004; Panikulangara et al., 2004) constructs in Arabidopsis, which resulted in a constitutive expression of HSPs and enhanced levels of basal thermotolerance (Lee et al., 1995; Pr¨andl et al., 1998). Heat-stress-dependent binding of AtHsfA1a to heat-shock gene promoters has been conﬁrmed by in vivo UV-laser crosslinking in Arabidopsis cells (Zhang et al., 2003). At present there is no evidence that in Arabidopsis a single HSF dominates the regulation of heat-shock response. Considering the high complexity of HSF genes in plants the isolation of HSF knockout mutants becomes crucial for determining their functional roles and biological importance in plants. T-DNA knockout mutations of class A HSF genes, AtHsfA1a or AtHsfA1b, showed only little effect on DNA binding, induction of heat-shock gene expression, and thermotolerance. Double knockout mutants (hsfA1a/1b) displayed an almost complete, selective loss of the early heat-shock-dependent DNA-binding capacity in plant cell extracts (Lohmann et al., 2004). The plants exhibited no detectable physiological or morphological

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phenotype and thermotolerance was only marginally impaired. However, the double knockout mutants exert clear negative effects in the immediate induction of HSF target gene expression. Thus these two class A HSFs (previously identiﬁed as positive transcriptional regulators of heat-shock gene expression, Lee et al., 1995; Pr¨andl et al., 1998) are required for only immediate early (within the ﬁrst 2 h of heat stress) regulation of the heat-shock response. In this early phase, differences in heat-induced mRNA levels, evident for different heat-shock genes, further suggest that not all heat-shock genes have the same requirements of HSF and/or synergistic effects between them. The transient accumulation of mRNA indicates that during sustained stress the transcription of heat-shock genes is negatively regulated in wild type (WT), probably via a negative regulation of HSF activity. After extended heat stress, WT and mutant plants showed comparable expression levels (mRNA and proteins) of all target genes tested (Lohmann et al., 2004). In WT, the transient accumulation of mRNA indicates that during sustained stress the transcription of heat-shock genes is negatively regulated, probably via a negative regulation of HSF activity. At present it is not known whether in AthsfA1a/1b double mutants this negative regulation is still implemented. Putative negative regulators of HSF activity are HSP70 and HSP90, which have been found to be associated in a complex with HSF in its inactive form in vertebrate cells (Mosser et al., 1993; Baler et al., 1996; Satyal et al., 1998; Zou et al., 1998). There is experimental evidence for an interaction between HSP70 and AtHSFA1a of Arabidopsis, which implicates a feedback regulation of the heat-shock response in plants (Kim and Sch¨ofﬂ, 2002). An alternative model for the shutoff of the heat-shock response suggests a replacement or inactivation of activator HSF by ‘repressor’ HSF, which become activated during later stages. Members of class B HSFs, which lack certain structural features of the class A activator HSFs (Nover et al., 2001), are implicated as transcriptional repressors or attenuators of the heat-shock response (Czarnecka-Verner et al., 1997, 2000). These class B transcription factors are known to inhibit promoter activity by repression mechanism that involves the C-terminal regulatory region (CTR). Deletion analysis revealed that in the CTR of soybean, GmHSFB1, which is potentially involved in protein–protein interaction with the general transcription factors, there were two sites, namely, the repressor domain (RD, located in the N-terminal half of the CTR) and the TFIIB-binding domain (located C-terminally from the RD) that binds to the TFIIB (Czarnecka-Verner et al., 2004).

12.1.5

Second-level regulation

The heat-dependent expression of certain class A and class B HSFs indicates that the immediate early phase (induction and expression of primary target genes), which is attributed to the action of constitutively expressed class A HSFs, also triggers a second wave of regulatory events. The expression of class B HSFs (AtHsfB1 and AtHsfB2b), which is controlled by class A HSFs, suggests that their function is required for regulating delayed effects of the heat-shock response. Certain other class B HSFs may serve as coactivators of gene expression during prolonged heat stress or during recovery (Bharti et al., 2004). The fact that also certain class A

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HSFs are expressed at a higher level after heat stress may indicate that the functions of putative ‘activator’ HSFs are required for the second-level regulation. Further analysis of Arabidopsis HSF knockout mutants will shed more light on the functional roles of class B HSFs in plants. In conclusion, loss-of-function mutant analysis provided evidence that two transcription factors, AtHsfA1a and AtHsfA1b, are fast response regulators, which are important for the coordination of stress gene expression and the generation of stress tolerance under rapidly changing environmental condition in nature. HSF functions seem to be required not only for the fast induction of stress genes (e.g., HSP, HSF) but consequently also for the timing of a negative feedback regulation causing transient expression in WT. Plants may have, in contrast to vertebrate cells, which clearly show defects in the heat-shock response when either Hsf1 or Hsf3 genes have been disrupted (McMillan et al., 1998; Tanabe et al., 1998; Xiao et al., 1999), a stronger backup and a more complex control of the stress-response system.

12.1.6

Heat stress target genes

HSP genes are known as the conventional targets of HSFs. Activated HSF binds to the conserved HSE sequences in their promoter regions, which results in the transcription of genes. Besides HSPs a few unconventional heat-shock genes like ascorbate peroxidase 2 (Apx2) and galactinol synthase1 (GolS1) (Panchuck et al., 2002; Panikulangara et al., 2004) and certain HSF genes (Lohmann et al., 2004) have been identiﬁed as HSF targets. Primary target genes were identiﬁed as genes whose short-term heat stress induction (1 h, 37◦ C) was signiﬁcantly impaired in AthsfA1a/1b knockout mutants of Arabidopsis (Lohmann et al., 2004). The transcriptome analysis of heat-stressed leaves of Arabidopsis WT and AthsfA1a/1b double knockout plants revealed a differential expression of a large number of genes (2567 and 3056 respectively) after short-term heat stress; however, only few of them (112) fulﬁlled the criteria for being direct targets of AtHsfA1a/1b (Busch et al., 2005). Among them were several of the known HSP genes and a number of novel genes with functions in different pathways, as, for example, in protein biosynthesis/degradation, membrane transport, oxidative stress response, and signaling (Busch et al., 2005). The exact biological functions of most of these genes are not known; however, some have been connected with environmental stress responses. For example, WRKY7 is involved in disease resistance (Maleck et al., 2000); scarecrow factors are involved in developmental processes but were also shown to be affected in expression by salt stress in Arabidopsis and osmotic stress in white spruce (Ueda et al., 2002; Stasolla et al., 2003); Dof zinc-ﬁnger proteins are associated with stress response and control of seed germination (Chen et al., 1996; Kang and Singh, 2000; Papi et al., 2000). Other HSF-upregulated targets are IAA2, a transcription factor, which is involved in auxin signaling (Reed, 2001), and AtERF4, an active repressor of transcription, which is induced by wounding, cold, high salinity, and drought stress (Fujimoto et al., 2000).

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The highest ranking unconventional heat-shock gene was GolS1; its mRNA is more than 100-fold induced by heat shock in WT, and it represents the highest score as an unconventional AtHsfA1a/1b-dependent heat-shock gene (Panikulangara et al., 2004; Busch et al., 2005). Within the family of sHSP, which comprises 18 members, the induction levels of 6 heat-shock-inducible sHSP genes were clearly dependent on AtHsfA1a/1b. Most striking was the AtHsfA1a/1b-dependent expression of other HSFs, in particular AtHsfB1, -B2a, and -A7a, which represent three out of six heat-inducible HSF genes. The identiﬁcation of AtHsfA7a (class A) as a HSF-dependent gene indicates that class B factors, which lack a AHA motif (transcriptional activation domain), are not the only ones involved in controlling expression of secondary HSF target genes for delayed functions in the heat-shock response. Microarray expression analysis of long-term heat-shock treatment (6 h, 37◦ C) of Arabidopsis WT plants resulted in much lower numbers (approximately tenfold) of differentially expressed genes (Rizhsky et al., 2004) compared to short-term (1 h, 37◦ C) heat stress (Busch et al., 2005). This discrepancy between expressionproﬁling data may be attributed to differences in the duration of heat stress. After short-term heat stress the proﬁling registers the fast, transient changes in the expression of many genes, whereas long-term heat stress may lead to an adjustment of the steady-state levels of mRNAs to control levels for a large number of transiently up- or downregulated genes. Thus, short-term heat stress may cover with a higher probability the primary HSF target genes, whereas long-term heat stress may have the potential to represent secondary target genes. Proteome and transcriptome analysis of knockout mutations in HSF-dependent HSF genes as, for example, AtHsfB1, -B2a, and -A7awill be required to clearly discriminate between primaryand secondary-level HSF target genes and functions.

12.1.7

Common stress-response genes and pathways

Several genes encoding enzymes involved in galactinol and RFO (rafﬁnose family of oligosaccharides) synthesis were identiﬁed as heat stress and HSF dependent (Busch et al., 2005). The expression of two enzymes, myoinositol-1-phosphatesynthase and galactinol synthase, belonging to this biosynthetic pathway, are also induced by other stresses. Myoinositol-1-phosphate-synthase is also induced by cold, drought, and salt stress in Arabidopsis (Kreps et al., 2002) and was found to be related to salt stress response and osmoprotection in the halophyte Mesembryanthemum crystallinum (Ishitani et al., 1996). Members of the galactinol synthase (GolS) gene family were also upregulated in response to different environmental stresses (Taji et al., 2002). Enhanced levels of galactinol and rafﬁnose, generated in leaves of transgenic plants by overexpression of GolS2, correlated with improved drought tolerance of Arabidopsis (Taji et al., 2002). The HSF-dependent expression of GolS1 correlates with an increase in the level of RFO, and knockout mutations of GolS1 are unable to accumulate stress-induced galactinol and rafﬁnose levels in leaves (Panikulangara et al., 2004). It has been shown that GolS1 and GolS2 genes are induced by drought and high salinity stress but the expression does not

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seem to be regulated by the drought transcription factor DREB (Taji et al., 2002). It is conceivable that HSFs may integrate different signaling pathways that lead to the expression of GolS1. The expression/function of these genes overlaps between different environmental responses that require protection by osmoprotective solutes. A new viewpoint regarding metabolic mechanisms of plant adaptation to thermal stress comes from a recent metabolite-proﬁling analysis by Kaplan et al. (2004). Using gas chromatography–mass spectrometry, a number of known and unknown metabolites were identiﬁed to be inﬂuenced by temperature stress; apart from a few stress-speciﬁc metabolites identiﬁed, interestingly, a majority of the heat stress metabolites overlapped with the cold stress metabolite proﬁles, thus uncovering common responses between high- and low- temperature stresses.

12.2 12.2.1

Cold stress Introduction

Low-temperature stress is one of the major stresses plants are exposed to in the environment. Different plant species have different abilities to tolerate cold stress. Many plants grown in tropical regions, like tomato, maize, and rice, are unable to tolerate temperatures below 10◦ C. Many other herbaceous plants from moderate climatic regions, depending on the species, are able to survive freezing temperatures as low as –30◦ C. However, plants can become acclimated to withstand low or freezing temperatures by exposing them for a short period to low nonlethal temperatures. This phenomenon to survive a normally lethal temperature is known as cold acclimation or acquired chilling or freezing tolerance (Guy, 1990; Thomashow, 1998). For instance, wheat plants grown at normal temperature are killed at a temperature around –5◦ C but can survive freezing temperature as low as –20◦ C after being cold acclimated; nonacclimated rye is killed at about –5◦ C, whereas cold-acclimated plants can withstand temperatures dropping down to −30◦ C; Arabidopsis plants grown at normal temperature are killed at –3◦ C, but after acclimation at 4◦ C (day) and 2◦ C (night) cycle for 5 days, plants can survive –7◦ C (Gilmour et al., 1988; L˚ang et al., 1994). Upon exposure to low-temperature stress, plants immediately pursue genetic programs to protect them from damage. The cascade of events starts with perception of stress, transduction of signals leading ultimately to the induction/expression of genes/proteins involved in protection of cells. In addition, biochemical changes occur, which may be involved in the perception of stress and initiation of signaling events.

12.2.2

Low-temperature sensing and signaling

The mechanisms by which low-temperature signals are perceived and transduced into biochemical responses are not completely understood. The model sketched in Figure 12.2 integrates the current knowledge about sensing and signaling of the

Figure 12.2 Regulatory network of cold stress response in plants. Octagonal boxes represent the transcription factors, and open bars promoter-binding elements of genes. ABA, abscisic acid; bZIP, a family of transcription factors with basic region and leucine zipper motif; CBF, CRT-binding factor; CDPK, calcium-dependent protein kinase; COR, cold-regulated genes; CRT, cold-response elements; DRE, dehydration-responsive elements; DREB, DRE-binding factors; ESK1, Eskimo 1 protein; HOS1, high expression of osmotically responsive genes 1; ICE, inducer of CBF expression; ICEr1 and r2, inducer of CBF expression region 1 and 2; KIN, kalt (cold) induced gene; MEKK1, MAPK kinase kinase 1 or ERK kinase kinase 1; MKK2, MAPK kinase 2; MPK4/6, MAP kinase 4/6; MYB, transcription factors with tryptophan cluster motif; MYC, transcription factors with basic-helix-loop-helix (bHLH) and leucine zipper motif; RAB18, response to abscisic acid 18; RAP2.1/2.6, related to AP2 transcription factor; RAV1, related to ABI3/VP1 transcription factor; SFR6, sensitive to freezing 6; ZAT12, zinc-ﬁnger protein 12; ?, unknown factors/regulators.

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cold stress response. Current models suggest that low temperature may be perceived directly via membrane-bound receptors, which sense biochemical changes, or indirectly by biochemical changes that result from dehydration, which subsequently activate an osmosensor. In both cases sensing and signaling require biochemical changes and the regulation of receptor protein activity. To date, no membranebound cold stress receptors have been identiﬁed in plants. An early response, when plants are exposed to low temperature, is a decrease in membrane ﬂuidity and coldinduced calcium inﬂux, followed by secondary responses in which calcium and cold-regulated (COR) protein kinases and phosphatases are believed to be involved (Monroy et al., 1998). In alfalfa, Ovar et al. (2000) showed that subsets of coldresponsive genes can be induced by chemicals that alter the membrane ﬂuidity, and that cytoskeletal reorganization occurs, which may be linked to membrane rigidiﬁcation and calcium inﬂux in response to cold. The calcium concentration in the cell increases due to an inﬂux of Ca2+ through the plasma membrane and by Ca2+ release from the vacuole (Knight et al., 1996). The magnitude of Ca2+ inﬂux correlated with the rate of temperature change in Arabidopsis (Plieth et al., 1999). The phytohormone abscisic acid (ABA) is involved in a second mechanism in cold sensing/signaling. In Arabidopsis the levels of ABA increase transiently during the ﬁrst day of cold treatment and thereafter decline gradually (L˚ang et al., 1994). The role of ABA in cold signaling is conﬁrmed by the fact that many cold-responsive genes are induced by external application of ABA (Thomashow, 1994). Another highly conserved stress-signaling mechanism among eukaryotes works via the activation of the mitogen-activated protein (MAP) kinase cascade. The cascade consists of three subsequently acting protein kinases, namely, MAP kinase kinase kinase (MAPKKK), MAP kinase kinase (MAPKK), and ﬁnally MAP kinase (MAPK). There have been indications of MAPK cascade being involved in mediating cold stress tolerance in plants, but upstream components of the cascade have not been identiﬁed. A cold-activated MAPK was demonstrated by Jonak et al. (1996) in alfalfa. In the Arabidopsis genome there are more than 60 putative MAPKKK, 10 MAPKK, and 20 MAPK. Out of the 20 MAPK, AtMPK3, AtMPK4, and AtMPK6 were induced by cold and a number of other stresses (Mizoguchi et al., 1996; Ichimura et al., 2000), and AtMKK2 was induced by cold and salt stress (Teige et al., 2004). Using yeast two-hybrid analysis and in vivo protein kinase assay it was shown that MKK2 directly targets MPK4 and MPK6 MAPK, respectively. MKK2-overexpressing transgenic Arabidopsis plants exhibited increased freezing and salt tolerance and showed enhanced expression of cold and salt stress marker genes including the transcription factors RAV1, CRT/DRE binding factor 2 (CBF2), CBF3, FAD8 (chloroplast-localized fatty-acid desaturase), and P5CS ( pyrroline5-carboxylate synthase). The roles of calcium as a messenger in response to cold and freezing acclimation are linked to the activity of calcium-dependent Ser/Thr protein kinases (CDPK), which are believed to participate in signal transduction. An increase in CDPK transcript levels in response to low temperature or other abiotic stresses has been reported for different plant species. The transcript levels of two CDPKs are differentially regulated by low temperature in alfalfa (Monroy and Dhindsa, 1995), and in rice CDPK

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RNA levels increase in response to cold and salt stress (Saijo et al., 1998). Overexpression of OsCDPK7 from rice confers both cold- and salt tolerance in rice (Saijo et al., 2000). In rice, a 12–18-h cold treatment activates a 56-kD membrane-bound CDPK, indicating that this enzyme is involved in late but not in the early events of the cold-adaptive response (Mart´ın and Busconi, 2001). Downstream components of this signaling path have still to be identiﬁed. In summary, the COR gene expression (the key to cold acclimation or freezing tolerance) is mediated through multiple pathways. The signaling pathway follows into two major routes: (1) calcium and CBF/DREB transcription factor dependent and (2) ABA mediated and bZIP, MYC, and MYB transcription factor dependent. Less well investigated are pathways involving other transcription factors like (3) RAV1 and ZAT12, and (4) ESK1. 1. In the ABA-independent signaling pathway, following perception of cold stress signal, a MYC-like basic helix-loop-helix transcription activator ICE (inducer of CBF expression), which is present in an inactive state at normal temperature, becomes activated for binding to the ICE box (CANNTG) in the promoter region of CBF3/DREB1a transcription factor gene (Gilmour et al., 1998; Chinnusamy et al., 2003). Following expression of CBF3/DREB1 the factor binds to the cis-element CRT/DRE (CCGAC) of the cold-responsive target genes, e.g., COR, KIN, and RAB18, which stimulates their transcription and expression. Further insight into the CBF-mediated induction of the cold-responsive genes was obtained from transcriptome analysis using CBF-overexpressing transgenic Arabidopsis plants (Fowler and Thomashow, 2002). In these plants the transcripts of RAP2.1 and RAP2.6 transcription factors are also upregulated, suggesting that they are also targets of CBF. These factors seem to act upstream of other cold-responsive genes as indicated by an involvement in COR gene expression. Only RAP2.1 contains the C-repeat/dehydration-responsive element (CRT/DRE) sequences in the promoter region, but the exact mechanism of expression and role in transcription are yet unknown. 2. The ABA-affected regulation of cold-responsive genes can be mediated through the activation of either CBF4/DREB1D or bZIP, MYC, and MYB transcription factors. The latter group of factors do not bind to the CRT/DRE sequences but recognize other sequences like the ABA response elements (ABRE) or the MYC/MYB-binding sites in the promoter region of the target genes. 3. An involvement of other pathways in cold stress response was indicated by results from transcriptome analysis (Fowler and Thomashow, 2002). Transcripts of cold-induced genes like the CBF2, RAV1, and ZAT12 appear at the same time (after 1 h of cold stress). Thus, they could be acting in parallel. ZAT12 and CBF2 seem to control partially overlapping sets of target genes. Overexpression of ZAT12 led to a downregulation of the CBF genes, indicating its role as a negative effector of CBF in the cold-response pathway (Vogel et al., 2005).

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4. Another CBF-independent pathway was identiﬁed in the esk1 (ESKIMO1) mutants in Arabidopsis. These mutants are constitutively freezing tolerant but the expression of genes with CRE/DRT sequences is not altered. This suggests that at least partial freezing tolerance can be achieved in a CBFindependent manner through ESK1 (Xin and Browse, 1998). Genetic screens have led to the identiﬁcation of other regulators of cold signal transduction. The hos1 (high expression of osmotically responsive genes) mutant was isolated after EMS mutagenesis of transgenic Arabidopsis plants carrying a COR promoter of RD29A fused to luciferase reporter gene (Ishitani et al., 1998). The hos1 mutant shows enhanced cold induction of CBF and cold-responsive genes. The gene encodes a RING-ﬁnger protein, and it was proposed that HOS1 acts as a negative regulator by targeting the positive regulators of CBF for ubiquitination and degradation (Lee et al., 2001). Other regulators identiﬁed via mutant screening are LOS1 (low expression of osmotically responsive gene 1) and LOS2 (low expression of osmotically responsive gene 2), encoding translation elongation factor 2 and a bifunctional enolase, respectively (Ishitani et al., 1997). Guo et al. (2002) found that in the los1 mutant CBF transcripts are highly induced in response to cold but the expression of the target genes bearing CRT/DRE sequences was blocked. Similarly the los2 mutants are also affected in the downstream target genes bearing the CRT/DRE sequences, suggesting that the LOS2 protein may function in the expression of delayed coldresponsive genes by transcriptional repression of ZAT10 (Lee et al., 2002). The Arabidopsis mutant sfr6 (sensitive to freezing), identiﬁed in a screen by Warren et al. (1996) and characterized by Knight et al. (1999), shows a lower expression of the COR genes containing CRT/DRE promoter elements. However, SFR6 was not involved in the regulation of CBF expression. At present it is not possible to draw a complete picture of the regulatory network in cold stress signaling. Further genetic, proteome, transcriptome, metabolome, and protein interaction analyses are required for gaining deeper insights into this complex stress-response system.

12.2.3

Transcription factors in ABA-independent pathways

Transcription factors involved in ABA-independent cold regulation were identiﬁed by the binding of proteins to the CRT/DRE sequences present in the promoters of COR genes (Stockinger et al., 1997). This led to the identiﬁcation of CBF1 (CRT/DRE binding factor 1) in Arabidopsis, which is present on chromosome 4 along with two other CBF genes organized in direct repetition (Gilmour et al., 1998). The transcript levels of all three CBF genes increase within 15 min in response to low temperature; thereafter, within 2 h, the transcripts of COR target genes accumulate (Gilmour et al., 1998). Transgenic overexpression of CBF1 in Arabidopsis led to the induction of multiple COR genes at nonacclimating temperatures and enhanced freezing tolerance of these plants (Jaglo-Ottosen et al., 1998), suggesting that CBF1 is the key regulator of COR gene expression leading to freezing tolerance.

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CBF1–3, synonymously designated DREB1b, DREB1c, and DREB1a, respectively (Liu et al., 1998), possess at the N-terminus a putative NLS signal, an AP2 DBD, and a C-terminal acidic region, which speciﬁes an activation domain (Stockinger et al., 1997; Gilmour et al., 1998). It was shown that the N-terminal 115 amino acids of CBF are necessary to direct the protein to the target genes and the C-terminal 98 amino acids are necessary for trans-activation of transcription (Wang et al., 2005). Within the activation domain four amino acid motifs (clusters of hydrophobic residues delimited from one another by small stretches of Asp, Glu, Pro, and other residues) were identiﬁed, which play a role in transcriptional activation. CBF orthologs have been isolated and studied in other plant species. Lycopersicum esculentum harbors three CBF genes (LeCBF1–3) arranged in tandem array, but only LeCBF1 is low temperature induced (Zhang et al., 2004). Constitutive overexpression of LeCBF1 in transgenic Arabidopsis led to the accumulation of the COR genes and enhanced freezing tolerance. In a closely related species, Brassica napus, four orthologs of Arabidopsis CBF/DREB transcription factors BNCBF-5, -7, -16, and -17 have been identiﬁed (Jaglo et al., 2001; Gao et al., 2002). The structures of BNCBF-5, -7, and -16 are very similar to Arabidopsis CBF1 but BNCBF17 contains two extra regions of 16 and 21 amino acids in the acidic activation domain (Gao et al., 2002). The transcripts of all genes were cold induced, but the mRNA of BNCBF17 was short lived. Library screening of two distant species, rye (Secale cereale) and wheat (Triticum aestivum), led to the identiﬁcation of cDNA clones, sharing 30 and 34% sequence similarity within the AP2 DBD of Arabidopsis CBF (Jaglo et al., 2001). A striking feature observed by the alignment of Arabidopsis, B. napus, S. cereale, T. aestivum, and L. esculentum sequences was the presence of short signature sequences PKK/RPAGRxKFxETRHP located immediately upstream of the AP2 DBD and the sequence motif DSAWR just downstream of the AP2 domain (Jaglo et al., 2001). These structural characteristics distinguish CBF from the other 140 or more AP2/EREBP proteins in Arabidopsis. Since the expression of CBF is induced by low temperature, Gilmour et al. (1998) proposed a cold-activated regulator acting upstream of CBF. Chinnusamy et al. (2003) carried out a genetic screen for regulators of CBF/DREB expression. Transgenic Arabidopsis plants bearing CBF3 promoter::luciferase (CBF3-LUC) constructs were chemically mutagenized and mutants with altered CBF3-LUC expression in response to cold were isolated. The mutant ice1 was impaired in CBF3LUC activity and cold acclimation. ICE1 encodes a MYC-like bHLH transcription factor binding to the MYC recognition elements in the promoter of CBF3 (Chinnusamy et al., 2003). Until recently the possibility that CBFs regulate their own expression was ruled out by two criteria: (i) the promoter regions of CBF1–3 lack the CRT/DRE-binding sequences and (ii) CBF1-overexpressing Arabidopsis has no inﬂuence on the expression of the other CBFs (Jaglo-Ottosen et al., 1998). However, Novillo et al. (2004) isolated an Arabidopsis T-DNA insertion in the CBF2/DREB1c gene. The cbf2 mutant showed enhanced transcript levels of the two other cold-induced CBFs at control temperatures and improved tolerance to freezing, dehydration, and salt stress. Hence, CBF2 may be a negative regulator of the other CBF/DREB (CBF1/DREB1b and CBF3/DREB1a) genes.

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In nature, multiple environmental factors are involved in governing a stress response. The work of Harmer et al. (2000) and Fowler et al. (2005) showed that both low temperature and circadian rhythm affect induction of CBF/DREB transcription factors. Other transcription factors like RAV1 and ZAT12, induced in parallel, were also subject to circadian regulation (Fowler et al., 2005). In addition to cold, CBF1–3 expression was also induced by mechanical agitation (Gilmour et al., 1998), ABA (Knight et al., 2004), and inhibition of protein synthesis (Zarka et al., 2003).

12.2.4

Transcription factors in ABA-dependent pathways

The ABA-dependent expression of cold-responsive genes is mediated by transcription factors of the bZIP, MYB, and MYC families, which recognize speciﬁc elements in the promoter of target genes. These transcription factors are known to respond to stresses like cold, dehydration, and exogenous application of ABA in plants like rice, maize, and Arabidopsis (Kusano et al., 1995; Lu et al., 1996; Nakagawa et al., 1996; Abe et al., 2003). Another ABA-independent induction of the COR genes is regulated by RAV1 and ZAT12 transcription factors. The transcription factor RAV1 (related to ABI3/VP1) has two distinct DBDs, the N-terminus is homologous to the AP2 DBD present in APETALA2 transcription factor and the C-terminus designated as B3 is homologous to that of ABI3/VP1 transcription factor. The two DBDs were shown to bind two unrelated sequences, CAACA and CACCTG, to achieve higher afﬁnity and speciﬁcity to binding (Kagaya et al., 1999). Six proteins of this family have been identiﬁed in Arabidopsis (Riechmann et al., 2000). ZAT12 is a zinc-ﬁnger protein that seems to be involved in the regulation of CBF genes. The involvement of RAV1 and ZAT12 in cold stress was suggested by transcriptome analysis (Fowler and Thomashow, 2002). Data of Rizhsky et al. (2004) implicated a role of ZAT12 in oxidative stress response. Recent transcriptome analysis (Vogel et al., 2005) showed that CBF2 and ZAT12 share a number of the highly induced putative target genes. Constitutive overexpression of ZAT12 in Arabidopsis caused a small increase in freezing tolerance, indicating its role in cold acclimation. Transcription factors of the RAP2 (related to AP2) family were identiﬁed as putative regulators, by transcriptome analysis of CBF-overexpressing Arabidopsis plants (Fowler and Thomashow, 2002). Members of this family (12 genes in Arabidopsis) are differently expressed in different tissues and AP2 seems to contribute to their expression throughout development (Okamuro et al., 1997). The exact role/function of two of these transcription factors (RAP2.1 and RAP2.6) in cold stress is not known.

12.2.5

Cold stress target genes

Genes expressed in response to cold are synonymously designated as cold-regulated genes (COR), or low temperature induced (LTI), or cold inducible (KIN), or early dehydration responsible (ERD) in different publications. These genes contain one

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or more binding sequences for transcription factors in the promoter regions. In the ABA-independent pathway, the expression of target genes is mediated by one or more CBF/DREB-binding sites (CRT/DRE) with the core sequence A/GCCGAC (Yamaguchi-Shinozaki and Shinozaki, 1994; Stockinger et al., 1997; Sakuma et al., 2002). In the ABA-dependent pathway, bZIP transcription factors bind to the ABRE consensus sequences ACGTGGC (Busk et al., 1997; Hobo et al., 1999; Zhu, 2002) and to the less conserved coupling elements (CE) with the core ACGT. Other ABA dependently expressed genes are targets of the MYB and MYC transcription factors. The recognition sites in the promoters of target genes are TGGTTAG and CACATG respectively (Abe et al., 1997, 2003). The knowledge about how cold-response target genes contribute to the attainment of cold/freezing tolerance is scant. From the group of CBF/DREB-controlled COR genes like KIN1, COR6.6/KIN2, COR15a, COR47/RD17, COR78/RD29a, and ERD10,−6,−9, the mode of action has been studied only for COR15a. Evidence came from the work of Artus et al. (1996), who showed that the constitutive expression of COR15a (COR15am) in Arabidopsis enhanced freezing tolerance of chloroplast (in vivo) and protoplasts (in vitro) in nonacclimated plants. As a result of freeze-induced dehydration the plasma membrane comes in close apposition with the chloroplast envelope; COR15am protein decreases the transition of lamellar to hexagonal II phase lipids (caused usually as a result of cold-induced dehydration) in these regions and alters the intrinsic curvature of the inner membrane of the chloroplast envelope (Steponkus et al., 1998). Increase in cold/freezing tolerance is not caused only by the action of COR proteins but also due to an increase in metabolite/sugar levels. CBF3-overexpressing plants, which are freezing tolerant, show in addition to the elevated levels of COR gene expression also increased amounts of proline and total sugars (Gilmour et al., 2000). The eskimo1 mutant (Xin and Browse, 1998) of Arabidopsis, which is also freezing tolerant, accumulates enormous amounts of proline. Proline is well known as a stress-dependent substance involved in freezing and salt tolerance, as for example demonstrated by antisense plants for proline dehydrogenase (AtProDH) (Nanjo et al., 1999). It is not shown but thought that the role of sugars, in part, might be to stabilize the membranes. Maruyama et al. (2004) grouped genes on the basis of expression level with respect to the duration of stress applied. Genes belonging to class I show increased expression within 5 h and reach a maximum level at 10 or 24 h (these include a few known DREB1A target genes like rd29A, cor15a, cor15b, kin1, kin2, erd10, rd17, AtGolS3, RAP2.1, erd7, and genes of unknown function). Class II genes are induced within 2 h and reach their highest expression at 5 h (DREB1A transcription factor); class III includes genes that are induced gradually up to 24 h (AtGRP7, AtPlc1, and genes of unknown function). Recently, microarray expression proﬁling became a useful tool in the analysis of cold stress response (a) to obtain a broader picture on the expression patterns of genes in response to different abiotic or biotic stresses; (b) to identify downstream targets of stress-responsive transcription factors; and (c) to study the regulatory network that crosstalks during stress. So far the method has been exploited to obtain new

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cold-responsive genes and other potential targets of CBF/DREB1 transcription factors. A number of microarrays using cDNA prepared from Arabidopsis grown under stress conditions like cold, drought, and salt, as well as from normal temperature grown CBF/DREB-overexpressing transgenic Arabidopsis plants (Seki et al., 2001; Fowler and Thomashow, 2002; Seki et al., 2002; Maruyama et al., 2004), have contributed to the identiﬁcation and categorization of COR genes that include (1) transcription factors, (2) late-embryogenesis-abundant (LEA) proteins, (3) PI metabolism, (4) KIN proteins, (5) RNA-binding proteins, (6) transport proteins, (7) hydrophilic proteins, (8) desaturases, (9) metabolic enzymes, (10) senescencerelated proteins, and many proteins with unknown function supporting earlier ﬁndings by Guy (1990), Mohapatra et al. (1989), and Thomashow (1999). Conﬁrmation of the existence of regulatory pathways distinct from CBF/DREB-dependent expression of genes is implicated by the observation that 28% of the cold-responsive genes and 15 transcription factors are obviously not regulated by the CBF/DREB.

12.3

Perspectives for plant biotechnology

In the natural environment, extreme temperatures, drought, salinity, and oxidative stress are often interconnected and cause common detrimental effects on plant growth and yield. As a consequence, diverse environmental stresses often activate similar cell signaling pathways and cellular responses. It should be noted that abiotic stress is the major cause for reducing the efﬁcient exploitation of the genetic potential for yield in crop plants worldwide (Boyer, 1982; Bray et al., 2000). Thus, the improvement of stress tolerance is an important goal in plant biotechnology-assisted breeding. The overlap in the responses between cold and drought and, to a lesser extent, between heat and drought stress responses implicates that the genetic manipulations may have a great potential to improve common stress tolerance. At present the most suitable targets for genetic engineering of stress tolerance are transcription factors because they are responsible for coordinating the expression of whole sets of target genes. Transgenic overexpression of transcription factors involved in the expression of heat- or cold-regulated genes has been successfully used for generating plants having improved basal tolerance to heat or drought and cold respectively. For example, overexpression of CBF/DREB factors resulted in a constitutive expression of COR genes and in improved cold/drought tolerance in Arabidopsis (Jaglo-Ottoson et al., 1998; Kasuga et al., 1999). However, a strong, S35-promoter-driven overexpression of DREB was associated with a dwarf phenotype of transgenic plants. This ﬁnding suggests that the native response system has two functions: (i) upregulation of genes, which are required for cellular protection from harmful effects, and (i) downregulation of genes, which are involved in growth and development. In CBF/DREBtransgenic Arabidopsis plants the growth effect problem could be partially solved by using inducible promoter constructs that limit the level of CBF/DREB overexpression or by treating plants with gibberellic acid.

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On the other hand transgenic overexpression of AtHSF1 and AtHSF3, respectively, in Arabidopsis plants resulted in constitutive expression of stress genes and enhanced basal thermotolerance (Lee et al., 1995; Pr¨andl et al., 1998). Interestingly, transgenic tomato plants overexpressing AtHSF3 (AtHSF1b) also showed a constitutive expression of different HSPs and an improved chilling tolerance (Li et al., 2003). However, HSF overexpression appears to become unstable with time in subsequent generations, possibly by homeostatic adjustments, gene-silencing effects, and/or counterselection under nonstress conditions (unpublished observations). The gain-of-function effects of transgenic overexpression of HSFs were very surprising, since several of the native transcription factors, for example HSF1 and HSF3, are constitutive proteins in WT where they require stress signals to become activated for target gene binding and/or initiation of transcription. There is no general answer to explain this phenomenon but it seems that overexpression of transcription factors shifts the equilibrium between the inactive and active forms of these transcription factors, possibly by a titration of their negative feedback regulators. There is evidence that HSP70 is involved in the regulation of HSF activity (Lee et al., 1986; Kim et al., 2002). Thus, the real target of genetic engineering may be the metastable HSF complexes whose activation depends on the balance between HSF and its negative regulators. Such complexes may act as cellular sensors for such environmental stresses, which cause a depletion of free chaperons by increasing the load of denatured proteins. The heat- and cold stress response systems and molecular mechanisms appear to be conserved in plants, and it seems possible to use the regulatory genes/proteins identiﬁed in one species for successful genetic engineering in another species. Transgenic expression of Arabidopsis CBF/DREB in tobacco or B. napus plants resulted in a constitutive expression of putative target genes and cold/drought stress gene expression and caused enhanced stress tolerance (Jaglo et al., 2001; Kasuga et al., 2004). Overexpression of the tomato CBF1 homolog had the same effect upon heterologous expression in Arabidopsis, but interestingly, stress tolerance was not improved when the tomato CBF was overexpressed in tomato plants (Zhang et al., 2004). This shows that the mechanisms of stress-response regulation are conserved in plants but not necessarily the sets of downstream target genes, which seem to differ between cold-acclimated species (Arabidopsis) and tomato, which cannot acclimate to cold. On the other hand the molecular mechanisms and functions in stress tolerance seem to be conserved between mono- and dicotyledonous plants. Rice DREB/CBF homologs function in a similar way in rice and transgenic Arabidopsis (Dobouzet et al., 2003; Oh et al., 2005). While many transgenic crops have been already commercialized, only a few stress-resistant transgenic crops have been moved from the laboratory to the ﬁeld for evaluation under natural stress conditions (Dunwell, 2000). To date, most of the genetically modiﬁed stress-tolerant plants are nonagronomic plants, and it will take some time until the knowledge gained from model plants has been successfully converted into useful stress-tolerant crops.

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13 Applications of inducible transcription in plant research and biotechnology Brian Tomsett, Angela Tregova and Mark Caddick

13.1

Introduction

Functional genomics is the key to our understanding of plants and their interactions in the environment. Analysis of plant genomes has revealed an amazing complexity, including a signiﬁcant proportion of sequences that are classiﬁed as having an ‘unknown function’. Even if the general class of function can be guessed, the degree of apparent redundancy among multi-gene families is such that their exact role requires investigation – are they functional in different cell types, different stages of development or in response to different environmental cues/stresses, etc.? The absolute deﬁnition of function for any gene, encompassing all possible epistatic or pleiotropic effects in all tissues and at all stages of development, requires analysis through transgenic plants. For this, transcriptionally regulated expression systems are a necessary component of the plant functional genomics tool kit. Most research using transgenic plants utilises constitutive promoters to direct expression at maximal rate in all tissues of the plant. For genotypically dominant markers, the phenotype is visible immediately. For recessive characters, selﬁng the plant can produce homozygous, hemizygous and azygous progeny to explore all possible interactions. However, for some genes, there can be signiﬁcant complications. Aberrant expression can disrupt normal function, for example by triggering embryo lethality or senescence, or by preventing meiosis, leading to sterility. Furthermore, deleterious effects at an early stage of development may mask a more subtle phenotype later in the life cycle. Inducible expression systems provide the ability to upregulate or downregulate one or more genes temporally, i.e. at a deﬁned time in growth or development, minimising such problems. While this chapter ranges broadly across this topic of inducible expression systems in plants, it cannot be exhaustive, since there is much current activity and even greater potential for both its development and its application. It includes an overview of inducible transgene expression systems, and then examines some examples of their use in plant functional genomics and plant biotechnology.

13.2

Conditional expression of transgenes

There have been a series of excellent reviews dedicated to this topic, which have examined in detail the mechanisms of inducible expression systems (Gatz, 1996,

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1997; Gatz and Lenk, 1998; Zuo and Chua, 2000; Padidam, 2003; Wang et al., 2003; Tang et al., 2004). Here, we attempt to draw together principles and options in relation to their beneﬁts, limitations and applications. As we will show, there is no ‘perfect’ system for conditional expression, and careful consideration is necessary to achieve satisfactory results. Furthermore, as we point out below, research and biotechnology are moving into a phase where we need multiple approaches, and so several of the systems described here will need to be used in conjunction.

13.2.1

The principles of regulated expression

Transcription is a process involving a complex of molecules acting in a concerted fashion to deliver an RNA transcript of deﬁned length and sequence. For some genes related to core housekeeping functions, expression will be constitutive – all cells, at all times. For many genes however, their promoter and enhancer sequences combine to precisely deﬁne expression levels for a speciﬁc cell type under speciﬁc conditions. Thus, expression could be controlled by signals for differentiation or development (speciﬁc cell types, tissues or organs; e.g. meristems), spatially (cells in deﬁned positions, and not similar cells in other locations; e.g. abscission zones), temporally (all cells at some times and not others; e.g. circadian clock genes) or in response to stimuli from the environment (abiotic or biotic stress; e.g. excess salt or pathogen attack). Potentially, any regulated promoter could be adapted for the conditional expression of a transgene. For some applications, an endogenous plant promoter will be the obvious choice, particularly where it is desirable to coordinate the expression of the transgene with that of a native gene and any corresponding cellular activity, while in others there may be a requirement to control expression entirely artiﬁcially. Either way, the principles will be similar. The regulation of transcription can be positive or negative. Negative regulatory circuits rely upon the production of a molecule that prevents transcription, for example by blocking the binding or destabilising the transcription initiation complex. A target gene is thus repressed until such time as an effector molecule interacts with the repressor to unblock transcription, referred to as de-repression. In positive-regulated systems, the promoter of the target gene remains quiescent until an activated regulatory protein stimulates transcription. In some cases, the inactive regulatory protein could be bound to the promoter/enhancer region of the target gene but not direct transcription until activated by the effector molecule. In others, the interaction of an effector ligand with the regulatory protein stimulates binding to the promoter and/or enhancer elements, and directly or indirectly promotes formation of the transcription initiation complex.

13.2.2

Generic mechanisms

The construction of all inducible expression systems relies upon a series of essential elements that will differ slightly, depending on the basis for the regulation (Figure 13.1). Whether positive or negative regulation is employed, the heart of the

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Figure 13.1 Generic mechanisms for conditional regulation of transcription. (R = the regulator gene and its protein product; TG = a transgene whose protein product is signiﬁed by ; RP = a reporter gene, which produces a product ; pR = is the promoter directing expression of the regulatory gene; pA = the promoter regulated by protein R and the inducer (I), which can be used for the expression of any transgene, a reporter gene, or both; t1, t2 and t3 = transcriptional terminator sequences for the three gene constructs, which should preferably be different.)

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system will be a regulatory protein (R) that binds to sequences associated with a promoter capable of activation (pA). In endogenous (single-component) systems, the regulatory protein is the product of a native gene within the host’s genome that is part of a regulatory mechanism responding to an internal or external stimulus (the inducer, I); a single transgene driven by pA will respond in the same manner as other genes in the circuit. In heterologous (two-component) systems, two transgenes will be required, one to produce a regulatory protein that responds to an inducer (I), the other being the gene of interest driven by pA. In the development of ‘gene switches’, reporter genes (RP) have been the transgenes of choice to determine the parameters of expression, including chloramphenicol acetyltransferase (CAT), glucuronidase (GUS), luciferase (LUC) and green ﬂuorescent protein (GFP). In two-component systems, expression of the regulatory protein must be considered. In most studies to date, the promoter (pR) directing the expression of the regulator has been a constitutive promoter, delivering high levels in all tissues, often the Cauliﬂower Mosaic Virus (CaMV) 35S promoter. In part, this has been to ensure that sufﬁcient amounts of regulatory protein would be available to ensure maximal induced expression. However, other options may be more favourable to optimise expression of a speciﬁc gene and to reduce background levels of expression. The structure of the regulatory protein and pA will depend on the system used. Proteins activating transcription generally require at least three major domains: a DNA-binding domain that recognises deﬁned sequences within the target promoter; a transactivation domain for efﬁcient transcription; and a ligand-binding domain that binds the molecule triggering a conformational change to initiate expression (see Tyagi, 2001). A speciﬁc regulatory protein may be utilised, but the modular nature of many transcription factors has meant that synthetic/chimeric regulatory proteins can be developed combining three domains from different genes. Similarly, in some systems, pA will be a native promoter from a characterised gene, containing appropriate response elements; in others, it will be an artiﬁcial construct containing plant promoter sequences, required to allow the initiation of transcription by the complex containing RNA polymerase, together with response elements that bind the speciﬁc regulatory protein that will in turn either repress or activate transcription. For inducible promoters, a minimal promoter, most often from the CaMV 35S promoter, can direct expression only when a regulatory protein containing an activation domain is bound to an adjacent response element. The ﬁnal component of any transgene is the terminator sequence. Most constructs use an ∼200–300-bp sequence from a well-characterised gene (e.g. from 35S RNA of CaMV, or the nos gene of the T-DNA of Agrobacterium tumefaciens); this positions a polyadenylation signal downstream of the ﬁnal translation stop codon to ensure that a mature and stable mRNA is produced.

13.2.3

Physical stimuli for activation

Recognition of physical stimuli relies upon the native responses of the host plant, and hence the regulatory protein will be an endogenous gene in the host genome. Those currently used are all stress related and so come with the limitation that

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the plant may be exhibiting ‘abnormal’ (stress) physiology at the time of transgene expression. Here we review three approaches: heat-, wound- and pathogen-inducible expression. Heat-shock inducible promoters are triggered by an 8–12◦ C rise in temperature above the ‘normal’ ambient temperature of growth. The plant responds by inducing the transcription of a deﬁned set of genes, encoding the so-called heat-shock proteins (HSPs), while many other genes show decreased transcription. In an early study, Callis et al. (1988) introduced a construct in which the CAT reporter gene was transcribed from the maize hsp70 promoter in maize protoplasts. At 26◦ C, they detected very low CAT activity, but this increased a further 35-fold by 37◦ C, and 200-fold at 40◦ C. Simultaneous expression of a 35S-luc reporter showed an approximately threefold reduction in expression at 37◦ C relative to the 26◦ C level. As will be discussed below (Section 13.3), heat-inducible systems have been used successfully to express genes in whole plants. Plants have defence mechanisms that protect them against the invasion of competing organisms, part of which is a wounding response that alters the physiology of the cells and activates defence. They respond to wounding in several ways: by producing reactive oxygen species, phytoalexins, ethylene, pathogenesis-related (PR) proteins, methyljasmonate, systemin, abscissic acid, auxin and/or salicylic acid. Many of these also act as signalling molecules causing cascades of gene expression of subsets within the response. Furthermore, some pathogen-derived molecules also activate certain genes and trigger defence. The promoters of these genes are thus a potential route for the expression of transgenes in an inducible manner. An important consideration is that many such promoters are inducible by a number of stimuli, which can be advantageous or disadvantageous, depending on the purpose of transgene expression. For example, Sa et al. (2003) have used the GAFP-2 promoter from a Gastrodia elata antifungal protein gene to examine reporter gene activity in transgenic tobacco plants. There was a signiﬁcant basal level (uninduced) GUS activity that was higher in roots than in stems and leaves, and strongly localised to vascular tissues. Expression was increased up to tenfold upon induction by Trichoderma viride, or on application of jasmonic acid or salicylic acid. In a similar approach, Perera and Jones (2004) have examined expression driven from a peroxidase gene promoter from the tropical forage legume Stylosanthes humilis. In transgenic tobacco, chewing or sucking insects induced GUS/GFP expression in cells around the feeding sites, but wounding or methyljasmonate could also activate reporter gene activity. Physical stress, for example from heat or wounding, can induce gene expression but these may not be as convenient as a response triggered by the application of a chemical in easily controlled doses, at speciﬁc sites and at deﬁned times. Thus, even those laboratory studies employing pathogen/wound-inducible promoters, often use one of the chemical elicitors that underlie the response, namely methyljasmonate and salicylic acid. Yamada et al. (2002) suggested the pathogenesis-related protein 1a (PR1a) promoter could be used as a benzothiadiazole-inducible promoter. While they demonstrate its effectiveness, this raises questions about their widespread use, due to both the wide range of conditions that could induce expression and the range

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of native genes that will also respond to the speciﬁc stimulus. For most laboratory studies however, this may not matter.

13.2.4

Chemical activators related to plant metabolism

Chemical activators can be divided into those that are known to be part of the plant’s normal metabolism, and those that appear to be unrelated (which will be discussed in Section 13.2.5). It is also of importance here whether the regulator protein is native or heterologous. In some studies, a native regulatory protein serves to dissect the physiology/development of the plant under investigation. For example, an auxin-inducible reporter gene has been used to analyse auxin distribution in the moss Physcomitrella patens (Bierfreund et al., 2003). Here the endogenous inducer and the native regulatory protein were used to drive the expression from heterologous promoters, one synthetic and the other from soybean. In this instance, the native regulation was the focus of the study. However, for many transgenes, regulation is required under very deﬁned conditions, and hence isolation of expression is (partially) achieved by using a regulatory protein unrelated to the plant’s own transcription regulators, derived from another organism. Ideally these would respond to an inducer that is not normally present in plants nor induces a signiﬁcant response in the absence of the regulatory system. Two of the best characterised examples of this approach use fungal regulatory proteins that act positively on their responsive promoters. Mett et al. (1993) described a two-component copper-controlled gene expression system for plants, which was based upon the regulatory circuit of the yeast metallothionein gene. A transcription factor (ACE1) was expressed from the 35S promoter, which could activate transcription in the presence of copper ions from a chimeric promoter (pA) containing the metal responsive element (MRE) binding domain linked to a −90 minimal 35S promoter; GUS was used as the reporter. In transgenic tobacco, signiﬁcant pA-directed GUS expression occurred with copper concentrations >5 μM when applied to the root solution, and from foliar sprays with as little as 0.5 μM CuSO4 . Induction was up to 50-fold over the basal level. Given that copper is a normal component of the plant nutrient solution (∼0.1 μM), one might expect a high basal level of activity. However, uninduced levels of GUS were low. Furthermore, levels of GUS were similar in plants (±Cu) containing pA:GUS but lacking the regulatory transgene, as in untransformed controls, indicating that the promoter did not respond to an endogenous transcription factor. The regulation from this system can be tight (non-leaky) and hence despite copper being normally available in the environment, and readily taken up by the plant, the system has great utility for transgene expression (Mackenzie et al., 1998). Granger and Cyr (2001) have further demonstrated its utility in Arabidopsis thaliana grown in agar; expression in roots is highest in the root cap and epidermis, which may indicate a higher exposure to copper in the medium. Unfortunately, expression was not extensively analysed in the above-ground parts of the plants, and while GFP could be detected, the transport of GFP itself rather than the inducer (Cu) cannot be excluded. More recently, even higher levels of expression have been reported through a modiﬁcation to the MRE (Peng et al., 2003).

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One possible advantage to this system is that expression can be sustained for some considerable time, presumably because while copper ions may be sequestered away from the ACE1 protein, the turnover is not as rapid as in metabolite-based systems. Thus, a single application of 0.5 μM copper as a foliar spray led to GUS activity at high levels at day 4, and remained high until at least day 12, before declining by day 16 (Mett et al., 1993). Furthermore, a degree of reversibility was demonstrated after removal of surface copper by washing with water, which triggered a decline in activity to below 50% of the maximally induced activity 2 days later. Clearly, this system is not without its limitations. Symptoms of copper toxicity appeared at 20 and 15 days in response to 5-μM and 50-μM copper (respectively) being applied to the roots. This was not the case for foliar spraying at 0.5 μM. In addition, the utility of this system for tobacco cell culture has been questioned (Granger and Cyr, 2000). Another system is based upon the alc regulon of Aspergillus nidulans. The regulatory protein, AlcR, expressed constitutively using a plant promoter (generally 35S), binds to sites (derived from the alcohol dehydrogenase gene, alcA) in a chimeric promoter linked to a −31 minimal 35S promoter (Caddick et al., 1998; Salter et al., 1998). Transcription is activated by the presence of an effector ligand, either ethanol or acetaldehyde, and while some other compounds have been shown to trigger expression (e.g. 2-butanone, acetone and propan-1-ol), these are not generally as effective (Junker et al., 2003; Garoosi et al., 2005). Ethanol has been the most extensively studied inducer; expression is dose dependent and sufﬁciently sensitive that vapour can be used to activate expression (Roslan et al., 2001; Sweetman et al., 2002). The response is very rapid; for example, luciferase expression could be detected in the roots of A. thaliana seedlings within 1 h of ethanol addition (Roslan et al., 2001). Expression can be as high as an equivalent line carrying a 35S-driven transgene, and it peaks between 3 and 5 days postinduction, before declining (Salter et al., 1998; Garoosi et al., 2005). Expression can be sustained at a high level through the subsequent additions of inducer (Roslan et al., 2001; Schaarschmidt et al., 2004). Ethanol induction appears to give expression systemically throughout the plant, but some tissues have higher levels than others in mature plants (Garoosi et al., 2005). Application of acetaldehyde as an inducer has been demonstrated to give local induction (Schaarschmidt et al., 2004). The alc system is extremely effective for academic research and may have applicability to the ﬁeld because the inducers are metabolites that can be degraded in the plant, and by microbes in the soil. However, these metabolites occur in plants under deﬁned conditions. Hypoxia/anoxia leads to ethanolic fermentation, during which pyruvate is converted initially to acetaldehyde by pyruvate decarboxylase, which in turn is converted to ethanol by alcohol dehydrogenase (Drew, 1997). Artiﬁcial anoxia does induce alc, but a 3-day submergence of the root (but not aerial) systems of plants did not lead to induction (Salter et al., 1998; Roberts et al., 2005). However, seedlings grown in agar show higher basal levels of expression, and cells in both callus and suspension cultures have levels that are effectively constitutive (Roslan et al., 2001; Roberts et al., 2005). Since both copper and ethanol/acetaldehyde are part of the normal metabolism of the plant, it is inevitable that application of these compounds may change the

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physiology of the plant. The true extent of their effects has not been determined; however, an analysis of more than 60 metabolites in potato tubers revealed that ethanol treatment altered the levels of 13, but acetaldehyde induction affected only 3 (Junker et al., 2003). Clearly, this will not be critical for many studies, but should be considered prior to experimentation.

13.2.5

Chemical activators unrelated to plant metabolism

Given the potential problems associated with the use of an inducer or regulatory protein that is part of the normal plant repertoire, a number of heterologous and/or synthetic systems have been developed. Some of these rely upon regulatory elements from microbes, and others from animal systems. Initial interest stemmed from the negatively regulated tet (and lac) operon of enteric bacteria (see Gatz, 1997; Padidam, 2003). However, high levels of the repressor were required in the nucleus to maintain a low basal expression from the target transgene (David and Perrot-Rechenmann, 2001). But by combining the activation domain of the VP16 protein of human herpes simplex virus (HSV) with the DNA-binding domain of TetR, the chimeric regulatory protein bound to the tet operator sequences activated transcription in the absence of tetracycline, the addition of which prevented expression (Gossen and Bujard, 1992; Weinmann et al., 1994; Love et al., 2000, 2002). However, there have been reports of leakiness of the promoters (De Veylder et al., 2000), and methylation of the tet operator sequences (Bohner et al., 1999), both of which have been addressed during the development of a dual regulatory system discussed below. The key elements of the lac system have been used to deﬁne a novel hybrid transcriptional regulation system, termed pOp/LhG4 (Moore et al., 1998; Baroux et al., 2005). The pOp (=pA) consisted of two lac operators (2xRElac ) placed upstream of a minimal 35S promoter; a chimeric regulatory protein (LhG4) composed of a mutant DNA-binding domain from the Lac repressor (with increased binding efﬁciency) fused to the activation domain II from Gal4 of Saccharomyces cerevisiae. Unlike the other systems described in this section, this is not activated by a chemical; rather separate transgenic lines, one carrying the pOp-transgene and the other 35S-LhG4, are crossed to produce an F1 with excellent expression throughout the plant. While there is no temporal control here, as will be discussed below, it is perfectly stringent, and can be combined with spatial and/or chemically inducible systems. In an alternative approach, a number of groups have constructed chimeric transcription factors responsive to hormones from animal systems. Three groups have developed control systems based on the receptor for the insect hormone ecdysone (EcR) because of its potential for ﬁeld application. Martinez et al. (1999) constructed a chimeric GVE regulatory protein using the DNA-binding domain and activation domain of the mammalian glucocorticoid receptor (GR) fused to the activation domain of V P16, and the hinge and ligand-binding domain (EcR) of Heliothis virescens. The target promoter (pA) had six copies of the glucocorticoid response element (GRE) attached to a minimal 35S promoter, and activation was achieved in transgenic tobacco through application of the commercially available

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non-steroidal ecdysone agonist tebufenozide. Unger et al. (2002) adopted a similar approach: their chimeric regulatory protein was made from VP16, Gal4 and the EcR from the European corn borer, Ostinia nubialis, and it was used to direct expression from 5xREgal (yeast Gal4-binding sites) linked to a minimal promoter after induction with the agonist methoxyfenozide. Padidam et al. (2003) constructed the GVE chimeric activator from Gal4, V P16 and the Choristoneura fumiferana EcR ligand-binding domain; another activator (LVE) was also constructed in which the Gal4 element was replaced by the LexA DNA-binding domain. Each was used with luciferase constructs with either 5xREgal or 6xRElex , and induced by application of methoxyfenozide in Arabidopsis and tobacco. In each of these systems, signiﬁcant levels of gene expression could be achieved, at least equivalent to the best 35S promoter activity, and while there was variation in both the basal and the induced levels of response, low basal activity could be achieved. However, this could be a greater problem in some species, since endogenous phytoecdysteroids have been reported (Saez et al., 2000). Other systems have been based on oestrogen as an inducer. Bruce et al. (2000) used the human oestrogen receptor (ER) in a fusion protein with the maize C1 activation domain. Zuo et al. (2000) developed a chimeric regulatory protein, XVE, using the LexA DNA-binding domain, V P16 activation domain, with the ER ligandbinding domain to direct expression from a pA composed of 8xRElex in an oestrogendependent manner. High levels of expression were achieved (three- to ﬁvefold 35S) without detectable basal levels. These systems appear to have high efﬁciency and low basal activity in transgenic plants; however, Zuo and Chua (2000) report deregulated expression in transiently transformed soybean cells, possible due to the presence of phytooestrogens. The most extensively used of the steroid-hormone-activated systems utilises the ligand-binding domain of the mammalian GR (Schena et al., 1991). Aoyama and Chua (1997) developed a chimeric regulatory protein, GVG, using the Gal4 DNAbinding domain, V P16 activation domain, together with the GR ligand-binding domain to direct expression from a pA composed of 6xREgal fused to a minimal 35S. Here, in the absence of an inducer ligand, GR associates with cytosolic proteins, but upon addition of a glucocorticoid inducer, the regulatory protein is translocated to the nucleus to bind to the target promoter (see Zuo and Chua, 2000). This has the advantage that compartmentation restricts non-ligand-directed interactions with pA, and thus the basal level of expression is minimised, while allowing rapid highlevel dose-dependent induction in the presence of inducer. Dexamethasone (dex), a synthetic glucocorticoid, is the most commonly used inducer, but other glucocorticoid derivatives have been shown to induce to differing extents (Aoyama and Chua, 1997; Tang and Newton, 2004). The system has been successfully adapted to rice by using the Gos2 gene promoter to drive the GVG construct (Ouwerkerk et al., 2001). However, the system is not without its limitations: dex toxicity has been an issue in rice at 10 μM (Ouwerkerk et al., 2001); severe growth defects, linked to the constructs themselves (rather than dex), have been observed in Arabidopsis; and furthermore the system has caused the induction of defence-related genes (Kang et al., 1999; Craft et al., 2005).

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The efﬁcacy of the GR element for induction has led to its inclusion into other systems recently. pOp6/LhGR is a modiﬁcation of the pOp/LhG4 system described above. The regulatory protein has been modiﬁed to include the GR ligand-binding domain at the N-terminus of the Lac DNA-binding domain and Gal4 activation domain; pOp6 (=pA) has been modiﬁed to include six ideal lac operators (6xRElac ) and the tobacco sequence in the 5 UTR (Craft et al., 2005; Samalova et al., 2005). pOp6/LhGR is thus a dex-inducible system, which shows very high inducible expression, and with a low basal level of activity. Roberts et al. (2005) have also used GR to solve a key problem with the alc system. Plant cells in tissue culture are often (partially) hypoxic and hence produce ethanol/acetaldehyde through ethanolic fermentation. Thus, alc tends to have high basal levels or be constitutive, depending on the culture method and its aeration. Thus, with the exception of the inﬂorescence inﬁltration methods used in Arabidopsis, the tissue culture stages associated with plant transformation will inevitably mean that any gene with a deleterious effect on cell growth may not yield viable/normal transgenic lines. By combining the GR ligand-binding domain at the C-terminus of AlcR, the transcription activator remains in the cytosol (even in the presence of ethanol) and thus cannot activate expression of the transgene. Upon dex addition, expression of the transgene is triggered. This not only obviates the transformation problem, but also enables the study of transgenes in cultured cells, increasing the applicability of alc to cell biology research. Finally, Bohner et al. (1999) have developed a dual control (positive and negative) system termed TGV, by combining elements of both the tet and GR systems. The regulatory protein is composed of the TetR DNA-binding domain, the GR ligand-binding domain and the V P16 activation domain; TGV can bind to a pA containing tet operator sequences. In the absence of dex and tetracycline, TGV will remain in the cytosol, and upon dex addition, it will translocate to the nucleus, bind to pA and activate transcription. The addition of the negative ligand tetracycline destabilises TGV binding, releasing it from the tet operator sites in pA. Different levels of expression were achieved with TGV by using different pA constructs; however, the higher levels of induced activity were associated with elevated background activity (Bohner and Gatz, 2001). Nevertheless, the ability to regulate the decline in activity following induction represents a novel contribution to the transgene expression tool kit. There is a strong argument for ‘artiﬁcial’ non-plant-derived transgene expression systems in terms of the minimal chance of inadvertent expression (low likelihood of initiation from the target promoter by plant transcription factors; little chance of effector ligands activating the introduced transcription factor) and minimal chance of interference of the introduced regulatory protein with host genes and less disruption to plant metabolism/development from the externally applied effector ligand. However, they are not without their drawbacks: dex and some GR constructs have proven to be toxic, and there appears to be induction of A. thaliana defence-related genes; some TetR-based systems have a signiﬁcant basal level of expression; some plants contain phytooestrogens or phytoecdysteroids. As stated earlier, there is no ‘ideal’ conditional expression system, but the development of these, their modiﬁcation and their combination are starting to make important contributions to functional genomic research.

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13.2.6

319

The conditional expression tool kit and its further development

The ideal conditional expression systems should have very low basal expression; high inducibility; high speciﬁcity with respect to the gene target and the inducer ligand; maximal expression levels that can be modulated in a dose-dependent manner; rapid response upon addition of the inducer; a rapid decline in expression following inducer withdrawal; inducers with zero toxicity that are not native to plants and have no physiological effect on the plant; environmentally safe inducers that can be used under ﬁeld conditions; transgene components that are publicly acceptable for ﬁeld use (e.g. see Zuo and Chua, 2000; Padidam, 2003; Tang et al., 2004). Clearly, no such system exists; many inducers are problematic in certain circumstances, and some chimeric regulatory proteins, containing e.g. mammalian or HSV sequences, may be unacceptable outside a controlled laboratory environment. The search for the perfect switch will continue, but there are some important considerations in relation to existing systems. Background expression is a key issue in conditional expression systems. One approach has been to prevent activation in the absence of the inducer by maintaining the regulatory protein and pA in separate lines and combining them by crossing (e.g. Moore et al., 1998), or through the use of site-speciﬁc recombinases to activate expression, e.g. the Cre/loxP recombination system from E. coli bacteriophage P1 (see Hare and Chua, 2002). However, both of these have the drawback that once crossing/excision has occurred, then the transgene is constitutively expressed, and reversal is not possible in those individuals. In many systems, background expression is not zero (under all circumstances). This can be because transcription from pA could be triggered by some endogenous process, or because the construction of a chimeric pA has a low constitutive activity, and/or because the level of expression of the regulatory protein is sufﬁciently high to initiate transcription in the absence of the inducer ligand. In a number of systems, pA has been designed to have strong transcription under inducing conditions, without regard to the effect on uninduced expression: the dual control TGV system demonstrated clearly that the stronger promoters had higher background activity (Bohner et al., 2001). In part, one of the problems is the utilisation of very simple constructs whereas native expression systems are often more complex, where the combinatorial effect of the different components leads to increased ﬁdelity. For many applications, transcription from pA may not need to be so high. In the case of the alc expression system, the risk of induction from endogenous inducer has been partially addressed (Salter et al., 1998; Garoosi et al., 2005): under hypoxic conditions ethanol/acetaldehyde is produced, which induces the transgene. However, ethanol/acetaldehyde occurs in some tissues/organs when growing naturally, for example in the vascular cambium and xylem sap of trees (MacDonald and Kimmerer, 1991), in large tubers of 16-week-old potato plants (Junker et al., 2003) or in the fruits of some species (Pesis, 2005). Low-level inadvertent induction of alc can thus occur in some cell types arising from endogenous levels of these inducers. We also cannot exclude the possibility that any of these systems may produce the regulatory protein in excess to the extent that higher background levels may be observed. It is

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obvious from the literature that most chemically activated gene expression systems have been developed for maximal expression, rather than for optimal expression. In the basic design, almost all use a ‘high’ constitutive promoter (35S) to express the regulatory protein, but perhaps we now need to address whether other plant (rather than viral) constitutive promoters need to be tested to ensure that appropriate levels of regulatory protein are present. It is vital then that a range of constitutive promoters are available, or that synthetic promoters are designed to ensure appropriate levels of transcription (see Bhullar et al., 2003; Potenza et al., 2004). This may also avoid the silencing associated with the 35S promoter (Al-Kaff et al., 2000), and with the increasing requirement for the study of multiple genes simultaneously, it will be essential that all the expression signals (promoters, terminators, etc.) are not repeated between multiple transgene constructs. One approach to avoid high-level expression systemically throughout the plant has been the use of spatial/tissue-speciﬁc expression. For example, Mett et al. (1996) adapted the Cu-inducible Ace1 system to be expressed in an organ-speciﬁc manner in nodulated Lotus corniculatus plants, under the control of the nod45 promoter. Others have adapted alc to be expressed spatially, either in deﬁned regions of meristems (Towers et al., 2003) or in a ﬂower-speciﬁc manner (Maizel and Weigel, 2004). The plastome also offers advantages for the expression of certain proteins, and an ethanolinducible T7 RNA polymerase, targeted to plastids, was able to direct expression of transgenes under the control of T7 regulatory elements (L¨ossl, et al., 2005). Finally, many of the chemically inducible systems may suffer from side effects either by the application of the chemical inducer, or from inappropriate expression of the regulatory protein. While most reports specify whether any ‘visible’ symptoms occur as a result of induction/transgene activation, there clearly could be a myriad of invisible/subtle changes to the development or physiology of the plant as a result of the modiﬁcation. To date the experimentation has been such that most researchers are measuring gross effects. As functional genomic applications increase, subtle but signiﬁcant changes in metabolism, for example from one inducer, may be avoided by using a different inducer or a different expression system. There is little data on such effects but, as mentioned for alc above, ethanol application changed the levels of 13 of the 60 metabolites in potato tubers, while acetaldehyde altered only 3 of these (Junker et al., 2003). There is thus a need to undertake transcriptome analysis to determine the effect of inducers and/or over-expressed heterologous transcription factors to determine the nature of their effect on the host plant’s transcriptome, metabolome and physiology.

13.3

Applications to plant functional genomics

The high throughput genome analyses have revealed large numbers of genes requiring detailed experimentation, individually and in groups, to determine their function. Traditionally, such analysis has always relied upon the examination of the phenotypes of cells/organisms arising from loss-of-function or aberrant gain-of-function

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mutations. Conditional expression systems can provide such analyses, and their use is increasing. Here we give some examples of the various approaches adopted.

13.3.1

Conditional over-expression

Plants in which there is an over-expression of a transgene can develop novel phenotypes for a variety of reasons: for example it could activate downstream genes; there can be a direct, deleterious affect on the phenotype, perhaps leading to lethality at an early developmental stage; or, in the case of the expression of a heterologous gene, a gain-of-function phenotype can result through interference with a normal cellular mechanism. The over-expression of plant transcription factors has been reviewed previously (Zuo and Chua, 2000; Zhang, 2003), and can be used successfully to demonstrate the downstream target genes for these proteins. The major use of conditional expression to date has been to investigate genes whose function is deleterious to the plant when constitutively expressed. Tobacco plants expressing yeast invertase from a strong constitutive promoter generated only weakly expressing transgenic lines, because high expression was deleterious; whereas lines generated as alc-invertase were normal until ethanol addition (Caddick et al., 1998). More recently, by directing AlcR expression from a patatin promoter, Junker et al. (2004) demonstrated that in response to acetaldehyde induction, invertase expression could be localised within the tuber, and dissection of the complex changes in carbohydrate metabolism could be investigated. Using a similar approach, Deveaux et al. (2003) have used alc to investigate the effects of SHOOT MERISTEMLESS and CYCLIN D3;1 in deﬁned subdomains of the shoot apical and ﬂoral meristems. Even if expression of the heterologous gene is not deleterious, normal plant function can be probed. Werner et al. (2003) used a heat-inducible bacterial ipt gene to elevate levels of cytokinin within Arabidopsis and identify novel cytokinin metabolites that are possibly involved in homeostatic mechanisms. Similarly, Koroleva et al. (2004) used an Antirrhinum majus CycD1;1 gene in Arabidopsis to demonstrate a divergence in D cyclin function between plants and animals.

13.3.2

Conditional knockout/knockdown

Insertional mutagenesis of the A. thaliana genome has been very successful, but many insertions do not yield a recognisable phenotype. This is in part due to functional redundancy, but it is compounded by our inability to recognise subtle phenotypic changes. Most phenotypic screens are relatively crude, analysing gross effects: hypothetically, a gene that is expressed only in a speciﬁc cell type in response to a speciﬁc cue may not reveal its phenotype unless a very detailed phenotypic/metabolomic analysis is undertaken throughout plant growth and development. For the analysis of some transcription factors for example, phenotypes have been observed only from multiple knockouts (see Zhang, 2003).

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Conditional knockout/knockdown has potential advantages, as subtle growth changes can be compared under isogenic conditions, in the same plant, at different times. Furthermore, such approaches have the potential to modulate the degree of knockdown by adjusting the concentration of the inducer, and timing of application. Several of the systems described above have been shown to be effective for RNAi on reporter genes: oestradiol-inducible Cre/loxP activated silencing of GFP and phytoene desaturase in Nicotiana benthamiana (Guo et al., 2003); heat-inducible RNAi of phytoene desaturase in Arabidopsis (Masclaux et al., 2004); alc triggered knockdown of GUS in tobacco (Lo et al., 2005); GVG controlled silencing of GFP in pine cells (Tang et al., 2005). Ethanol-inducible silencing of the chlorophyll biosynthetic genes magnesium-chelatase subunit 1 and glutamate 1-semialdehyde aminotransferase led to progressive loss of chlorophyll over 7–9 days, but the subsequent new leaves were normal (Chen et al., 2003). Furthermore, local silencing by application of ethanol to a single leaf left other parts of the plant unaffected. Ketelaar et al. (2004) have also demonstrated that alc-inducible RNAi of actin-interacting protein 1 leads to Arabidopsis plants with cells in the leaves, roots and shoots that fail to expand normally, and in the severest cases, the plants die. Guo et al. (2005) have also demonstrated microRNA activity in downregulating target RNA levels using the oestradiol system.

13.3.3

Conditional complementation

Since genes may have roles both early and late in the development of a plant, constitutive expression of a transgene, or mutation of the gene, may lead to the masking of some phenotypes (Zuo and Chua, 2000). One approach to mutant analysis is to complement the loss of function conditionally, thus revealing the temporal requirement for its gene product. In a study of ufo mutations in A. thaliana, Laufs et al. (2003) were able to use the alc system to express UFO at deﬁned stages of ﬂower development to dissect its function and determine aspects that had not previously been observed through mutation studies. With the wealth of developmental mutants in some species, there is clearly much potential for this approach.

13.4

Potential applications to plant biotechnology

Genetically modiﬁed crops have great potential to improve the growth range, quality and yield of both food and non-food products. Conditional expression is clearly essential for the functional genomics that will generate the transgenes for use in plant biotechnology. But will they ever be used in the ﬁeld, and if so, to what end? Basically, conditional expression would be used to address a particular need for transgene expression only at one time and not another, and hence the technology would need to be stringent to avoid expression when it was not required. The requirement for conditional expression could be (i) to avoid toxicity/contamination to the plant, man or the environment; (ii) to optimise plant growth and productivity at

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different stages of development or in response to environmental conditions; or (iii) to manipulate metabolism for the enhancement of some products over others. One major criticism of GM crops has been the use of selectable markers as indicators of transformation, and hence there has been much interest in the prospect of marker excision. To this end, Cre/loxP excision systems have been developed that are either heat-shock inducible (Hoff et al., 2001; Liu et al., 2005) or oestradiolinduced via XVE (Zuo et al., 2001). Such technology is designed to be used in the development of the crop, prior to growth in the ﬁeld. A second concern has been the ‘superweed’ argument – the introgression of herbicide or pesticide traits into native plants or weed communities around ﬁelds with a subsequent inability to control those weeds. While there have been few examples to date, chemically inducible herbicide resistance has been demonstrated by expressing a rat cytochrome P450 monoxygenase by benzothiadiazole activation of the tobacco PR1a promoter (Yamada et al., 2002). This approach would negate the superweed argument after transgene escape. Recently, engineered disease resistance has been reviewed in detail (Gurr and Rushton, 2005). The optimisation of plant growth or productivity can involve a number of strategies from plant protection against biotic or abiotic stress for growth in marginal environments, to modifying plant development to optimise yield. Salt tolerance, for example, could be achieved through increased production of osmoprotectants, but there may be advantage to produce these only when required. For protection against pathogens, there are clear possibilities through the use of wound/pathogen-inducible promoters. Breitler et al. (2004) used a wound-inducible promoter to direct cry gene expression in Bt transgenic rice, and showed that while it was as effective as constitutive expression, there were more external symptoms of attack due to the time lag to protection. Approaches such as these can lead to a more targeted approach to plant protection. Increased yield has been achieved through the development of shorter crop varieties in which lodging is reduced. The constitutive expression of the GAI protein in transgenic rice led to a series of detrimental effects, affecting ﬂowering and seed production (Fu et al., 2001). However, conditional expression of GAI using the alc system in Arabidopsis enabled GAI expression to be temporally controlled thus avoiding the side effects (Ait-ali et al., 2003; Tomsett et al., 2004). The increased yield associated with F1 hybrid seed production has generated much interest in conditional male sterility, which also can suppress gene ﬂow from biocrops to the wild. Of course, male sterility must be reversed to maintain the inbred parental lines to make F1 hybrids in the following season. Several crops exploit cytoplasmic male sterility (cms); for example, mutation of the maize MS45 gene results in the abortion of microspore development that can be restored through complementation with a functional MS45 gene. Unger et al. (2002) have demonstrated ecdysone-inducible restoration of male fertility in ms45 mutant maize. In a novel approach, cms has been engineered through the expression of β-ketothiolase in the chloroplast genome of tobacco (Ruiz and Daniell, 2005). In this study, restoration was achieved through growth in continuous light in a few ﬂowers, but the

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combination of this with a chemically inducible RNAi to suppress β-ketothiolase expression would work even better. Plant metabolic engineering is complex and in its infancy. While there is much to do in the improvement of crop nutritional qualities, much of this is unlikely to need conditional promoters. However, the non-food uses, some of which will be toxic to the plant, or potentially hazardous in the environment, may proﬁt from temporally controlled expression. Scheller and Conrad (2005) have recently reviewed the potential for production of silk and mammalian proteins, as well as for biodegradable plastic. While such synthesis can be targeted to organs or organelles to compartmentalise the product, it may be that temporal control may be required to ensure sufﬁcient yield only after plant growth and development is complete.

13.5

Conclusions

We need to develop conditional gene expression systems further, not just to apply them to the analysis of single traits, but to manipulate multiple genes in an individual temporally, e.g. to understand development/metabolism both for research and for the development of novel crops. In the research stages at the very least, multiple and different regulation will be required – one or more genes to be over-expressed, while one or more others are downregulated. This will enable the ﬂux of primary metabolism to be diverted to speciﬁc ends, for example. It will be essential therefore that each of the regulatory systems described above is developed further to allow their use simultaneously; that will mean promoters and other signals must avoid similar sequences to prevent silencing. Conditional expression systems will then make signiﬁcant inroads on the wealth of data generated by ‘omic technologies.

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B. Tomsett, A. Tregova, A. Garoosi and M. Caddick (2004) Ethanol-inducible gene expression: ﬁrst step towards a new green revolution? Trends in Plant Science 9, 159–161. M.I. Towers, M. Ito, G. Roberts and J.H. Doonan (2003) Developmental control of the cell cycle. Cell Biology International 27, 283–285. A.K. Tyagi (2001) Plant genes and their expression. Current Science 80, 161–169. E. Unger, A.M. Cigan, M. Trimnell, et al. (2002) A chimeric ecdysone receptor facilitates methoxyfenozide-dependent restoration of male fertility in ms45 maize. Transgenic Research 11, 455–465. R.H. Wang, X.F. Zhou and X. Wang (2003) Chemically regulated expression systems and their applications in transgenic plants. Transgenic Research 12, 529–540. P. Weinmann, M. Gossen, W. Hillen, H. Bujard and C. Gatz (1994) A chimeric transactivator allows tetracycline-responsive gene-expression in whole plants. The Plant Journal 5, 559–569. T. Werner, J. Hanus, J. Holub, T. Schm¨ulling, H. van Onckelen and M. Strnad (2003) New cytokinin metabolites in IPT transgenic Arabidopsis thaliana plants. Physiologia Plantarum 118, 127–137. T. Yamada, Y. Ohashi, M. Ohshima, et al. (2002) Inducible cross-tolerance to herbicides in transgenic potato plants with the rat CYP1A1 gene. Theoretical and Applied Genetics 104, 308–314. J.Z. Zhang (2003) Overexpression analysis of plant transcription factors. Current Opinion in Plant Biology 6, 430–440. J.R. Zuo and N.-H. Chua (2000) Chemical-inducible systems for regulated expression of plant genes. Current Opinion in Biotechnology 11, 146–151. J.R. Zuo, Q.W. Niu and N.-H. Chua (2000) An estrogen receptor-based transactivator XVE mediates highly inducible gene expression in transgenic plants. The Plant Journal 24, 265–273. J.R. Zuo, Q.W. Niu, S.G. Moller and N.-H. Chua (2001) Chemical-regulated, site-speciﬁc DNA excision in transgenic plants. Nature Biotechnology 19, 157–161.

14 Modulation of transcriptional networks in crop plants Tong Zhu

14.1

Introduction

As a precisely controlled biological process, transcription converts the onedimensional information (nucleotide sequences) encoded by the genome into multidimensional quantitative information in the highly dynamic transcriptome, directing when, where, and how much a speciﬁc type of transcript should be transcribed, processed, and degraded. This process is the ﬁrst key step to creating complex messages for plants and other organisms to control complex developmental programs, maintaining a proper metabolic ﬂux of multiple pathways and interactions, and responding to various genetic and environmental stimuli and damages with speed and precision. Transcription regulates many biological processes and consequently affects traits, including many with economic values. Changing transcript levels of even a single gene could dramatically disrupt normal plant development, or alter a plant’s response to environmental stimuli. In fact, complete suppression or reduction of the abundance of a transcript type (i.e., knockout or knockdown, respectively) and the signiﬁcant increase of the abundance of a transcript type (overexpression) have become routine methods to study gene functions (Zhang, 2003; Ostergaard and Yanofsky, 2004). The sensitivity to the transcription change exhibited by plants demonstrates not only the essential function of the transcription of life messages, but also its precise regulation in their life cycle and interaction with their environment. It also provides opportunities to change phenotype by genetic modiﬁcation of existing transcription regulation. The genetic engineering of transcription regulation is a forward engineering process. It revises or builds new systems by introducing new features to the transcriptome systems or completely new pathways to the plants. This can be and has been one of the major paths toward improvement of crop performance and introduction of new functions (Dunwell, 2000; Gantet and Memelink, 2002; Gutterson and Zhang, 2004). In contrast to the modiﬁcation of transcriptional regulation, the identiﬁcation and prioritization of target genes to be manipulated in a genome are reverse engineering processes. Instead of building a system, they are concerned with raveling the operational principles underlying the existing system. This is crucial for the successful manipulation of the trait of interest, but it can also be a challenge. In general, many genes participate in the same transcriptional pathways. They play different

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roles, and the products of these genes may or may not be a rate-limiting factor in a metabolic or regulatory pathway. Furthermore, there are considerable crosstalks among different transcriptional regulatory pathways, demonstrating the existence of a complex transcription regulatory network (Harmer et al., 2000; Shinozaki et al., 2003; Chen and Zhu, 2004; Broun, 2005). The complexity of the transcriptional regulation implies that the simple up- or downregulated gene expression may be suitable to manipulate certain monogenic traits, but may not yield the desired phenotypes for complex traits. It also emphasizes the importance of understanding the gene interaction and regulation in selection and prioritization of target genes in trait improvement by modulation of gene transcription. Furthermore, unraveling a transcription regulatory network in crop species could enable the prioritization of the candidate genes according to their functions, and targeting the transcription of key genes, thus effectively and precisely introducing the expected effects and eliminating or minimizing the unexpected negative effects. In this chapter, basic methods for dissecting transcriptional regulatory networks will be introduced, and recent advances in this area will be discussed. The impact of understanding regulatory pathways in target gene selection for crop improvement will also be addressed.

14.2

Genes, regulatory factors, regulatory pathways, regulatory nodes, and regulatory networks

Although transcription regulations in plants are highly speciﬁc and believed to occur at the individual gene level, recent global surveys of plant transcriptome under normal growth and development and various environmental conditions revealed that no gene acts alone to perform biological functions. The complexity of the transcription regulations at the genome level can be demonstrated by the numbers of genes being induced by a single simple stimulus and their organized response. Numbers of transcriptome-proﬁling experiments illustrated a common theme of the transcription response. Any environmental stimuli, such as light, circadian, wound, pathogen, and abiotic stress, can induce transcription changes in hundreds to thousands genes (Harmer et al., 2000; Shinozaki et al., 2003; Chen and Zhu, 2004; Schnable et al., 2004; Eulgem, 2005). These genes can be generally categorized into two groups: genes encoding signaling molecules and genes encoding proteins functioning as effectors. The signaling genes include genes encoding protein kinases, transcription factors, and other signaling molecules. Their transcription is characterized by the fast response speed and short half-life. The effector genes encode functional proteins such as various enzymes. Their transcription in response to environmental or developmental stimuli is usually slow and steady (Harmer et al., 2000; Tepperman et al., 2001; Cheong et al., 2002; Fowler and Thomashow, 2002). It is generally accepted that transcription of genes in a signaling or a metabolic pathway is coordinately regulated to form a transcription pathway. However, it is less clear how different transcription pathways interact with each other. Characterization of these interactions has been proved challenging by the gene-by-gene

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331

approach. The systems-wide survey, such as transcriptome proﬁling, on the other hand, revealed such interactions or crosstalks. Genes previously associated with a particular established signal transduction pathway or a biochemical pathway are found to be induced or suppressed by stimuli activating other transcription pathways. For example, it was found that mechanical wounding signiﬁcantly elevates transcript levels of genes involving wounding and other signals, including pathogen attack, abiotic stress factors, and plant hormones (Cheong et al., 2002). Therefore, different transcription regulatory pathways interact with each other, sometimes by sharing common regulatory components, to form the crosstalks among different pathways. The crosstalks between different regulatory pathways constitute transcription regulatory networks. The transcription networks enable the coordination of synthesis of molecules with differential functions in a biological process by regulating complex interactions among transcription pathways. They also enable processing biological functions by alternative paths. The transcription regulatory networks could be depicted as a graphic representation of the regulatory relationships reﬂecting the functional organization of the transcription in a cell. In such a diagram, the transcription factors are placed in the center as nodes, and the interactions between genes are depicted as connected lines called edges. The transcription factors and their peripherally located target genes form a regulatory module or motif. These genes either involve the same biological process, or belong to the same biochemical or regulatory pathways. When the genes in the regulatory module share similar expression pattern, they are considered as coexpressed, sometimes being hypothesized as coregulated (regulon). There are three major forms of the regulatory modules (Figure 14.1): single-input modules (a single transcription factor regulates a group of genes), feedforward loops (a single transcription factor regulates a target gene directly or indirectly through a second transcription factor), and bi-fans (both transcription factors regulate both target genes). These forms can occur independently or in combination in a regulatory network. Regulatory modules or motifs are the basic structural and functional units of the regulatory network. Each regulatory network could comprise multiple regulatory modules (Chen and Zhu, 2004).

14.3

Functional characterization of transcription factor genes

Characterization of the functions of the transcription factors is essential to interpret the biological meaning of the transcription regulatory network. Toward this aspect, genome-wide analyses of spatial and temporal expression patterns of transcription factor genes were used to imply putative functions to speciﬁc members of transcription factor gene families (Chen et al., 2002; Czechowski et al., 2004). The openreading frames of all transcription factor genes were cloned to systematically analyze their functions in Arabidopsis (Gong et al., 2004). Large-scale reverse genetics studies using a variety of transposon- or tDNA-tagged mutant population were also used to identify the association between the disrupted transcription factor genes and morphological characteristics (Ostergaard and Yanofsky, 2004). CBF2/DREB1C,

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Figure 14.1 A diagram showing the three major types of regulatory modules. Transcription factors (TF) are indicated by oval circles; genes encoding transcription factors or other products are indicated by the boxes. The interaction between the transcription factors and promoters of genes is illustrated by the solid arrows, and feedback regulation of the transcription factors by the factors themselves is shown as dashed arrows.

a gene with its product functioning as a negative regulator of CBF1/DREB1B and CBF3/DREB1A (Novillo et al., 2004), ABORTED MICROSPORES (AMS), a gene that encodes a MYC class transcription factor functioning in postmeiotic transcriptional regulation of microspore development (Sorensen et al., 2003), and DAG1 and DAG2, both of which encode Dof zinc-ﬁnger proteins controlling seed germination (Gualberti et al., 2002), are among many transcription factor genes being identiﬁed and characterized by this approach. However, in some cases, the systematic

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333

disruption could become a challenge, as many insertion lines lack obvious morphological phenotypic differences (Meissner et al., 1999; Bouche and Bouchez, 2001), partially due to the existence of high functional redundancy among the transcription factor gene family members (Riechmann and Ratcliffe, 2000). The high-throughput analysis of plants containing overexpressed transcription factor genes (Zhang, 2003) and the prediction of functional redundancy by phylogeny reconstructions (Riechmann et al., 2000) have been used to help to combat the obstacles.

14.4

Reverse engineering of transcription regulatory network

The reverse engineering of a transcription regulatory network is the process used to establish the understanding of the necessary components. These components make up the parts list (a list of genes or proteins that participate in the network); the characteristics of the parts (when and where the genes are expressed); the organization of the parts (pathways and processes that known genes participated in); and dynamics and functions of the organized parts. Genome-wide expression analyses are one of the most useful approaches to predict and characterize these regulatory modules. These analyses identify most if not all of the genes in a network and roughly group them together according to their temporal and spatial expression patterns, and the functional nature of the encoded protein products. A number of clustering algorithms are developed to classify the genes in a system – hierarchical clustering, self-organizing map, or principal component analysis, just to name a few (Clarke and Zhu, 2006). The input used for the clustering analysis varies, from gene expression values alone to composite functional indices that consider average expression of all genes known to fall into a certain functional category based on existing knowledge resources such as the Gene Ontology (Cheng et al., 2004; Fang et al., 2006). In many cases the composite functional indices result in clusters that better reﬂect the structure of the data. The expression patterns detected from the genome-wide expression analyses, regulatory sequences, and ontology-based functional predictions form clusters of putative regulatory linkage groups (regulons). It is expected that the coexpressed genes share common DNA-binding sites if they are coregulated; thus an overrepresented cis-regulatory motif could be an indication of the existence of regulatory linkage. A general strategy for predicting the regulatory linkage (edge) within a regulatory group is to quantify the association of a known DNA-binding motif with coexpressed genes. This can be done by comparing the regulatory sequences of coexpressed genes with the regulatory sequences of randomly selected genes from the same genome. The occurrence of a consensus sequence within a prescribed distance from 5 to the start of transcription is counted and compared between the two groups. If the consensus sequence is statistically signiﬁcantly overrepresented in the coexpressed genes than those random genes, then consensus sequences could be predicted as potentially functional binding motifs that mediate the gene regulation (Harmer et al., 2000; Chen et al., 2002; Zhu et al., 2003). Several algorithms based on this string-based motif prediction have been

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developed to avoid the inﬂuence from the plant genome compositions and take the degenerate bases into consideration (Hudson and Quail., 2003; Kreps et al., 2003). The availability of expression data of the model plants and several crop species, such as barley, rice, and maize (Table 14.1), and the regulomics databases and tools (Lescot et al., 2002; Davuluri et al., 2003; Shahmuradov et al., 2003; Steffens et al., 2004; Guo et al., 2005; O’Connor et al., 2005) further empower this approach by identifying coexpressed target genes and their regulators in diverse genetic and environmental conditions. However, this simple model considers only the transcription regulation mediated by one regulatory motif bound by one transcription factor. It discounts the cooperative and competitive interactions between transcription factors and cofactors and their effects in the binding afﬁnity and speciﬁcity. Furthermore, this model is difﬁcult to apply to identify novel transcription factors with unknown binding consensus sequences (Chen and Zhu, 2004). Novel algorithms using more realistic models for transcription regulation by considering multiple binding sites of different strength and accounting for cooperative and competitive interactions have been further developed (Rombauts et al., 2003; Beer and Tavazoie, 2004). One such algorithm predicts the probability that a transcription factor binds within a promoter region by examining the free energy of binding for all possible bases at each position in a binding site, with or without considering the effect of cooperative and competitive interactions (Liu and Clarke, 2002; Granek and Clarke, 2005). An additional method for regulatory motif prediction is using phylogenetic footprinting and shadowing among different species (Wasserman and Sandelin, 2004). This is based on the fact that cis-regulatory elements are frequently conserved (Wray et al., 2003), and its success is recently further demonstrated in mammals (Boffelli et al., 2003) and plants (Hong et al., 2003). Two aspects of the predicted regulatory linkage groups require functional validation. First, the connectivity and relations between transcription factor genes and target genes should be examined experimentally. To identify the downstream target genes, the transcription of transcription factor genes could be disrupted, or induced by ectopic expression, and the transcription of the suspected target genes from the same cluster as the transcription factor genes could be examined. Gene disruption mutant collections provided useful resources for examining the linkage between regulatory factors and target genes in a number of plant species, including Arabidopsis, rice, and maize. Systematic overexpression of transcription factor genes in Arabidopsis overcomes difﬁculties due to the functional redundancy among transcription factor genes, and provides valuable additional resources (Zhang, 2003). Transcriptome proﬁling of such mutants and transgenic plants have led to the identiﬁcation of target genes of APETALA3 and PISTILLATA, class B ﬂoral homeotic genes (Zik and Irish, 2003), of ripening-inhibitor (RIN) and nonripening (NOR) transcription factors (Moore et al., 2002), and target genes of transcription regulators for ﬁber differentiation (Ehlting et al., 2005). These results not only establish the linkage between the transcription factor gene and its downstream genes, but also characterize the type of the interaction (activation or repression).

Multiple species including plants, public depository Multiple species including plants, public depository Multiple species including plants, public depository Multiple plant species Arabidopsis, public depository Arabidopsis Arabidopsis Barley Soybean Maize Rice Tomato Multiple plant species, stress related

Gene Expression Omnibus

PLEXdb TAIR Gene Expression NASCArrays Botany Array Resource BarleyBase SGMD ZEAMAGE RED TED OSMID

SMD

ArrayExpress

Species

Major public microarray databases that archive plant data

Database

Table 14.1

Yazaki et al. (2002) Fei et al. (2003)

Shen et al. (2005) Rhee et al. (2003) Craigon et al. (2004) Touﬁghi et al. (2005) Shen et al. (2005) Alkharouf and Matthews (2004)

Ball et al. (2005)

Parkinson et al. (2005)

Barrett et al. (2005)

Reference

http://www.plexdb.org/ http://www.arabidopsis.org/info/expression/index.jsp http://affymetrix.arabidopsis.info/ http://bbc.botany.utoronto.ca www.barleybase.org http://psi081.ba.ars.usda.gov/SGMD/default.htm. http://www.maizearray.org/ http://red.dna.affrc.go.jp/RED/ http://ted.bti.cornell.edu/ http://www.osmid.org/

http://genome-www5.stanford.edu/

http://www.ebi.ac.uk/arrayexpress/

http://www.ncbi.nlm.nih.gov/geo/

URL

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Second, the physical association of transcription factors with corresponding promoter sequences should be further examined in order to support the establishment of the regulatory linkages. Yeast one-hybrid experiments are useful to detect protein– DNA interactions and to isolate new proteins that bind to a speciﬁc regulatory element (Luo et al., 1996). The technical advancements in combination of chromatin immunoprecipitation (ChIP) with microarray analysis enable the genome-wide survey of the transcription factor–DNA interaction (Ren et al., 2000). ChIP is a method that allows one to identify the speciﬁc locations in the genome where proteins of interest are bound within living cells. When combined with microarrays with tiled probes representing collected promoter sequences or whole genomes, it is possible to identify target sites of transcriptional regulatory proteins and speciﬁc features of chromatin, on a genome-wide basis in an unbiased manner. These methodologies have provided new insight into the mechanisms by which proteins ﬁnd their correct target sites in living cells, and have played a very important role in elucidating the transcriptional circuitry that underlies cellular differentiation and the response to environmental cues. Using this approach, genes regulated by the transcription factors functioning in ﬂower development and light signaling are identiﬁed (Zik and Irish, 2002; Gao et al., 2004). However, currently, the technical challenge and high cost associated with this approach limit the application for studying target genes for all transcription factors of a plant genome in a systematic way. This technical hurdle is especially true while using the whole-genome tiling arrays (Mockler et al., 2005). In order to elucidate the remote indirect interaction among genes (‘trans’ effect) in the regulatory network, the synergy between global gene expression studies and genetic linkage analysis has been used to identify expression quantitative trait loci (eQTL) (Bystrykh et al., 2005; Li and Burmeister, 2005). Since mRNA levels for many genes are heritable quantitative phenotypes, the genetic variants that inﬂuence gene expression can be characterized (Chen et al., 2005; Kliebenstein et al., 2006). A recent microarray analysis of Arabidopsis shoot development in 30 recombinant inbred lines derived from a cross of Col and Ler ecotypes produced quantitative measurements of the phenotypes. Using these data, ﬁve major QTLs with signiﬁcant marker-by-gene linkages were identiﬁed. The most signiﬁcant eQTLs, particularly those overlapped with shoot regeneration QTLs, showed genetic regulation in ‘cis’ because of variants in the gene’s own regulatory regions, while additional less signiﬁcant eQTLs showed ‘ trans’ effect, i.e., by loci elsewhere in the genome (Decook et al., 2006). Although this methodology is still in development, there is no doubt that it will shed light on the genetic basis of the regulatory networks, and on the process that transforms genetic blueprints into cellular functions. Reconstruction of a genome-wide complex regulatory network from large-scale data sets depends on the development of computational algorithms. Several algorithms have been developed to utilize the results from analyzing single data type from literature, transcription proﬁling data, and yeast two-hybrid data or combined heterologous data types. The most commonly used is combinatorial analysis of promoter elements and transcriptome data. It establishes links between transcription factors that bind to the cis-elements and genes containing the combination of cis-elements based on the common expression patterns emerged from microarray

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data (Pilpel et al., 2001). Module network is another algorithm that ﬁrst partitions the genes into different regulatory modules based on the expression pattern revealed by large-scale transcriptome analysis. It then further analyzes the relations among the genes and their regulators within each regulatory module based on a probabilistic relational model (Segal et al., 2003). This algorithm can be used to obtain in-depth information about the regulatory modules that are most relevant to the trait of interest. Similar to the module network algorithm, the genetic regulatory module algorithm also establishes the regulatory network, based on the identiﬁcation of regulatory modules. In addition, it uses the global binding data from the ChIP microarray analyses to connect transcription factors with target genes with different expression patterns (Bar-Joseph et al., 2003). Finally, the Bayesian network model converts the quantitative data into a probabilistic framework, and thus is able to combine heterologous data types to predict an interaction (Troyanskaya et al., 2003). Although computational inference of molecular interaction could provide guidance for targeted experimental validation, and overcome some time-consuming and difﬁcult steps faced by the experimental approaches, such as identiﬁcation of all the in vivo interactions, and characterization of the kinetic parameters associated with in vivo biochemical, biomechanical, or electrophysiological interactions (Bolouri and Davidson, 2002), it is important to recognize that the interactions suggested by the computational prediction and large-scale in vitro or in vivo functional analysis may not be accurate and may not correlate. In a recent comparative analysis of the results obtained from yeast two-hybrid system, in silico prediction based on sequence motif and transcriptome proﬁling, it was found that no single approach produced reliable results as the results from these approaches frequently do not relate to each other and overlap to each other (von Mering et al., 2002). It demonstrated the importance of combining the evidence from two or three methods in improving the accuracy and coverage of the predicted interactions.

14.5

Transcription network in crop plants

To date, most of the studies on reverse engineering of plant transcriptional regulatory network were conducted in Arabidopsis. The translation of the genomic information and knowledge obtained from a model species into agriculturally relevant plants for improvement could be achieved by (1) discovering leads from the regulatory networks of model systems that correspond to orthologs in crops, if the regulatory network modules are evolutionarily conserved, and (2) discovering leads and reconstructing the regulatory network directly in crops, using an experimental approach, if the regulatory network module is not conserved (Clarke and Zhu, 2006). Comparative transcriptomics studies could be used to experimentally determine the overall similarity and differences of regulatory networks between different species. A recent study revealed that rice transcriptome consists of many unique transcripts compared to that of Arabidopsis. Microarray analysis conﬁrmed that a large number of predicted genes without signiﬁcant Arabidopsis homologs are in fact expressed. Among the best matched homologous genes of certain functional groups between the two species, the spatial and temporal expression pattern could

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differ signiﬁcantly (Ma et al., 2005). These results illustrate the variations in degree of conservation among different regulatory modules between the two species and signal the potential pitfalls in translation of certain regulatory relations from model species to distant crops. When the regulatory modules are functionally conserved, the comparative analysis of the orthologs and their positions in the network between closely related species or genotypes within a species can determine the nature of the transcriptional ﬂux: if the transcriptional ﬂux is operated by similar genes with different timing in those species or genotypes, then the difference between them represents a mechanistic solution; if the transcriptional ﬂux is operated by different genes with similar timing, then the difference represents a functional solution (Clarke and Zhu, 2006). In many crop species, the regulatory network can be revealed directly using the available functional genomic tools and data. Custom-designed and commercial microarrays have become increasingly available for crop species (Zhu, 2003) to construct large data sets for this purpose. For species having less functional genomics tools, microarrays of a closely related model species could be used to experimentally explore the regulatory networks in crops by heterologous detection (i.e., cross-species probe-target hybridization) (Zhu et al., 2001). Because the degree of sequence conservation is not always consistent among the genes between the model and applied species, this approach is considered a prescreening method. The relatively low-signal speciﬁcity during cross-species hybridizations makes distinguishing the expression of a speciﬁc gene from a sequence-conserved gene family a challenge task. Nevertheless, the results could provide valuable reference data based on not only sequence similarity but also expression pattern for regulatory network comparison. The existence of common regulatory modules for many traits is supported by the discovery of shared common key transcription factors among phylogenic distant species. Because these transcription factors represent the key nodes in the transcription regulatory network, their commonality could imply the similar regulatory modules among different species. Cold acclimation is a phenomenon referring to the increased freezing tolerance in response to low, nonfreezing temperatures in plants. It has been shown that cold acclimation is transcriptionally controlled by the CCAAT-binding factor (CBF)/dehydration-responsive element-binding (DREB) transcriptional activators and the CBF-targeted genes (CBF regulon) in Arabidopsis (Thomashow, 2001; Shinozaki et al., 2003). CBF-like proteins have been identiﬁed in many other species including Brassica, wheat, rye, tomato (Jaglo et al., 2001), barley (Choi et al., 2002), rice (Dubouzet et al., 2003), pepper (Hong and Kim, 2005), maize (Qin et al., 2004), and soybean (Li et al., 2005). Among them, tomatoes are freezing sensitive, and do not cold acclimate. Nevertheless, the CBF-like proteins showed conserved amino acid sequences that are unique among other AP2/EREBP protein family members (Jaglo et al., 2001). The transcripts of these genes and the homologs of the Arabidopsis CBF target genes can be induced by low-temperature exposure. Moreover, the constitutive overexpression of the Arabidopsis CBF genes has shown the induction of the expression of orthologs of Arabidopsis CBF-targeted genes and

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increases the freezing tolerance of both nonacclimated and cold-acclimated plants. Similarly, overexpression of genes encoding CBF-like proteins in Arabidopsis has resulted in improved cold and salt stress tolerance in many species (Zhang et al., 2004a). These results suggest that the components of the CBF cold-response pathway are highly conserved in ﬂowering plants and not limited to those that cold acclimate. The identiﬁcation of the common key regulatory nodes is essential for the detection of similar regulatory network modules, and is the basis for enabling a generic strategy to manipulate the traits of interest across a variety of crops. However, the target genes within the regulon or regulatory network module and their interaction with the transcription factors could vary among species; thus, precaution should be taken when applying such an approach. Slight difference in the regulatory elements could lead to dramatic changes in phenotype (Frary et al., 2000). A recent study illustrated that the key transcription factor genes could activate different set of the target genes in different species. The nonacclimated plants such as tomato contain functional CBF transcription activators, but the tomato CBF activates a different set of target genes compared to the cold-acclimated plants, such as Arabidopsis (Zhang et al., 2004b). In another case, the key regulator LeMADS-RIN (ripen-inhibitor), a MADS transcription factor that is found expressed in nonclimacteric fruit plants, is also present in tomato, a species of climacteric fruits whose ripening is initiated by ethylene (Moore et al., 2002). These examples demonstrate the difference between the conserved regulatory network key nodes and the conserved regulatory function, and postulate a ﬁne map of the regulatory network modules.

14.6

Transcription factors as gene switches for genetic engineering

Because of the essential positions transcription factors occupied in a regulatory network, they have been targeted for developing gene switches for activation and repression of an entire transcription module by genetic engineering (Lam and Meisel, 1999; Memelink et al., 2001; Broun, 2004). There are several advantages to forwardengineer the transcription regulatory network via manipulating the transcription of transcription factor genes. (1) It is possible to regulate multiple pathways by manipulating the expression of a transcription factor at the high level of hierarchy of the pathway and central node. (2) Changing transcript levels of genes encoding transcription factors could have better ﬁtness during natural selection. It was found that genes encoding transcription factors that are transiently transcribed are signiﬁcantly enriched in Escherichia coli regulatory network motifs and hubs (Wang and Purisima, 2005). In Arabidopsis, it is also shown that the genes encoding transcription factors are targeted for selection (Chen et al., 2005). Because these genes have short transcript half-lives, they can alter their transcript levels quickly, to facilitate network adaptation to the rapid environmental changes. Therefore, the node could represent an excellent target for changing the network motif and further altering the phenotypes. (3) Transcription of transcription factor genes is ﬂexible to manipulate through breeding. By this approach signiﬁcantly fewer genes will need to be introgressed.

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Of the 1500 transcription factor genes identiﬁed in the Arabidopsis genome (Riechmann et al., 2000), the most extensively studied stress-related transcription factors are probably members of the CBF/DREB transcription factors family (Thomashow, 2001; Shinozaki et al., 2003). The transcriptions of CBF1 and CBF3 are induced by various abiotic stresses, including drought, cold, and salinity, but their products also activate the transcription of their direct target genes (COR for cold regulated, named by the original observation) (Jaglo-Ottosen et al., 1998) by binding to the CCGAC motif in the DRE/CRT cis-acting elements. Overexpression of one of these transcription factor genes under the control of various promoters could improve the stress tolerance in Arabidopsis and other plants (Zhang et al., 2004a). These results imply that the elevated transcript levels of the transcription factor genes are translated to the increased functional transcription factors. Genetic manipulation of the expression of the transcription factor genes requires precision to minimize the interaction between the transgene expression and the remainder expression of the existing transcription regulatory network in the host plants. This can be exempliﬁed by the transgenic expression of the CBF1. Constitutive overexpression of CBF1 using 35S promoter can lead to undesirable agronomic performance and yield drag (Liu et al., 1998; Gilmour et al., 2000), partially due to the interference with endogenous regulatory pathways. However, when CBF1 is expressed under the control of the stress-inducible promoter rd29A, mimicking the expression regulation of native copies, the transgenic plants exhibit less yield drag under normal development and better survival when exposed to salt, freezing, and drought, than do the transgenic plants controlled by constitutive promoter (Kasuga et al., 1999; Lee et al., 2003). The modulation of the expression of transcription factors can also be achieved by engineering transcription factors such as zinc-ﬁnger DNA-binding proteins. The unique features of plant zinc-ﬁnger protein in DNA binding and sequence recognition enable more speciﬁc regulation. Using this strategy, a number of genes, including those encoding transcription factors, are regulated in a heritable fashion (Guan et al., 2002). Post-transcription regulation has been used to reduce the level of endogenous transcripts. RNAi is RNA interference by short RNAs. Using a chimeric hairpin RNA construct, all members of the multigene family encoding codeinone reductase are silenced through RNA interference, resulting in accumulation of nonnarcotic alkaloid reticuline in the transgenic opium poppy (Allen et al., 2004). Since it does not affect transcription of other genes in the same pathway, it demonstrated the potential utility of the RNAi in modifying the transcript level of the transcription factor genes in nonmodel crop plants.

14.7

Perspectives

Introduction of foreign genes into plants have been a major route to improve plant performance in the past decades (Dunwell, 2000). Since this approach can introduce independent transcription pathways, it has been used to engineer complete novel functions that do not exist in the plant host, such as novel agronomic traits

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(Ye et al., 2000; Paine et al., 2005), and producing biopharmaceuticals such as mammalian antibodies, vaccines, hormones, and antibodies (Ma et al., 2005), or other novel proteins (Scheller and Conrad, 2005). This approach could be complemented by targeted regulation of transcription of the endogenous genes, especially those with regulatory functions, such as genes encoding transcription factors to improve agronomic performance, especially complex traits such as yield and drought tolerance. Modiﬁcation of transcription of the genes encoding functional proteins such as enzymes has been successfully used in metabolic engineering strategies to overcome single or few rate-limiting enzymatic steps in one pathway. The ﬂux through an already existing pathway in the host plant can be increased or decreased and can result in a modiﬁed accumulation of particular metabolites of interest. For example, overexpression of phosphoethanolamine N -methyltransferase, a rate-limiting enzyme of the plant choline synthesis pathway, signiﬁcantly increases the production of osmoprotectant glycine betaine by 30-fold, and leads to improved resistance to osmotic stresses and improved nutritional value (McNeil et al., 2001). However, in some cases, identiﬁcation of those rate-limiting steps could be unenviable. Change of expression of transcription factor genes, on the other hand, could result in much broader effects and does not require the identiﬁcation of the ratelimiting steps. For example, overexpression of maize LEAF COLOR (LC), a gene encoding MYC-type transcription factor, could result in increased accumulation of anthocyanin and other classes of ﬂavonoids in various organs and tissues in tomato (Bovy et al., 2002). These examples demonstrated a general nonspeciﬁc strategy to coordinately upregulate or activate multiple existing host pathways. Recent efforts in unrevealing the transcriptional regulatory network have identiﬁed the key regulators and their target genes, and provided many candidates for improvement of a number of complex traits. However, to be able to predict the outcome of the modiﬁcation of a transcriptional regulatory network continues to be a challenge: (1) The dynamic nature of the regulatory network and additional interconnected layers ranging from signal transduction pathways involving kinase cascades to transcription control and post-transcriptional regulation of RNA pools, e.g., by microRNAs, to regulatory units that regulate the expression of physical gene clusters at the chromosomal level (Chen and Zhu, 2004) remain to be understood. It is now known that the transgenes originated from other organisms have limited interaction with the host transcriptome (El Ouakfaoui and Miki, 2005). Such studies should be extended to characterize the interaction between the transgenic regulation and host regulatory network, when the transgene has a native copy. (2) The criteria of an optimal target for such genetic manipulations need to be deﬁned and applied. Among the regulatory genes in the regulatory network that were related to the traits of interest, selecting one to maximize the positive impact and minimize the deleterious effects on plant performance is not an easy task. In addition to the genetic and epigenetic effects, such as the inserted transgene being tight linked to the undesired native variation, or being silenced by methylation, it is possible that many intermediate steps in these series of events directly inﬂuence other layers of gene regulation often linking simultaneously to more than one layer. The tight interconnection of signaling, transcription control, and epigenetic changes becomes evident in many

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examples related to regulatory networks. It is essential to include all layers of gene regulation, as functional gene–gene dependencies and feedback loops often involve different levels including protein and DNA modiﬁcation as well as transcriptional changes. Only when the plant transcription network and its interaction with foreign genetic components are well characterized, the genetic improvements of crops through transcription enhancement can have the precision and effectiveness. This will be an essential task of the rapidly emerging ﬁeld of systems biotechnology.

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Index Note: genes and mutants are italicized. A AAG box, 205 ABC model, 253 ABCDE model, 256, 261 acetylation, 57, 63, 69, 278 activation domain, 28 activator sequence-1-like (as-1) element, 268 ADP-ribosylation, 82 AGAMOUS (AG), 39, 42, 123, 255 AlcR, 315, 318, 321 AP2/ERF, 30, 31, 34, 270, 338 APETALA (AP), 255, 334 ARID, 34 AT-hook motif, 55, 58, 96, 114 avirulence gene (avr gene), 267 B bHLH, 30, 31, 35, 274 bimolecular ﬂuorescence complementation (BiFC), 262 BRAHMA (BRM), 117 BRE, 2 bromodomain (BRD), 10, 84, 86, 87, 88, 90, 114 bromodomain extra-terminal protein, 89 bZIP, 31, 71, 241, 270, 295, 298 C CAAT box, 6 CArG box, 256, 258 CBF/DREB, 295, 297, 300, 331, 338 CCAAT box, 6, 7 CDK8/Srb8-11 module, 16 CenH3, 122, 125 chromatin, 42, 54, 58, 65, 112, 278 chromatin assembly factor 1 (CAF-1), 127, 225 chromatin immunoprecipitation (ChIP), 9, 84, 86, 123, 278, 336

chromatin remodeling complex (CRC), 89, 113, 239 chromocenter, 82, 122 chromodomain, 99, 114, 119 CHROMOMETHYLASE3 (CMT3), 120 cis-element, 4, 28, 40, 68, 162, 268, 334, 336 CK2, 57, 63,65,71,169, 173, 203 cold stress, 292 cold-regulated (COR) gene, 295, 298, 300, 340 combinatorial control, 68 conditional gene expression, 309, 319, 321 CONSTANS (CO), 117, 236, 237, 238, 240, 243 copper-controlled gene expression, 314 core histone, 79 core promoter, 4 cosuppression, 136, 138 cotranscriptional processing, 171 C-terminal domain (CTD), 15, 16, 172 D database of Arabidopsis transcription factors (DATF), 30 DDM1, 114, 121, 123 defense response, 266, 270 DEFICIENS (DEF), 258 DELLA, 242 DNA bending, 64 DNA binding, 28, 57, 64, 116, 184, 205, 227, 256, 312 DNA binding domain, 28, 34, 58 DNA demethylation, 102 DNA methylation, 102, 120, 175 Dof, 32, 35, 71, 236, 332 DRD1, 124 DRM1/2, 120

348

INDEX

E ecdysone-controlled gene expression, 316 epigenetic modiﬁcation, 101, 102, 123 enhancer, 4, 68, 82, 137 ethanol-induced gene expression, 315 ethylene-response factor (ERF), 270 euchromatin, 82, 92, 95 expressed sequence tag (EST), 34 expression quantitative trait locus (eQTL), 336 external transcribed spacer (ETS), 163 E(z)-type, 96 D downstream promoter element (DPE), 4 F FACT, 127 FCA, 228 feedforward loop, 330, 331 FLC (FLOWERING LOCUS C), 37, 42, 95, 120, 127, 225, 228, 229, 231 FLD (FLOWERING LOCUS D), 225, 226 ﬂoral homeotic mutants, 255 ﬂuorescence resonance energy transfer (FRET), 261 FRI, 240 FT, 117, 235, 238, 240, 243ﬂuorescent in situ hybridisation (FISH), 122 G general transcription factor (GTF), 1, 12, 19 gene silencing, 101, 137, 138, 148, 165 genomic imprinting, 96 GLOBOSA (GLO), 258 globular domain of H1 (GH1), 55, 129 glucocorticoid-controlled gene expression, 317 GNAT/MYST family, 86 GRAS, 32, 35 H H1 linker histone, 55, 58, 66, 112, 128, 129 HB, 31, 35 HD2 family, 92 head module, 16 heat stress, 285, 290 heat shock protein (HSP), 285, 289, 300, 313

heat shock transcription factor (HSF), 285, 288, 300 heterochromatin, 82, 93, 99, 122, 139, 240 Heterochromatin Protein 1 (HP1), 96, 98, 100, 234 high mobility group (HMG) protein, 54, 88 histone acetylation, 81, 100 histone acetyltransferase (HAT), 10, 83, 85, 88, 100, 116, 127, 169, 173 histone code hypothesis, 84, 112 histone deacetylase (HDAC), 83, 90, 100, 119, 127, 175, 225, 276 histone demethylase, 99, 226 histone H2A, 79, 81 H2AF/Z, 125, 126, 229 H2A.X, 125, 127 H2B, 79 H3, 79, 81 H3.3, 125, 126, 227 H4, 79, 81 histone methylation, 93, 100, 175, 231 histone methyltransferase (HMT), 93, 101, 128, 227, 232 histone replacement, 112 histone variant, 112 HMGA, 55, 67 HMGB, 54, 59, 67HMG-box domain, 58, 64, 168 homeodomain, 34 I initiator region (Inr), 4, 7 intergenic spacer (IGS), 162, 166, 174 internal transcribed spacer (ITS), 162 J jasmonic acid (JA), 268, 274, 277 jumonji domain, 227 K Kryptonite (KYP), 98, 123 L Lac repressor, 316 LEAFY (LFY), 30, 39, 42 leucine zipper, 117 Like Heterochromatin Protein 1 (LHP1), 98, 234, 240 loop domain, 140 LSD1 (lysine-speciﬁc histone demethylase 1), 99, 226 LSH, 121, 124

INDEX

M MADS, 30, 31, 34, 35, 37, 42, 235, 253, 256, 260, 262, 339 MAF1-5, 37, 231 MAP kinase, 275, 278, 294 matrix attachment region (MAR), 67, 140, 142, 150 mediator, 11 MET1, 120, 122, 129 methylation, 57, 63, 82, 93, 94 methyl CpG binding (MBD) protein, 124 microarray analysis, 11, 34, 39, 86, 267, 270, 336 micro RNA (miRNA), 242, 341 middle complex, 15 module, 4 multi-input module, 330, 331 MYB, 30, 31, 35, 295, 298 N NEP promoter, 190, 196 NIN, 32, 35 nuclear encoded plastid RNA polymerase (NEP), 186, 187, 207 nuclear export signal (NES), 286 nuclear factor Y (NFY), 6 nuclear localization signal (NLS), 286 nuclear scaffold, 82 nucleoid, 184 nucleolar dominance, 82, 92, 173 nucleolus, 163 nucleolus organizer region (NOR), 162, 174 nucleoprotein structure, 68 nucleosome, 11, 54, 66, 79, 80, 112 nucleosome positioning, 82 O oestrogen-controlled gene expression, 317 P p300/CBP family, 87 Paf1C, 231 pathogen-associated molecular pattern (PAMP), 266, 277 PEP promoter, 189, 196 PGT box, 205 phosphorylation, 57, 65, 82, 278 PIE1(PHOTOPERIOD-INDEPENDENT YEARLY FLOWERING 1), 120, 127, 228

349

PICKLE (PKL), 119 PISTILLATA (PI), 255, 334 plant chromatin database, 60, 62, 114 plant homeodomain (PHD), 87, 95, 114, 233, 239 plastid encoded plastid RNA polymerase (PEP), 186, 188, 207 plastidial promoter, 189 plastid transcription, 185, 192, 202 Polycomb-group (PcG), 96, 232, 243 position effect, 136, 137, 148 post-transcriptional gene silencing (PTGS), 138, 142, 151, 153 preinitiation complex (PIC), 1, 18 promoter, 1, 40, 68, 82, 86, 137, 172, 258, 268, 310 pytopathogen, 266 Q quantitative trait locus (QTL), 336 R reactive oxygen intermediate (ROI), 276 repression domain, 28 resistance gene (R gene), 267, 272 retinoblastoma (Rb) protein, 227 RNA-dependent RNA polymerase (RDRP), 139 RNA-induced silencing complex (RISC), 138 RNA-induced transcriptional gene silencing complex (RITS), 139, 150 RNA interference (RNAi), 123, 138, 322, 324, 340 RNA polymerase I, 162, 166, 169 RNA polymerase II, 1, 12, 18, 93, 229 RNA polymerase III, 18 RNA polymerase IV, 175 RPD3/HDA1 family, 90 S salicylic acid (SA), 267, 275, 277, 313 SANT domain, 114, 117, 127, 230 scaffold attachment region (SAR), 267, 270, 275 SEPALLATA (SEP), 257 SET domain, 95, 97 SIR2 family, 92 single-input module, 331, 332 siRNA, 121, 125, 138, 175

350

INDEX

SNF2, 113, 230 SNF5, 119 SOC1, 117, 235, 237, 242 SPLAYED (SYD), 117 SQUAMOSA (SQUA), 258 STRUWWELPETER (SWP), 15 SUMOylation, 82, 230, 278 Su(var)3-9 type, 97 SWI/SNF, 113, 115 systemic acquired resistance (SAR), 267 σ -factor, 185, 196, 198 T tail module, 12 TAFII 250 family, 87 tandem afﬁnity puriﬁcation (TAP), 262 TATA, 2, 7, 18, 167, 189 TATA-binding protein (TBP), 2, 18, 93, 114, 166, 167 TATA-less promoter, 8 TBP-associated factor (TAF), 4, 8, 9, 166 TetR, 316, 318 TFP response element (BRE), 2 TGA factor, 270, 275 TIF-IA/RRN3, 166 TIF-IB/SL1, 166, 173 TIF-IC, 166 transactivator, 1 transcriptome, 290, 329, 330 transcriptional network, 278, 329, 333, 337 transcription factor, 1, 28, 68, 267, 270, 278, 286, 311, 330 transcription factor IIB (TFIIB), 2, 18

transcription factor IID (TFIID), 6, 8, 12 transcription initiation site (TIS), 163, 166 transcription start sequence motif (TSS motif), 6, 7 transcriptional gene silencing (TGS), 139, 142, 150 transcriptional repressor, 227 transcriptional silencing, 96 transgene expression, 136, 142, 152 Tritorax-group (TrxG), 97 U ubiquitination, 82, 231, 278 upstream activating sequence (UAS), 2 upstream binding factor (UBF), 166, 168, 173 upstream control element (UCE), 166 V vernalization, 232 vernalization independence (VIP) genes, 231 W WRKY, 31, 34, 35, 37, 268, 270, 273, 275, 290 WUSCHEL (WUS), 42, 117 Y yeast two-hybrid analysis, 11 Z zinc ﬁnger, 29, 30, 92, 96, 117, 232, 274, 298, 340

Plate 1 Multicopy transgene loci can form visible heterochromatic knobs. Interphase (A and B) and early prophase (C and D) nuclei from transgenic Arabidopsis were analyzed by DAPI (4 -6-diamidino-2phenylindole) staining to visualize total DNA (panels A and C) and by ﬂuorescence in situ hybridization to visualize centromeric repeats (pAL1, lavender, panel B) and hygromycin phosphotransferase DNA from the hygromycin phosphotransferase transgene (HPT, green, panels B and D). The transgenic HPT locus forms an independent heterochromatic knob (arrows in A and C) that localizes apart from the centromeric heterochromatin. (This plate is modiﬁed from Figure 1 in Probst et al. (2003) and reproduced with the permission from Blackwell Scientiﬁc Publishing.)

Plate 2 MARs increase transgene expression. NT1 tobacco suspension culture cells were cotransformed by microprojectile bombardment with a reporter and selectable marker plasmids as described by Allen et al. (1993, 1996). Independent hygromycin-resistant cell lines were picked and assayed for GUS (b-glucuronidase) by histochemical assay. The top panel shows 58 individual cell lines transformed with a MAR-ﬂanked CaMV 35S-GUS reporter plasmid. The bottom panel shows 60 individual cell lines transformed with a control CaMV 35S-GUS reporter plasmid. The intensity of blue staining indicates the level of GUS expression in each cell line.