Thesis
Reference
Assessing the impact of transgenerational epigenetic inheritance on phenotypic variation in Arabidopsis thaliana
REINDERS, Jon
Abstract
Le maintien de la méthylation des cytosines situées dans un contexte CG (mCG) joue un rôle essentiel dans la régulation épigénétique de la transcription chez les plantes et les mammifères, via la structure de la chromatine. Cependant, la transmission des mCG au cours des générations a été étudiée au niveau de quelques loci seulement. Dans ce travail de thèse, les liens fonctionnels entre la transmission trans-générationnelle de la méthylation de l'ADN et les variations phénotypiques ont été analysés en utilisant d'une part des générations successives d'un mutant d'Arabidopsis thaliana affecté dans la maintenance des mCG, le mutant met1-3, et d'autre part une population de lignées recombinantes (appelées epiRILs pour epigenetic recombinant inbred lines) possédant des chromosomes mosaïques, constitués de segments sauvages et de segments appauvris en mCG.
REINDERS, Jon. Assessing the impact of transgenerational epigenetic inheritance on phenotypic variation in Arabidopsis thaliana. Thèse de doctorat : Univ. Genève, 2009, no.
Sc. 4103
URN : urn:nbn:ch:unige-25725
DOI : 10.13097/archive-ouverte/unige:2572
Available at:
http://archive-ouverte.unige.ch/unige:2572
Disclaimer: layout of this document may differ from the published version.
UNIVERSITÉ DE GENÈVE
Département de Botanique FACULTÉ DES SCIENCES et de Biologie végétale Professeur Jerzy Paszkowski
____________________________________________________________________________________________________________
Assessing the Impact of Transgenerational Epigenetic Inheritance on Phenotypic Variation in Arabidopsis thaliana
THÈSE
présentée à la Faculté des sciences de l’Université de Genève pour obtenir le grade de Docteur ès sciences, mention biologie
par Jon Reinders
de
Winnebago, MN (États-Unis)
Thèse No 4103
GENÈVE
Atelier d'impression ReproMail 2009
REMERCIEMENTS
I would like to thank Jerzy Paszkowski for his guidance and constant support during these projects. I thank all Paszkowski lab members; especially Sally Adams, Larissa Broger, Joël Nicolet, Marie Mirouze, Mélanie Dapp, Etienne Bucher, Olivier Mathieu and Isabelle Vaillant for their assistance with the epiRIL experiments. I thank Brande B. H. Wulff and Arturo Marí-Ordóñez (CNRS, Strasbourg) for their dedication and effort in characterizing the epiRILs. I thank Wilfried Rozhon(University of Vienna, Vienna) for assistance in analyzing the methylation levels within the epiRILs. I thank Patrick Descombes (NCCR, Genève), Céline Delucinge Vivier (NCCR, Genève), Didier Chollet (NCCR, Genève), Dirk Schübeler (FMI, Basel), Fabio Mohn (FMI, Basel), Michel Weber (FMI, Basel), and Grégory Theiler for DNA methylation profiling advice and analysis assistance. I acknowledge computations using R (http://www.R-project.org) were performed at the Vital-IT Center (http://www.vital-it.ch) for high-performance computing of the Swiss Institute of Bioinformatics. Last, I would like to thank my wife, Lina, for her love, support, tolerance, and everlasting encouragement while at the University of Genève.
TABLE OF CONTENTS
RESUME EN FRANÇAIS……….vi
LIST OF ABBREVIATIONS……….………ix
CHAPTER ONE: INTRODUCTION……….1
1.1 The Arabidopsis DNA “methylome” ……….2
1.2 CG Methylation………...4
1.3 Non-CG Methylation ………..5
1.4 RNA directed DNA methylation (RdDM) ……….6
1.5 DNA demethylation………8
1.6 Transposable Elements………9
CHAPTER TWO: TRANSGENERATIONAL EPIGENETIC INHERITANCE OF DNA METHYLATION IN THE met1-3 EPIGENOME ………...16
2.1 Introduction………16
2.2 Materials and Methods………...…17
a. Recurrent selection experiment………..……17
b. Methylated DNA immunoprecipitation and microarray analysis………...…18
c. Bisulfite genomic sequencing………...19
2.3 Results………19
a. Inbreeding met1-3 rapidly aggravates developmental defects………...….19
b. mCG controls proper targeting of asymmetrical methylation……21
c. DNA methylation changes in genic regions of met1-3 plants………..……23
2.4 Discussion………..…23
2.5 References………..………25
CHAPTER THREE: GENOME-WIDE, HIGH-RESOLUTION DNA METHYLATION PROFILING USING BISULFITE-MEDIATED CYTOSINE CONVERSION..…….…26
3.1 Introduction………26
3.2 Materials and Methods………...………27
a. Plant material and DNA extraction...27
b. Bisulfite conversion……….………..…………28
c. DNA amplification……….………28
d. Post-amplification quality assessment………...………30
e. DNA fragmentation, labeling, hybridization………….…………31
f. Data processing and analysis……….…………32
g. Validation of novel DNA methylation polymorphisms……….…33
3.3 Results………34
a. A novel random amplification method for BiMP………..………34
b. Reproducibility of the BiMP analysis………36
c. Validation of the BiMP Method………38
3.4 Discussion………..………45
3.5 References………..………47
CHAPTER FOUR: COMPROMISED STABILITY OF DNA METHYLATION AND DNA TRANSPOSON MOBILIZATION IN MOSAIC ARABIDOPSIS EPIGENOME………49
4.1 Introduction………49
4.2 Materials and Methods……….………..51
a. EpiRIL population development………...……….51
b. DNA extraction and methylation analysis……...………..52
c. Bisulfite methylation profiling and microarray data analysis……52
d. Methylation–sensitive cleavage amplification polymorphism assays...53
e. RT-PCR analysis………..………..53
4.3 Results………55
a. Generation of the met1-3 epiRIL population……….………55
b. Phenotypic variation within the epiRIL population…………...…56
c. Inheritance of DNA methylation during epiRIL inbreeding…..…60
d. Dynamic epi-allelic interactions within recombined parental chromosomal segments………...……..63
e. Genetic instability within the epiRIL population………...………72
4.4 Discussion………..………75
4.5 References………..………78
CHAPTER FIVE: ENDOGENOUS RETROTRANSPOSON MOBILIZATION IN MOSAIC ARABIDOPSIS EPIGENOMES………..…81
5.1 Introduction………81
5.2 Materials and Methods……….………..………82
a. Plant material……….…………..………..82
b. Genetic Mapping……….……….…..83
c. Southern Blot analysis……….………..83
d. DNA methylation analysis………...…………..83
e. Expression analysis………....83
5.3 Results………84
a. Identification of the superwoman phenotype…...………..84
b. Discovery of an active Ty1/COPIA LTR retrotransposon…...…..86
c. Evadé is a bonafide epiallele……….….90
5.4 Discussion………..………93
5.5 References………..………95
CHAPTER SIX: GENERAL DISCUSSION AND CONCLUSIONS……….97
6.1 Technical aspects of DNA methylation profiling………..…………97
6.2 Biological aspects of epigenetic regulation………...…………98
6.3 Novel aspects of epigenetic inheritance………...…100
6.4 Future Perspectives………..……103
6.5 References ………..….………105
APPENDICES……….108
Appendix A………..108
Appendix B……….….120
Appendix C……….….…127
Appendix D………..131
Appendix E………..142
RESUME EN FRANÇAIS
Le maintien de la méthylation des cytosines situées dans un contexte CG (mCG) joue un rôle essentiel dans la régulation épigénétique de la transcription chez les plantes et les mammifères, via la structure de la chromatine. Cependant, la transmission des mCG au cours des générations a été étudiée au niveau de quelques loci seulement. Dans ce travail de thèse, les liens fonctionnels entre la transmission trans-générationnelle de la méthylation de l’ADN et les variations phénotypiques ont été analysés en utilisant d’une part des générations successives d’un mutant d’Arabidopsis thaliana affecté dans la maintenance des mCG, le mutant met1-3, et d’autre part une population de lignées recombinantes (appelées epiRILs pour epigenetic recombinant inbred lines) possédant des chromosomes mosaïques, constitués de segments sauvages et de segments appauvris en mCG .
Des profils de méthylation nouveaux et aberrants ont été détectés dans l’épigénome du mutant met1-3, au cours de générations successives, en l’absence de
mCG. Ces profils de méthylation ont pu être détectés en utilisant la technique
d’immunoprécipitation des 5-méthylcytosines (mCIP), ainsi que la technologie BiMP (pour Bisulfite Methylation Profiling). Cette dernière technologie a été rendue possible par la mise au point d’une étape d’amplification de l’ADN dont les cytosines non
méthylées ont été préalablement converties par un traitement au bisulfite. L’analyse de la plante mutante met1-3 au cours des générations a également révélé une grande instabilité phénotypique, confirmant le rôle majeur de la méthylation CG comme coordinateur central de la mémoire épigénétique, essentielle pour la transmission stable de l’information épigénétique chez les plantes.
Dans la population des lignées epiRILs, des variations significatives ont été détectées pour un grand nombre de critères phénotypiques analysés, suggérant qu’une variation épigénétique peut éventuellement affecter l’héritabilité des variations
phénotypiques dans cette population. L’utilisation de la technologie BiMP ainsi que des analyses Southern blot sur trois lignées epiRILs ont permis d’identifier la présence de segments chromosomiques parentaux (sauvages et appauvris en mCG) recombinés, alternant avec des polymorphismes de méthylation non-parentaux présents à une fréquence étonnamment élevée. Ces résultats montrent l’existence d’interactions épi- alléliques durables et contraires aux prédictions mendéliennes dans des plantes hybrides ayant hérité d’épigénomes parentaux différents. La présence de telles « instabilités » épigénétiques persistantes au cours des générations doit être prise en compte lors d’analyses de génétique quantitative et rend difficile l’utilisation de cartographie génétique classique dans des populations recombinantes épigénétiques.
De plus, l’analyse des lignées epiRILs a montré la remobilisation d’éléments transposables. Le transposon à ADN CACTA, immobile dans les lignées parentales, est ainsi activé de manière stochastique dans 28% des lignées epiRILs. L’hypothèse de variations phénotypiques attribuables à une variation génétique ne peut donc pas être écartée lors de l’analyse des epiRILs. Enfin, la mobilisation d’un rétrotransposon endogène de la famille Ty1/Copia, Evadé, a été détectée dans environ la moitié des lignées epiRILs. En partenariat avec mes collègues, nous avons montré que la méthylation CG était responsable de la suppression transcriptionnelle d’Evadé.
Etonnamment, après la réactivation transcriptionnelle, les étapes suivantes du cycle d’Evadé semblent réprimées par les ARN polymérases IV/V, spécifiques aux plantes. De
façon remarquable, cette inhibition s’opère indépendamment du mécanisme de méthylation de l’ADN via la production d’ARN (ou RdDM pour RNA-directed DNA methylation) mais nécessite la présence de l’histone méthyltransférase KRYPTONITE (KYP). Ces résultats inattendus montrent que le contrôle épigénétique des
rétrotransposons ne se limite pas à la suppression transcriptionnelle; de plus la régulation des rétrotransposons semble s’exercer de façon spécifique.
En conclusion, nous avons montré que les analyses épigénomiques chez Arabidopsis doivent désormais prendre en compte les instabilités génétiques liées à la perte de mCG. De plus, nos travaux ont révélé que l’héritabilité de la méthylation de l’ADN différait selon les loci considérés, allant d’un maintien stable de la méthylation au cours des générations à une héritabilité métastable pouvant changer rapidement entre les générations et se produisant indépendamment des recombinaisons méiotiques. De nouvelles stratégies doivent donc être considérées en vue de détecter ou éventuellement de diminuer ces variations épigénétiques métastables, afin de faciliter l’identification d’épi-allèles responsables de variations phénotypiques.
LIST OF ABBREVIATIONS basepairs (bp)
kilobase (kb) megabase (Mbp) nucleotide (nt)
CG methylation (mCG) deoxyribonucleic acid (DNA) ribonucleic acid (RNA)
SET and RING finger-associated (SRA) 5-methyldeoxycytidine (mC)
histone (H)
dimethylation of Histone 3 at lysine 9 (H3K9me2) RNA-directed DNA methylation (RdDM)
short interfering RNA (siRNA) double-stranded RNA (dsRNA) days post sowing (dps)
long day (LD)
room temperature (RT) false discovery rate (FDR) polymerase chain reaction (PCR)
methylcytosine immunoprecipitation (mCIP) bisulfite methylation profiling (BiMP) standard deviation (SD)
CHAPTER ONE: INTRODUCTION
The term “epigenetics” has had multiple definitions which have generated confusion regarding its use and meaning. "Epigenetics" was first used by C. H.
Waddington in 1942 to describe the genetics of epigenesis, the differentiation of cells from their initial totipotent state in embryonic development 1. Since Waddington created the term before the physical nature of genes was understood to be transmitted by DNA, the term was initially a conceptual model of how genes might interact to produce a phenotype. Later, epigenetics began to describe the mechanisms of temporal and spatial control of gene activity during the development 1 and "epigenetics" began to imply any aspect other than the DNA sequence per se that influenced an organism’s development.
Thus, the current meaning of epigenetics implies heritable changes to gene expression patterns due to modifications acting upon the DNA that may be potentially reversible, yet are independent of genetic mutations or DNA sequence changes 1.
Epigenetic modifications affect not only DNA (e.g. cytosine methylation, see below) but also include modifications of the nucleosome, an octamer formed by a central H3/H4 tetramer between two H2A/H2B dimers and wrapped by approximately 150 basepairs (bp) of DNA 2,3, which is the core subunit of chromatin. Once stabilized, nucleosomes are organized into chromatin fibers, referring to the combination of DNA, RNA, and protein that together eventually comprise the chromosome. The contrasting states of euchromatin and heterochromatin have been classically described “active” and
“silent” chromosomal regions 4, respectively, that are generally associated with specific combinations of epigenetic modifications, or a “code”.
Post-translational covalent modifications to the protruding N-terminal amino acids of histones can alter their interactions with DNA and/or nuclear proteins. Histone modifications can include methylation, acetylation, phosphorylation, ubiquitination, sumoylation, citrullination, and ADP-ribosylation. These modifications occur at specific amino acids of the histone that together create a “histone code” defining the regulatory potential of that chromosomal domain 3. Additionally, histone variants with distinct features from the four major histones can be incorporated into nucleosomes and are believed to confer specific functions of chromatin metabolism 2.
Therefore, the term “epigenome” refers to the genome-wide distribution of epigenetic marks such as DNA methylation, histone modifications and the presence of histone variants 5. The specific combinations of these marks are thought to determine local chromatin structure that affects transcription and genome stability 5 and
cumulatively comprise the “epigenetic code” underlying the different phenotypes in different cells, despite these cells (except B lymphocytes) having potentially identical genomes 6. It is from this perspective that the following experiments were created in an effort to systematically measure the transgenerational inheritance of epigenetic
information to assess its heritability and effect on phenotypic variation.
1.1 The Arabidopsis DNA “methylome”
DNA methylation is a well characterized epigenetic modification and was the main focus of these experiments. While other DNA modifications have been reported, 5- methylcytosine is the predominant covalent modification of DNA known to alter gene expression in higher organisms 1. Although absent, or nearly so, within some organisms
(e.g. S. cerevisiae, D. melanogaster, and C. elegans), DNA methylation is ubiquitous in terrestrial plants, but with variable levels. For example, 25% of the Zea mays genome is methylated, but only 6% of the Arabidopsis thaliana genome is methylated 7. Here, DNA methylation will refer to the presence of 5-methylcytosine and the genomic distribution of methylated cytosines is referred to as the “methylome”.
Faithful propagation of DNA methylation is critical for proper development in mammals and plants. A deficiency in the maintenance of DNA methylation in mouse results in embryonic lethality 8 and likewise, severe deficiencies of methylation maintenance in A. thaliana lead to near embryonic lethality 9. The rare survivals are attributed to compensatory epigenetic mechanisms 10. Further, normal development in both mammals and plants requires proper propagation of methylation patterns and aberrations in somatic DNA methylation interfere with correct cell identity. This can be illustrated by certain cancer types that are characterized by genome-wide
hypomethylation accompanied by discrete gains in DNA methylation, notably affecting oncogenes and tumor suppressor genes, respectively 11. Similarly, global
hypomethylation associated with locus-specific hypermethylation has been observed in A.
thaliana mutants and resulted in a loss of fitness and/or specific developmental abnormalities 12-15. Additionally, hypomethylation can result in increased activities of DNA transposons 16-18. Thus, apart of its role in development, methylation of DNA has been implicated in protecting genome integrity.
1.2 CG Methylation
Mammalian de novo methyltransferase activities, primarily conferred by DNA NUCLEOTIDE METHYLTRANSFERASE 3a and 3b (Dnmt3a and Dnmt3b,
respectively) add methylation patterns that are propagated through DNA replication by the maintenance DNA NUCLEOTIDE METHYLTRANSFERASE (Dnmt1) almost exclusively at cytosines preceding guanines (mCG). Dnmt1 functions at the replication fork, prefers hemi-methylated DNA as a template, and interacts with PCNA in vivo 19. In plants, as in mammals, mCG is the predominant methylation pattern and is maintained in a similar manner by METHYLTRANSFERASE 1 (MET1) 12,14, a homolog of the mammalian Dnmt1.
Recently, additional interacting proteins required for proper maintenance
methylation have been reported. In mammals, a SET and RING finger-associated (SRA) domain protein UBIQUITIN-LIKE CONTAINING PHD AND RING FINGER
DOMAINS 1 (UHRF1) is required to efficiently target DNMT1 to the replication fork and to maintain high levels of CG methylation 20-22. Important to this targeting was preferential binding of the UHRF1 SRA domain to hemi-methylated CG sites resulting from the replication of methylated DNA 21. The Arabidopsis homolog of UHRF1, VIM1/ORTH2, also binds methylated CG sites and is required for maintenance of DNA methylation 23,24, suggesting that this pathway is widely conserved in eukaryotes.
In addition to DNA methyltransferases, additional proteins affect DNA
methylation 25. Notably, the loss of DECREASE IN DNA METHYLATION 1 (DDM1), a chromatin remodeling ATPase 26-28, results in progressive DNA hypomethylation following inbreeding, including the loss of mCG and non-CG methylation. These DNA
methylation changes are initially observed at heterochromatic, multi-copy repetitive sequences and subsequently at low-copy sequences encoding genes 13,26,29, with only local, and not genome-wide, changes to the repressive di-methylation modification of histone 3 at lysine 9 (H3K9me2) 30. Interestingly, the delayed onset of aberrant
phenotypes in ddm1 may result from the restriction ofectopic non-CG hypermethylation in genic regions due to the activity of a H3K9 demethylase, INCREASE IN BONSAI METHYLATION (IBM1) 31.
Although the above section focused on CG methylation, it should be made clear that unlike mammals, where DNA methylation is almost exclusively confined to mCGs, any cytosine can be methylated in plants. Although both MET1 and DDM1 play
important roles in maintaining proper CG methylation, non-CG methylation patterns within plant genomes are believed to have evolved as an additional layer of epigenetic control resulting from related enzymatic functions acting in parallel to CG methylation.
1.3 Non-CG Methylation
Non-CG methylation occurs at CNG and asymmetric CHH sites (with N= A, C, G, T and H = A, C, T). DOMAINS REARRANGED METHYLASE 2 (DRM2) is believed to be the primary de novo methyltransferase of cytosines in all sequence
contexts 32, with major role in maintaining asymmetrical CHH methylation 33. The plant- specific CHROMOMETHYLASE3 (CMT3) plays a central role in maintaining CNG methylation 34-37 which is also dependent on an SRA-domain protein, KRYPTONITE (KYP/SUVH4) 36,38. Previous data suggests KYP catalyzes the methylation of histone H3 lysine 9 (H3K9) which provides a binding site for CMT3 through its chromodomain 36,38.
Additionally, SUVH5 and SUVH6 can also methylate H3K9 in this manner 39,40. Likewise, the report that KYP and SUVH6 can bind directly to methylated CHG sites through their SRA domains suggests a self-reinforcing silencing mechanism between H3K9 and CHG methylation 23. This interaction between H3K9 and non-CG is of specific interest in regards to Chapter 5. More generally, the importance of non-CG methylation is of interest to the experiments below, especially in Chapters 2 and 4.
1.4 RNA directed DNA methylation (RdDM)
Following the loss of MET1 or DDM1 activity, initial studies reported DNA remethylation at some loci to be extremely slow, or nonexistent, even when the wild-type enzymatic function was restored 41-43. However, this cannot be generally applied to all newly hypomethylated loci, since the accumulation of de novo DNA methylation patterns have been detected in met1-3 homozygous plants 10,44-48. One mechanism that can
establish novel methylation patterns is the RNA-directed DNA methylation (RdDM) pathway 49,50. The RdDM pathway is one of the small RNA pathways involved in inactivation or repression of a variety of endogenous and exogenous genetic elements, including genes, transposons and retroelements, viruses, and transgenes 51,52.
In Arabidopsis, 24 nucleotide siRNA biogenesis results from RNA-DEPENDENT RNA POLYMERASE2 (RDR2)/DCL3/PolIV activities and functions through AGO4 to initiate or maintain transcriptional silencing through DNA methylation and/or histone modifications 53-57. The basic mechanism involves a double-stranded RNA (dsRNA) trigger, possibly resulting from bidirectional transcription of DNA, self-complementary RNA hairpin loops, or the production of RNA-dependent RNA transcription. RNA
transcription of single stranded RNA can form double stranded RNA transcribed by PolIV, which utilize the NRPD1 and NRPD2 subunits 58, which become templates for RNA DEPENDENT RNA POLYMERASE 2 (RDR2). These steps produce the double stranded RNA that become the substrate for the activities of RNase III–type activities of DICER-LIKE (DCL) enzymes in complexes that catalyze formation of small RNA duplexes 59,60. Although the Arabidopsis genome encodes four DICER-LIKE (DCL) enzymes (DCL1-4) that are believed to act within specific pathways, the DCL’s may also act in a partially redundant manner 61. Following the cleavage of the dsRNA by a DLC enzyme, one strand of the duplex is incorporated into RNase H–like ARGONAUTE (AGO)-containing effector complex. This RNA loading confers sequence-specificity in guiding the AGO protein 62. Subsequent pathway steps remain unclear as to how the eventual RNA-directed transcriptional silencing is established, but more recent data has suggested PolIV and PolV have distinct roles.
Although PolIV was first considered to utilize both NRPD1 and NRPE1 subunits, it has more recently been shown these activities of these subunits are functionally
different, and thus, PolIV and PolV have separate RNA polymerase activities 58. This is based on evidence showing PolIV-dependent transcripts indeed require the conserved polymerase active sites, common to eukaryotic RNA polymerases, and that PolV
physically associates to the both the transcribed loci and the RNA transcripts themselves.
Further, these findings indicate that PolV is not involved in siRNA biogenesis, but rather that PolV transcription at a locus makes it possible for transcriptional silencing to become established if PolV transcriptional activity overlaps with PolIV-dependent siRNA
biogenesis. PolV activity was also shown work downstream of DEFECTIVE IN RNA-
DIRECTED DNA METHYLATION (DRD1), a putative SWI/SNF chromatin
remodeling protein, which is believed to mediate PolV recruitement to chromatin. Hence, the model proposed by Wierzbicki et al. 58 is that PolV transcripts interact with the AGO- bound siRNA and that together these activities lead to transcriptional silencing. This could result from the nascent transcript acting to stabilize or interact with the silencing complex. This model, however, can not exclude the possibility that PolV simply opens chromatin and allows accessibility of the DNA to cytosine methyltransferases 63. In this second model, potential interactions of the nascent transcripts with the AGO-bound siRNA complex would have no functional role 63.
1.5 DNA demethylation
In Arabidopsis, demethylation of DNA results from the ability of DNA
glycosylases to recognize 5-methylcytosine. Arabidopsis DNA glycosylases, including REPRESSOR OF SILENCING 1 (ROS1) and DEMETER (DME) have been
characterized at the genetic and biochemical level 64-68. Notably, the 5-methylcytosine glycosylase activity ofROS1 was 10-times higher than its DNA mismatch repairactivity, indicating its primary function is indeed active DNA demethylation 64. More recently, DEMETER-LIKE 2 (DML2) and DEMETER-LIKE 3 (DML3) have also been
genetically characterized 69, but appear to be restricted to a relatively small subset of genomic targets. The current perspective is that these enzymes prevent the over- accumulation of DNA methylation as a mechanism to ensure normal regulation of potentially methylated genes. Interestingly, recent data has shown this mechanism to
again be directed by small RNA, revealing yet another connection between transcription and DNA methylation.
Recent genetic data indicates REPRESSOR OF SILENCING 3 (ROS3), a regulator of DNA demethylation, acts within the ROS1 pathway to prevent TGS. ROS3 requires it’s N-terminal RNA recognition motif domain that was shown to bind small RNAs in vitro and in vivo 70. Additionally, the purification of small RNAs (15–
30 nucleotides) bound to the immunoprecipitated ROS3 protein identified genomic regions previously reported to be hypermethylated in ros1 dml2 dml3 demethylase triple mutant relative to the wild type control 48. DNA methylation analysis at these regions indicated hypermethylated CG, CNG and CNN methylation levels in ros3 compared to the wild type, suggesting that DNA demethylation by ROS1 may be guided by small RNAs bound to ROS3 70. Immunostaining experiments also revealed co-localization of ROS3 and ROS1 proteins in discrete foci dispersed throughout the nucleus, supporting a critical role for ROS3 in preventing DNA hypermethylation 70. Together, the above data indicate how proper control of the methylome is maintained by balancing DNA
methylation and demethylation.
1.6 Transposable Elements
Transposable elements (TEs) are ubiquitous in prokaryotic and eukaryotic genomes and are believed to have greatly impacted genome evolution. Effects of TEs within genomes include insertional mutagenesis, chromosomal breakage, genome
rearrangement and illegitimate recombination (see reviews 71-73). A benefit of TEs acting as “controlling elements” facilitating the evolution of adaptive regulatory effects has been
proposed 73. Such effects could include influencing the transcript levels of adjacent genes (positively or negatively), by acting as enhancers or promoters, producing alternative splice variants, or altering polyadenylation patterns following transposition into new sites. Hence, despite their mutagenic potential, the adaptive flexibility conferred to the host genome might explain the persistence of these elements throughout evolution 72.
With the advent of genome-wide sequencing over the past decade, it is now clear TEs comprise a significant fraction of most eukaryote genomes. Two major classes of mobile elements exist: DNA transposons and retrotransposons. Autonomous DNA
transposons have terminal inverted repeats (TIRs) and a single open reading frame (ORF) that encodes a transposase. If the element’s coding capacity has been lost, but the cis- sequences necessary for transposition remain, it is considered non-autonomous. Indeed, the first elements characterized, the “Dissociation-Activator two-unit” system, included a non-autonomous element (Ds) that could only transpose or break chromosomes when the transposase of another autonomous locus (Ac) was present 74. A key feature of DNA transposons is that transposition starts by nicking the transposon and target site ends, followed by a stand transfer reaction catalyzed by the transposase 75. Replicative transposition occurs if this intermediate complex is replicated, leaving the donor site unaltered, while a new copy of the transposon in gained at the acceptor site 75. Nonreplicative transposition occurs when the transposon physically moves (“cut and paste”) to the acceptor site leaving a potentially lethal, double stand DNA break at the donor site 75. As briefly stated above, only two transposons families, CACTA (CAC1 and CAC2) and AtMu1, have been reported to become mobile in hypomethylated Arabidopsis mutants 16-18. Notably, no activity has been reported in met1 single mutants.
The above transposition mechanisms separate DNA transposons from elements that require their encoded transcript (mRNA) as the transposition intermediate, known as retrotransposons. Eukaryotic genomes have three types of retrotransposons that can be divided based on structure: LTR retrotransposons with long terminal repeats (LTRs) in direct orientation that encode reverse transcriptase (RT) and/or integrase (e.g. Ty1 and Copia); non-LTRs retroelements without terminal repeats that encode RT and/or endonuclease (e.g. LINEs); and a nonviral superfamily without terminal repeats and without coding capacity (e.g. SINEs). The retrotransposon lifecycle generally includes transcription, translation, reverse transcription and subsequent integration of element cDNA into the acceptor site (“copy and paste”) 75.
Paradoxically, transcription does not necessarily correlate with transposition. For example, in yeast, an average of only one Ty1 cDNA is integrated into the genome for every 14,000 Ty1 transcripts 76. Thus, despite their high copy number in plant genomes, very few active retrotransposons have been identified in plants (see refs 77,78). More importantly, no report exists for active, endogenous retroelements in A. thaliana.
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CHAPTER TWO: TRANSGENERATIONAL EPIGENETIC INHERITANCE OF DNA METHYLATION IN THE met1-3 EPIGENOME
2.1 Introduction
Following the initial characterization of MET1/met1-3 heterozygotes, it was indicated that the loss of DNA methylation during the post-meiotic cell divisions in gametes deficient in MET1 cannot be rescued by the subsequent restoration of wild-type MET1 in the next generation 1. Therefore, it was predicted CpG methylation is essential for transgenerational epigenetic inheritance 1, but the exact mechanisms underlying the perturbed epigenome in the mutant background remained unclear.
Furthermore, phenotypic characterization in met1 hypomorphs had relatively mild phenotypes 2-4 that could accumulate developmental abnormalities during inbreeding 2. Since these results were correlated with a gradual loss of mCG, and a similar progression of developmental anomalies occurred in decrease in DNA methylation 1 (ddm1) mutants during inbreeding, it was expected progressive demethylation explained the gradual accumulation of developmental aberrations during inbreeding of ddm1 mutants.
Surprisingly, we routinely observed phenotypic variants among homozygous met1-3 plants, despite the immediate depletion of nearly all mCGs. Therefore the met1-3 phenotypes could not be correlated with a variable loss of mCG.
Hence, I initiated a selective breeding experiment using recurrent selection for divergent rosette sizes (large and small), a phenotype broadly reflecting plant vigor. The expectation was that novel epi-alleles associated with plant development were
segregating in the met1-3 epigenome and were associated with the phenotypes. If so, it
was expected these could be stabilized and then identified by genetic mapping, as
previously described for ddm1-induced epi-alleles 5. While this experiment was ongoing, my colleague, Olivier Mathieu, reported heterochromatin of inbred met1-3 mutants was progressively remethylated with H3K9 modifications. This further stimulated the interest to determine the extent and nature of epigenetic variation during inbreeding. We
therefore performed a transgenerational analysis of the met1-3 epigenome using array- based DNA methylation profiling, as well as locus-specific DNA methylation
experiments.
2.2 Materials and Methods
2.2a Recurrent Selection Experiment
Third generation met1-3 individuals (n = 28) were grown on soil under long day (LD) growth conditions (16 h light, 8 h dark at 22°C). Importantly, these plants were sibilings derived from one self-fertilized met1-3 progenitor. Individuals with the most divergent rosette sizes were selected and classified as either “large” or “small”. One representative from each class was selected based on high fecundity (the amount of seed produced) and 14 progeny per class were advanced to the next generation. Fourth generation met1-3 individuals from each phenotypic class were grown under LD conditions and photographed at 5 weeks post sowing. Leaf area was measured using Adobe Photoshop CS (Adobe Systems, Inc) and the classes were compared using Excel’s (Microsoft) single factor analysis of variance function.
2.2b Methylated DNA immunoprecipitation and microarray analysis.
Rosette leaf tissue sampled from 9-12 plants during the late vegetative growth phase was frozen in liquid nitrogen. DNA was extracted using CTAB and precipitated with isopropanol. Resuspended pellets were treated with RNase A and Proteinase K. The DNA was re-extracted using phenol:chloroform:isoamyl alcohol (25:24:1); chloroform extracted and ethanol precipitated. DNA concentrations were then assayed with a TKO 100 fluorometer (Hoefer) using the Hoechst 33258 dye.
Two replicate 3 µg genomic DNA samples of 2nd generation met1-3, 4th generation met1-3 and Col-0 were sheared by sonication and methylated DNA was immunoprecipitated as previously described. Immunoprecipitated DNA was amplified following the chromatin immunoprecipitation assay protocol (Affymetrix). Two replicates per entry with 7.5 µg DNA were fragmented; end labeled, and hybridized on Affymetrix ATH1 arrays as recommended (Affymetrix).
Microarray data analysis was performed using the following procedure. First, background adjustments were made using the gcRMA method available in the Bioconductor package of R. Next, background-adjusted values from the six ATH1 datasets were quantile normalized and average signal intensities were determined in log2
scale per probe set. Contrast coefficient ratios for all pair-wise comparisons were calculated as follows: met1-3 2nd/Col-0, met1-3 4th/Col-0, and met1-3 4th/met1-3 2nd. Corrections for multiple comparisons at the 5% false discovery rate (FDR) were
performed and significant differences were detected using Fisher’s test. For each probe set, three outcomes (significantly hypermethylated, no difference, and significantly
hypomethylated) were possible per comparison, creating 27 possible methylation profiles that were counted at the 5% FDR level.
2.2c Bisulfite genomic sequencing
Three replicate 2-µg DNA samples of 2nd generation met1-3, 4th generation met1-3 and Col-0 were digested with DraI (Promega) as recommended. Following
chloroform extraction and ethanol precipitation, bisulfite conversion was performed using the EpiTect Bisulfite kit (Qiagen) as recommended. Primary PCR reactions were
performed with 1µl of treated DNA in 20 µl reactions at 3 min at 95°C followed by 30 cycles of 95°C, 50°C and 72°C (45s each) with a final 5 min elongation at 72°C.
Secondary PCR reactions using 1 µl of primary reaction product in 40 µl reactions were started with 3 min at 95°C and followed by 30 cycles of 95°C, 50°C and 72°C with a final 10 min elongation at 72°C. See Appendix B for PCR primers. PCR products were purified using the GeneElute PCR purification kit (Sigma) and cloned into pGEM-T Easy vector (Promega). Three clonal replicates for each of the 9 bisulfite-treated samples were sequenced.
2.3 Results
2.3a Inbreeding of met1-3 rapidly aggravates developmental defects
Homozygous met1-3 individuals are not only under-represented in the progeny of plants heterozygous for met1-3 , but also show developmental abnormalities of variable penetrance. These include short plant stature, late flowering, altered flower morphology
and reduced fertility. Further inbreeding of met1-3 plants increased the frequency and severity of abnormalities (Fig. 2.1A); the 4th generation was generally terminal.
Figure 2.1 Transgenerational phenotypic aggravation and altered heterochromatin structure in met1-3. (A) Gradual aggravation of met1-3 plant phenotype. Representative pictures of 3-week-old WT and met1-3 plants of the indicated generation are shown. Bar
= 1.5 cm. (B) Phenotypic variation observed within 4th generation siblings. 3rd generation met1-3 siblings with divergent sizes were self-fertilized and compared in size to the 4th generation progeny. Bar = 1.5 cm.
Simultaneously inbred met1-3 lines showed marked variability in range and severity of phenotype. Following recurrent selection based on rosette size between 3rd generation siblings, a stochastic range of phenotypes was observed in the selected 4th generation material. For example, within the expected “large” 4th generation family, three aberrant individuals with deformed development were observed (Fig. 2.1B). Further, the expected “small” family had rosette sizes larger than their progenitor and a greater
average than the “large” 4th generation family, but the difference was not significant (P <
0.055). Thus, no correlation between parental and progeny phenotypes was observed, suggesting epigenetic instability inherently occurred during gametogenesis in the met1-3 background (Fig. 2.1B).
2.3b mCG controls proper targeting of asymmetrical methylation
DNA methylation patterns in wild-type and 2nd and 4th generation met1-3 plants were compared further using bisulfite sequencing at specific heterochromatic loci,
namely the gypsy-class retrotransposon AtGP1, the copia-like retrotransposon Ta3, a 180- bp single repeat and the At5g36660 pseudogene. At all loci, mCG was virtually erased in 2nd and 4th generation met1-3 plants, while CNG methylation was only slightly altered (Fig. 2.2A; the region of the At5g36660 pseudogene examined is free of CG and CNG sites). At AtGP1, the level of mCHH declined in 2nd generation met1-3 plants but
increased in the 4th generation, reaching levels higher than in the wild type (Fig. 2.2,). At all loci, de novo methylation appeared ectopically at new cytosine residues in met1-3, mainly in asymmetrical contexts (Fig. 2.2A, marked by asterisks). Moreover, these novel methylation patterns were not faithfully inherited between the 2nd and 4th met1-3
generations (Fig. 2.2A).
Together, our results suggested that met1-3 plants gain ectopic CHH methylation at heterochromatic loci following mCG depletion. Hence, proper mCG distribution and/or MET1 itself has a critical role in controlling the levels and patterns of non-CG
methylation. However, the degree and the kinetics of aberrant CHH methylation appeared to vary between targets and met1-3 inbred lines.
Figure 2.2 Genome-wide aberrant de novo non-CG methylation in met1-3.
(A) met1-3 altered non-CG methylation patterns at heterochromatic loci. DNA
methylation of the indicated heterochromatic sequences in WT and plants homozygous for the met1-3 mutation for two (met1-3 2nd) and four generations (met1-3 4th) was assayed by bisulfite sequencing. The percentages of methylation of each cytosine residue present along the different sequences analyzed were calculated. Asterisks denote de novo methylated cytosines in met1-3 plants of either generation relative to the WT.
(B) Aberrant de novo methylation within 3’ genic regions revealed by mCIP analysis on the Arabidopsis ATH1 microarray at the 5% false discovery rate. Hypomethylated and hypermethylated patterns represent the loss or gain in DNA methylation, respectively, in the met1-3 generations relative to the wild type.
2.3c DNA methylation changes in gene-rich chromosomal regions of met1-3 plants Methylcytosine immunoprecipitation (mCIP) of methylated DNA for methylation profiling of the Arabidopsis ATH1 microarray was used to investigate DNA methylation changes within euchromatic regions induced by the met1-3 mutation upon inbreeding.
Results revealed methylation differences in ~28% of genes between the wild type and met1-3 (Fig. 2.2B), similar to the previous report of ~33% of genes detected on the Arabidopsis tiling microarray 7. Surprisingly, similar proportions of the genes were hypermethylated or hypomethylated in met1-3: 8.5% and 9.1%, respectively. For these genes, the DNA methylation changes were conserved between met1-3 generations.
However, progressive methylation changes were observed for number of genes. In the 4th generation compared with both 2nd generation met1-3 and the wild type, the observed changes were more frequently due to hyper- than hypomethylation (Fig. 2.2B):
progressive hyper- and hypomethylation patterns were detected for 1,125 genes (~5.0%) and 562 genes (~2.5%), respectively. Moreover, 2.1% and ~0.7% of the genes profiles were transiently hypermethylated or transiently hypomethylated in 2nd generation met1-3 compared to wild-type plants, respectively (Fig. 2.2B), supporting the dynamic changes in methylation found with bisulfite analysis (Fig. 2.2A). Together, these results show that aberrant de novo DNA methylation in met1-3 progenies is not restricted to
heterochromatin but occurs in a genome-wide manner.
2.4 Discussion
Previous examples of ectopically hypermethylated loci in met1 partial loss-of- function mutants or in MET1-antisense lines were reported, but the extent of the
hypermethylation was unclear. Here, we provided evidence that de novo non-CG methylation involving the RdDM pathway is triggered by mCG erasure and occurs genome-wide, affecting both heterochromatic and genic loci. The new methylation patterns are formed stochastically and are irregularly inherited. Thus, the continual maintenance of mCG patterns is the key factor in controlling transgenerational inheritance of epigenetic information
Additional results presented by my colleagues demonstrated that loss of mCG repressed DNA demethylases activity, possibly directly or indirectly, and that progressive H3K9 remethylation occurred within the epigenome 6. Interestingly, since the H3K9me2 marks are relocated away from heterochromatic chromocenters in the absence of mCG, we expected this state to be stable unless mCG patterns were restored. Surprisingly, upon inbreeding of the met1-3 epigenome, non-CG methylation and H3K9 methylation
patterns were re-established in a highly stochastic fashion. This was evidenced by transgenerational progressive de novo deposition of these marks, even at previously unmarked locations 6. We concluded these pathway activities were an induced epigenetic response to partially compensate for the loss of mCG marks, albeit in a highly
uncoordinated and stochastic fashion. Moreover, these observations provide an explanation for the low survival rate of met1-3 plants, as well as for the stochastic appearance of developmental defects. Taken together, our results suggest that mCG not only orchestrates the distribution of non-CG and H3K9 methylation, but is also essential for stable transgenerational inheritance of epigenetic information.
Since altered DNA methylation patterns could be found genome-wide, even within genic regions, it was reasonable to expect these patterns could indeed affect gene
regulation, and thus, the phenotype. A limitation of genome-wide methylation profiling method used here was that the resolution was limited by the size fractionation step. Thus, we were interested to increase the detection resolution of our methylation profiling method beyond the limit of sonication (approximately 500 bp) (see Chapter 3).
From a biological perspective, these results supported the met1-3 mutant background can generate phenotypic variation and epigenetic modifications beyond simple changes to mCG patterns. Yet, despite selecting based on a phenotypic trait, the heritability was highly variable between met1-3 individuals. Therefore to stabilize the inheritance of epi-alleles contributing to phenotypic variation, it would be necessary restore MET1 activity within perturbed epigenomes (see Chapter 4).
2.5 References
1. Saze, H., Mittelsten Scheid, O. & Paszkowski, J. Maintenance of CpG
methylation is essential for epigenetic inheritance during plant gametogenesis.
Nat Genet 34, 65-9 (2003).
2. Finnegan, E.J. The Role of DNA methylation in Plant Development. in Epigenetic Mechanisms of Gene Regulation (eds. Russo, V., Martienssen, R. & Riggs, A.) 127–140 (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York, 1996).
3. Kankel, M.W. et al. Arabidopsis MET1 Cytosine Methyltransferase Mutants.
Genetics 163, 1109-22 (2003).
4. Ronemus, M.J., Galbiati, M., Ticknor, C., Chen, J. & Dellaporta, S.L.
Demethylation-induced developmental pleiotropy in Arabidopsis. Science 273, 654-7 (1996).
5. Stokes, T.L. & Richards, E.J. Induced instability of two Arabidopsis constitutive pathogen-response alleles. Proc Natl Acad Sci U S A 99, 7792-6 (2002).
6. Mathieu, O., Reinders, J., Caikovski, M., Smathajitt, C. & Paszkowski, J.
Transgenerational Stability of the Arabidopsis Epigenome Is Coordinated by CG Methylation. Cell 130, 851-862 (2007).
7. Zhang, X. et al. Genome-wide high-resolution mapping and functional analysis of DNA methylation in arabidopsis. Cell 126, 1189-201 (2006).
CHAPTER THREE: GENOME-WIDE, HIGH-RESOLUTION DNA
METHYLATION PROFILING USING BISULFITE-MEDIATED CYTOSINE CONVERSION
3.1 Introduction
Genome-wide DNA methylation profiling allows parallel analysis of many loci, even when the methylation states of individual loci are not known a priori. During my Ph.D. tenure, newly available high density oligonucleotide arrays tiling across entire genomes provided a feasible platform for such efforts. But in addition to the platform, the methods for detecting methylation polymorphisms needed to be considered.
The resolution of current DNA methylation profiling methodologies is limited by the length of DNA fragments used as query probes for microarrays. For example, the use of methylation-sensitive restriction endonucleases requires DNA fractions of 1- to 4-kb for hybridizing to microarrays 1,2. Other techniques, such as affinity chromatography with methyl-binding domain proteins 3 or anti-mC antibodies to enrich for methylated DNA (named mCIP or MeDIP) 4-6 also employ inherently large probe fragments that limit resolution 7. Moreover, large probes also increase the likelihood of co-precipitating adjacent, unmethylated DNA, causing false-positive signals, especially on high-density oligonucleotide arrays. Finally, these approaches require relatively large amounts of input DNA (2-20µg), thus, their application to small tissue samples remains difficult.
To increase resolution, bisulfite treatment of DNA, in which cytosines are converted to uracil, but mC remains unmodified 8, represents a promising approach 7. Bisulfite-mediated cytosine conversion and subsequent PCR creates C-to-T transitions,
which can be detected by sequencing, or possibly, on oligonucleotide arrays, analogous to single nucleotide polymorphisms 9,10. Indeed, probes derived from bisulfite-converted DNA of a hypermethylated locus in human tumors proportionally increased signal intensity in methylation-dependent manner when hybridized to methylation-specific oligonucleotide arrays 11. However, bisulfite methods have not been previously applied for genome-wide DNA methylation profiling. This is likely due to DNA fragmentation during bisulfite treatment, precluding the preparation of microarray probes representing all chromosomal loci equally.
Here we prepared genomic probes suitable for high-density oligonucleotide tiling arrays by developing a novel technique that reduces the amplification bias for bisulfite- treated DNA. We performed methylation profiling with the same Arabidopsis strains and arrays previously used for mC immunoprecipitation (mCIP) experiments 6. Our results not only agreed with previous mC immunoprecipitation (mCIP) data 6, but also identified additional methylation polymorphisms due to increased resolution.
3.2 Methods
3.2a Plant material and DNA extraction
Plant growth conditions were as previously described 12. DNA from leaf material combined from 9 individuals per sample was CTAB extracted, isopropanol precipitated, and RNase A and Proteinase K treated, as previously described 13. After enzymatic treatment, the DNA was purified by phenol/chloroform/isoamyl alcohol (25/24/1, Sigma) extraction and ethanol precipitation. DNA quantity was estimated using a TKO100 fluorometer (Hoefer Scientific) with Hoechst dye 33528 (Polysciences). Its purity was
measured in a Genequant pro spectrophotometer (Amersham Pharmacia) and its integrity was assessed electrophoretically.
3.2b Bisulfite conversion
DNA aliquots of 4μg were digested to completion with DraI endonuclease (Promega) followed by extraction with phenol/chloroform/isoamyl alcohol, and ethanol precipitation. After two 70% ethanol washes, the pellet was resuspended in 23µl water and 1µl aliquots were again analyzed for concentration, digestion and purity as described above. The sample concentrations were adjusted with water to 100ng/μl. Aliquots of 20µl (2μg) of each DNA sample were subjected to bisulfite treatment using the EpiTect
Bisulfite Modification Kit (Qiagen), which includes a DNA protective buffer. The degree of conversion was determined by sequencing a region of the PHAVOLUTA locus which lacks mCs in the wild type 14. Only samples with conversion levels exceeding 98% were used for random genomic amplification (data not shown).
3.2c DNA amplification
For random genomic amplification, 1/20th of the bisulfite-converted samples (corresponding to maximally 100ng) were ethanol precipitated and resuspended in 7µl water and subjected to random primer extension. To each sample, 2µl of 5X Sequenase buffer (USB) and 1µl of primer “sixN” (40μM) (GTTTCCCAGTCACGATCNNNNNN) or primer “fourN” (40μM) (GTTTCCCAGTCACGATCNNNN), for the “sixN” or
“fourN” method, respectively, were added. In addition to the bisulfite-converted DNA samples, controls of genomic DNA prepared in parallel, but without bisulfite conversion,
and template-free controls (“no-template control”) were prepared. The samples were placed in a thermal cycler, denatured at 94°C for 2 minutes and cooled to 10°C. During the 10°C hold (lasting 5 minutes), 5µl of the elongation reaction mix was added to each sample, and samples were mixed gently. The elongation reaction mix for one sample consisted of 1µl of 5X Sequenase buffer (USB), 1.5µl of a dNTP mixture (10mM each of dATP, dCTP, dGTP, dTTP), 0.75µl DTT (0.1M), 1.5µl bovine serum albumin
(500μg/ml) and 0.3µl Sequenase (13U/µl) (the elongation reaction mix was prepared on ice). To anneal random primers, the temperature was slowly increased (0.05°C s-1) to 37°C and extension was allowed to occur for 8 minutes. The denaturation, Sequenase addition (0.9µl Sequenase and 0.3µl Sequenase dilution buffer), primer annealing and elongation steps were repeated per sample. After the elongation cycles, sample volumes were adjusted to 60µl. Half of the material (30µl) was subjected to PCR amplification with primers complementary to known sequences introduced during the random priming reaction (GTTTCCCAGTCACGATC). For each sample, PCR amplification was
performed in three separate aliquots (due to volume limits in PCR reactions). A reaction mix contained 10µl of elongation reaction, 8µl of 25mM MgCl2, 20µl of 5X PCR amplification buffer, 5µl of a dNTP mixture (10mM each of dATP, dCTP, dGTP, 8 mM dTTP, and 2mM dUTP), 1µl of primer (100 pmol/µl), 1µl GoTaq DNA polymerase (Promega 10 U/µl) adjusted to 100µl with water. Samples were denatured at 94°C for 3 minutes followed by 30 cycles of 94°C (30 seconds); 40°C (30 seconds); 50°C (30 seconds); 72°C (1 minute) followed by 10 minutes at 72°C. Each reaction was purified using the GenElute PCR clean-up kit (Sigma), and the three replicate reactions per
