Methylome evolution in plants
- Amaryllis Vidalis†1,
- Daniel Živković†2,
- René Wardenaar3,
- David Roquis1,
- Aurélien Tellier2Email author and
- Frank Johannes1, 4Email author
© The Author(s). 2016
Published: 20 December 2016
Despite major progress in dissecting the molecular pathways that control DNA methylation patterns in plants, little is known about the mechanisms that shape plant methylomes over evolutionary time. Drawing on recent intra- and interspecific epigenomic studies, we show that methylome evolution over long timescales is largely a byproduct of genomic changes. By contrast, methylome evolution over short timescales appears to be driven mainly by spontaneous epimutational events. We argue that novel methods based on analyses of the methylation site frequency spectrum (mSFS) of natural populations can provide deeper insights into the evolutionary forces that act at each timescale.
Cytosine methylation is a heritable epigenetic modification and a pervasive feature of most plant genomes [1–4]. It has important roles in regulating the expression of transposable elements (TEs), repeat sequences, and genes. Extensive experimental work has shown that changes in DNA methylation are associated with plant phenotypes [5–20], genome stability [21–25], polyploidization , recombination [27–31], and heterosis [32–40], and that such changes actively mediate environmental signaling [41–43], pathogen responses [44–46], and priming [47–49]. For these reasons, DNA methylation has emerged as a potentially important factor in plant evolution [50–53] and as a possible molecular target for the improvement of commercial crops [54, 55].
In the model plant Arabidopsis thaliana, cytosine methylation occurs in symmetrical CG and CHG contexts, as well as in asymmetrical CHH sequence contexts (where H = A, T, C) . Extensive forward genetic screens in this species have made tremendous progress in dissecting the genetic pathways that establish and maintain context-specific methylation patterns throughout the genome . These efforts have been facilitated by parallel technological developments in measuring methylomes at high resolution , which have permitted detailed assessments of the molecular impact of specific mutant genotypes.
Early methylome sequencing studies of the A. thaliana Columbia reference accession revealed that this model plant methylates about 10.5% of its cytosines globally (30% in context CG, 14% in CHG, and 6% in CHH, approximately), maintains dense methylation within TE and repeat sequences (at CG, CHG, and CHH sites), and (on average) intermediate methylation levels in gene bodies (mainly at CG sites) [59–62]. Insights into the evolutionary origin of these methylome features and into the forces that have shaped them over time cannot be readily obtained from experimental molecular studies, but require comprehensive inter- and intraspecific comparative epigenomic analyses. A major goal of these comparative approaches is to answer the following questions: ‘What are the factors that generate inter-individual variation in DNA methylation?’ and ‘How do evolutionary forces, such as selection, recombination and drift, act on this variation?’ A recent surge in fully sequenced plant genomes and methylomes is now providing the raw material that can be used to begin to answer these questions.
To date, the methylomes of about 90 diverse plant species have been analyzed by whole-genome bisulfite sequencing (WGBS-seq) [4, 57, 63–67] or by high-performance liquid chromatography (HPLC) . These species include representatives of major taxonomic groups such as angiosperms (flowering plants), gymnosperms, ferns, and non-vascular plants, which diverged nearly 500 million years ago and thus cover much of the phylogenetic breadth of the plant kingdom. (For a list of plant species whose methylomes have been analyzed by WGBS-seq or by HPLC, and are analyzed in this Review see Additional file 1.) In addition to these interspecific data, deep genome and methylome sequencing has been performed for over 1000 natural A. thaliana accessions from all over the world [63, 69–75], as well as for several experimentally derived populations in A. thaliana, Zea mays and Glycine max [16, 17, 19, 76–80].
Here, we illustrate how these studies are beginning to provide deeper insights into methylome evolution in plants. Our review shows that long-term methylome evolution appears to be mainly a byproduct of genomic changes, such as the differential expansion of TE and repeat sequences as well as genetic mutations in pathways that control DNA methylation or transcriptional states. By contrast, short-term methylome evolution seems to be strongly dominated by heritable stochastic changes in DNA methylation (i.e., epimutations) that occur at relatively high rates and are largely independent of genomic backgrounds.
Because these two processes operate at different timescales, an obvious empirical goal is to be able to delineate their relative contributions to inter- and intraspecific methylome diversity patterns. We provide a proof-of-principle demonstration in A. thaliana showing that a formal analysis of the species’ methylation site frequency spectrum (mSFS) in terms of epimutational processes provides a powerful framework for addressing this challenge. We argue that further applications of such modeling approaches, in conjunction with high-throughput sequencing data, will be necessary to understand the forces that shape the evolution of plant methylomes over timescales that are of agricultural and evolutionary relevance.
Methylome evolution over long timescales
Our understanding of the genome-wide properties of DNA methylation in plants has been deeply shaped by observations of A. thaliana, but this model plant of the Brassicaceae family has an unusually small and compact genome and a plastic methylome. Early comparisons between A. thaliana and several commercial crops, such as Z. mays and Oryza sativa, already signaled that many features of the A. thaliana methylome are not entirely representative of all plant species [64, 81–83]. In order to grasp the full evolutionary significance of these differences, and to be able to identify factors that can account for them, a more extensive phylogenic sampling of plant methylomes is necessary.
Genome size and methylome diversity
These quantitative estimates support previous observations from a comparative analysis of three Brassicaceae species—A. thaliana, Capsella rubella and Arabidopsis lyrata —which showed that methylome differences are mainly associated with centromeric expansion and deletion of repetitive sequences and TEs. In particular, the loss of three centromeres in A. thaliana relative to A. lyrata and C. rubella has led to a 10% reduction in its genome size and has a measurable impact on cytosine methylation distribution.
The extent of interspecific diversity in GMLs depends strongly on cytosine context. GMLs calculated from CG sites (i.e., CG-GMLs) vary only threefold between species, whereas for CHG-GMLs and CHH-GMLs, there is ninefold and 16-fold variation, respectively. Moreover, although genome size is associated with CG-GMLs and CHG-GMLs, there is no detectable association with CHH-GMLs (Fig. 1d). The biological source of these differences is not entirely clear, but may be at least in part due to technical difficulties in ascertaining CHH methylation states from WGBS-seq data in general [3, 4].
DNA methylation pathways and methylome diversity
Beyond genome-size evolution, inter- and intraspecific diversity in genome-wide and context-specific methylation levels can also be the outcome of genetic divergence in pathways that target DNA methylation. Studies with experimental mutants in A. thaliana, Z. mays and O. sativa show clearly that perturbations of de novo and maintenance methylation genes can strongly affect GMLs as well as context-specific methylation patterns [19, 95, 96]. Few natural experiments exist that would permit a comprehensive evaluation of the impact of such perturbations in the wild. Recently, Bewick et al.  reported that two angiosperm species, Eutrema salsugineum and Conringia planisiliqua, have independently lost CHROMOMETHYLASE 3 (CMT3), an essential methyltransferase that catalyzes histone H3 lysine 9 di-methylation (H3K9me2)-associated CHG methylation . These natural mutants show significantly reduced gene body methylation as well as a reduction in global CHG methylation levels ([3, 97]; Fig. 1d).
Even single point mutations in otherwise highly homologous genes are sufficient to generate extensive methylation diversity. Dubin et al. , for instance, used a meQTL mapping approach to show that two trans-acting SNPs in the gene encoding CHROMOMETHYLASE 2 (a homologue of CMT3) substantially alter CHH methylation levels among A. thaliana accessions sampled from the north and south of Sweden, and another causative polymorphism in this gene has been identified in larger Eurasian samples . Furthermore, Quadrana et al.  recently performed a genome-wide association (GWA) analysis in A. thaliana accessions in which they treated TE copy number as a quantitative trait. Their scan identified a candidate causal SNP in the gene encoding MET2a, a poorly characterized homologue of the CG methyltransferase MET1 [100, 101]. This example illustrates that genetic mutations that affect DNA methylation pathways can act as facilitators of genomic changes, and set into motion complex co-evolutionary dynamics between genomes and epigenomes.
The systematic identification of similar pathway mutations is far more challenging in the context of interspecific analysis. Many genes are involved in DNA methylation pathways [56, 102], and so a comprehensive investigation of gene family phylogenies would be necessary to reveal connections between the functional conservation of specific orthologs and methylome diversity patterns. To date, such information is on the way for the CMT gene family , but only limited results are currently available for other methyltransferase genes or other DNA methylation-related genes [1, 4, 102, 104]. Potential insights from such an analysis are further complicated by the fact that the functional consequences of pathway mutations can be highly dependent on genomic backgrounds. This is exemplified by failed attempts to construct composite loss-of-function mutations in DNA methylation genes in Z. mays , even though similar mutations are fully viable in A. thaliana .
Nonetheless, Niederhuth et al.  recently argued that an indirect approach to assessing the differential efficiency of DNA methylation pathways across species is to compare measures of intragenomic variability in site-specific methylation levels or in the degree of strand-symmetrical methylation at CG and CHG sites. In this formulation, a methylation pathway is considered robust if intragenomic variability is low and symmetrical methylation at CG and CHG is high. The fact that angiosperms differ substantially along these metrics suggests that methylation maintenance efficiency is species-dependent, even if the underlying pathway perturbations remain unknown. These metrics are certainly interesting but need to be evaluated carefully with regards to technical confounders such as mappability, genome coverage, and differential heterogeneity of the sampled tissues.
Gene-body methylation (gbM) as a neutral byproduct of transcription
Arguably one of the most enigmatic features of plant methylomes is the methylation of gene bodies. Body methylated (BM) genes have been heuristically defined as genes that methylate more than 90% of their CG sites and less than 5% of their CHG and CHH sites . The latter requirement filters out genes that feature TE-like methylation patterns, perhaps because they were originally derived from TEs or contain intact or degenerate TE copies. In A. thaliana, about 18% of genes are BM whereas about 65% are unmethylated (UM). Unlike its repressive role in TEs and repeats, methylation in gene bodies tends to occur in moderate to highly expressed genes [62, 97]. The molecular mechanisms by which gene-body methylation (gbM) contributes to transcription, if at all, and its evolutionary significance are not fully understood.
gbM is associated with evolutionarily important genes
Indirect evidence that gbM may be evolutionarily important has come from the observation that BM and UM genes in A. thaliana differ markedly in sequence composition. BM genes are about twofold longer and have greater exon content . Moreover, comparisons of A. thaliana and A. lyrata orthologs show that the ratio of nonsynonymous (K A ) to synonymous (K S ) substitutions is markedly lower in BM than in UM genes (K A /K S = 0.198 and K A /K S = 0.23, respectively; p < 10−5), suggesting that BM genes are subject to stronger evolutionary constraints. Interestingly, in addition to the lower K A /K S ratio, BM genes seem to evolve at a slower rate in general. This is evidenced by the fact that the actual rate of, presumably neutral, synonymous (K S ) and intron (K INT ) divergence is significantly reduced in BM compared with UM genes (K S = 0.122 in BM and 0.140 in UM, K INT = 0.107 in BM and 0.137 in UM). In support of this argument, Takuno and Gaut  showed that nucleosome occupancy is positively correlated with K S and K INT values, attributing this to more efficient DNA-repair machinery in nucleosome-free regions . However, the DNA-repair argument does not readily extend to CG dinucleotides: BM genes are highly depleted in GC content as well as in the proportion of CpG dinucleotides compared with UM genes, which reflects the well-known mutagenic potential of methylated cytosine to change to thymine as a result of deamination . That this difference in CG content is so visible in current sequencing data suggests that methylation levels in gene bodies must have been maintained for significant evolutionary periods.
The selection hypothesis
But how can gbM be maintained as evolution proceeds while methylated cytosines are continually lost through deamination? One explanation for this paradox is that gbM, itself, is under positive selection, which would result in an equilibrium CG content that is defined by the balance between the rate of deamination and the strength of selection [106, 107]. This selection hypothesis implicitly assumes that gbM is essential for gene function, and should therefore be conserved between orthologs across plant species. Initial methylome comparisons between two related grasses, Brachypodium distachyon and O. sativa, seemed to support this prediction , but more extensive taxonomic sampling now shows that gbM can be highly variable across species , even within the same taxonomic groups [3, 97]. The most extreme cases are the two angiosperm species that have no CMT3 (E. salsugineum and C. planisiliqua) and lack gbM altogether. Despite the loss of gbM, the transcriptional state of orthologous genes in these two species seems to be largely conserved, suggesting that gbM has no causal role in the functional conservation of these orthologs.
The emerging neutrality hypothesis
The potential uncoupling of gbM from transcriptional states has raised the question of why gbM often appears in moderately and highly expressed genes in the first place. An emerging hypothesis is that gbM is simply the neutral byproduct of active transcription. Bewick et al.  recently proposed a molecular model for this neutrality hypothesis in which H3K9me2 is stochastically incorporated into transcribed genes. The transient presence of H3K9me2 kickstarts CMT3-dependent methylation of CHG sites and occasionally leads to the methylation of neighboring CGs, which are then maintained by the CG methyltransferase MET1. However, not all transcribed genes are body methylated. Bewick et al.  identified additional sequence and chromatin features that facilitate the accumulation of gbM within transcribed genes.
The hypothesis that gbM is a neutral byproduct of transcription predicts that it should, at least partly, track the evolution of transcriptional states in plant populations, provided that the full DNA methylation machinery is in place. Preliminary evidence that supports this prediction comes from a recent integrative transcriptome and methylome analysis in A. thaliana natural accessions . Causal modeling shows that most cis- or trans-acting SNPs that are associated with both the expression and the methylation levels of a given gene tend to affect methylation through their effects on gene expression rather than the other way around. In other words, methylation is a byproduct of genetic effects on transcription. Many of these causal SNPs show evidence of positive selection , suggesting that the evolving genetic basis that underlies these transcriptional states leaves secondary signatures at the level of gbM.
Methylome evolution over short timescales
Spontaneous epimutations can rapidly generate methylome diversity
Spontaneous epimutations can be defined as heritable stochastic changes in the methylation status of individual cytosines or of clusters of cytosines. In plants, such stochastic events can occur at CG, CHG, and CHH sites. The meiotic inheritance of epimutations, however, appears to be mainly restricted to CG dinucleotides [76–78], probably as a result of context-specific methylation resetting during gametogenesis and early development . Estimates in MA-lines indicate that the rate of forward epimutations (i.e., stochastic gains of methylation) is about 2.56 × 10−4 per CG site per haploid genome per generation, while the rate of backward epimutations (i.e., stochastic loss of methylation) is about 6.3 × 10−4 . Hence, methylation loss is globally about 2.5 times as likely as methylation gain. The asymmetry in these rates has immediate consequences for understanding GMLs in A. thaliana: it implies that about 30% of all CG dinucleotides should be methylated at equilibrium and 70% unmethylated, provided that evolutionary forces such as selection and gene conversion are negligible. These percentages are roughly consistent with actual measurements of GMLs in the A. thaliana reference accession (Columbia), suggesting that epimutations are fundamental to methylome evolution despite the myriad of ways in which genomic changes can shape methylation patterns in the long term.
Putting these rates into perspective, the rate of CG epimutations is about five orders of magnitude higher than the rate of genetic mutations in A. thaliana (7 × 10−9) . In sheer numbers, about 10,000 CG methylation changes occur in a single generation, which contrasts with the two base changes resulting from genetic mutations. The fast accumulation of these methylation changes causes methylomes to diverge rapidly over short timescales. Even after only 30 generations of independent selfing, the methylomes of early-generation and late-generation MA-lines can be clearly distinguished. As the methylation status of individual CG sites is simultaneously subject to both forward and backward epimutations, methylome divergence does not increase linearly over time [72, 78, 117] but saturates rather quickly to some equilibrium divergence value (Fig. 3). On the basis of estimates from Van der Graaf et al. , only about 4000 generations would be needed in a hypothetical mutation accumulation experiment for methylome divergence to be within 99% of this value. This insight leads to the evolutionary prediction that epimutational processes should dominate methylome diversity in the early stages of lineage divergence but only marginally at later stages.
The high epimutation rates have additional implications for studying methylome diversity within and across populations. First, the observed shared methylated state between two individuals (so-called identity by state) cannot be assumed automatically to be inherited from the same parent (so-called identity by descent), because it could have been generated by independent epimutation events. This concept is defined as homoplasy and has been largely studied for microsatellite markers . Second, as divergence in the methylome between populations increases rapidly, backward and forward epimutations would occur at many sites. Therefore, homoplasy will be observed when comparing diverged populations of the same species, thus decreasing the accuracy of inference of past evolutionary events.
Epimutation-induced methylome diversity patterns are potentially long-lived
Because chromosome architecture is broadly stable over long evolutionary timescales, the signatures of epimutational events are potentially long-lived. Indeed, a striking observation is that the epimutation-induced methylome diversity patterns in the MA-lines are highly correlated with those seen among worldwide natural accessions (pericentromeric regions: ρ = 0.94, chromosome arms: ρ = 0.72; Fig. 4), despite the latter having diverged for hundreds of thousands of years [119, 120]. These correlations are even stronger, particularly in chromosome arms, when the MA-lines are compared to a selected sample of North American natural accessions that diverged from a common founder about 200 years ago  (pericentromeric regions: ρ = 0.92, chromosome arms: ρ = 0.82; Fig. 4). Together, these observations indicate that—while the accumulation of sequence polymorphisms affects methylation diversity patterns over time—in the current state of the species’ evolutionary trajectory, these effects are not overwhelming. Similar conclusions can be reached on the basis of a careful evaluation of meQTL studies in A. thaliana accessions [63, 73, 75], which show that on average only about 18–35% of all DMRs are associated with cis- or trans-acting sequence polymorphisms . The above insights raise the following important questions. Are spontaneous epimutations generally a major cause of methylome diversity in natural plant populations? And if so, what are the evolutionary forces that act on these epimutations?
Analysis of the methylation site frequency spectrum (mSFS)
Analysis of mSFS in A. thaliana: an example
To demonstrate the power of this approach, we constructed the mSFS from public WGBS-seq data of 92 worldwide natural A. thaliana accessions  (Fig. 5; see Additional file 3 for a description of how the methylomes used for the mSFS calculations were filtered). These 92 accessions represent a so-called species-wide sample of A. thaliana, characterizing the collecting phase of the species’ coalescent tree . This sample can be seen as a panmictic population and thus fulfills our model’s assumptions (Box 1). For this analysis, we focused only on genic CG sites, because this approach allowed us to draw connections between epimutational processes and the nature of gbM discussed above. As shown in Fig. 5, our theory-based estimates give an accurate description of the observed mSFS, indicating that the underlying model assumptions are sufficient and that epimutations are a major factor in shaping species-level methylome diversity in A. thaliana. Several important insights are emerging from this model fit.
First, the best fitting model provides no evidence for selection on genic CG epimutations at the genome-wide level. This observation is consistent with earlier theoretical models of the MA-lines, which have shown that epimutations accumulate neutrally under benign environmental conditions and in nearly isogenic sequence backgrounds . The lack of selection also provides support to the molecular model of Bewick et al. , which posits that gbM is essentially a neutral by-product of expression, although a more detailed mSFS analysis that considers separate classes of BM and UM genes will be required to confirm this.
A second major insight from the mSFS fit is that the ratio of forward and backward population epimutation rates is similar to that estimated in the MA-lines (3.43 vs. 4.24, respectively). This result indicates that the epimutation bias parameter is robustly maintained in natural environments and in the context of varying genomic backgrounds, a conclusion that has also been reached by Hagmann et al.  using less formal arguments. Estimates of the actual epimutation rates, however, are not available from the mSFS output because the population epimutation parameters are a function of the effective population size (N e ), and cannot be disentangled (Box 1). This is unfortunate as it would be interesting to assess the extent to which the actual rates are modulated by environmental and genetic factors. A previous experiment in which MA-lines were derived under high-salinity soil conditions provided evidence that epimutations are more frequent under this stressor . Similar experiments are underway to assess the rate and spectrum of epimutations as a function of varying genomic backgrounds.
Interesting future directions in the analysis of mSFS
The mSFS analysis approach opens up exciting research avenues. Most notably, it provides a formal framework for carrying out methylome-wide scans for signatures of epigenetic selection by identifying DMRs that significantly diverge from the expected mSFS. While the interpretation of such regions is difficult, as they could be the result of direct selection on methylation states or the outcome of indirect selection on cis- or trans-acting genetic variants, this approach would provide a way to prioritize regions for further analytical or experimental analysis. These methylome-wide scans will also provide a new perspective on the large number of methylomes that have been recently collected in A. thaliana, or will be collected for other plant species in the near future. Another interesting extension of the mSFS approach is to generalize the theoretical result of Charlesworth and Jain  to account for time dependence and therefore to incorporate changes in the population size. Such a model could be used in conjunction with genic CG mSFS data to define a kind of ‘fast-ticking’ molecular clock. Genic CG epimutations can be considered as neutral and occur at rates far exceeding the genetic mutation rate, and so such a re-calibrated clock would yield high-resolution insights into very recent demographic events that would otherwise be invisible on the basis of DNA sequencing data alone.
The recent availability of high-resolution inter- and intraspecific methylome data is providing new insights into the evolutionary role of DNA methylation in plants. Such insights complement the tremendous progress made in recent years in understanding more proximal questions regarding the molecular mechanisms that control DNA methylation during the life course of a plant and during its reproductive stages. This review provides a first unified framework for understanding the evolution of methylation in plants, based on the fact that the epigenomic divergence observed at the longer timescales is necessarily the result of processes occurring within populations at shorter timescales.
At the population level, spontaneous epimutations appear to be a major factor in generating methylome diversity. These epimutations are characterized by their high, asymmetric rates, and the fact that they occur at a finite number of cytosines. Following population genetics theory, drift and selection should drive the changes in epimutation frequencies over time, thus shaping the mSFS in a population. We predict that most plant populations will be close to statistical equilibrium with respect to epimutation, genetic drift, and selection, and that they will be characterized by extensive homoplasy. Cases of positive or purifying selection on epialleles have never been reported, probably because of a lack of appropriate statistical analyses. Hence, an open question is whether epigenetic selection is pervasive or rare in plant populations. A theory-based analysis of the empirical mSFS provides a framework for detecting signatures of positive and purifying selection at the genome-wide scale. Using such an approach, future studies should assess the extent to which the mSFS for different annotation units is conserved between plant species. For instance, is the neutral mSFS that we have detected in A. thaliana natural populations typical? The fact that genic sequences in complex genomes are often ‘contaminated’ with TEs and sequence repeats  would suggest that epimutation dynamics differ fundamentally among different genomes and may be subject to selection. Population-level methylome data in several other plant species will soon emerge to answer these questions.
When populations diverge, drift and high epimutation rates generate fast divergence in methylation at existing cytosine sites. If local adaptation occurs and is mediated by DNA methylation, selection should be observable in the mSFS, and possibly also with the greater divergence between populations of mSFS in key genes for adaptation. Within populations, more drastic genomic changes will arise slowly; these might include, for example, genome rearrangements, gene duplication, the repeating or expansion of TEs, changes in methylation pathways, and so on. We know that these genomic changes affect methylation patterns because DMRs are often associated with segregating structural variants or with mutations in methyltransferase genes. When these features become fixed in a population, the methylome landscape changes drastically. This can be then observed in comparative epigenomics studies that show the cumulative outcome of genetic changes.
From a theoretical perspective, a crucial future step is to develop models that bridge these different time and spatial scales. Such models should include not only population genetic processes (drift, epimutation, recombination, migration, and selection) but also genomic rearrangements and TE dynamics to derive testable hypotheses and statistics suited for the analysis of intra- and interpopulation and species data.
These data-driven modeling efforts should be complemented by rigorous experimental studies that determine how heritable DNA methylation changes arise in different plant species and mating systems, and the extent to which these changes contribute to plant fitness and respond to artificial or natural selection.
Analysis of the methylation site frequency spectrum (mSFS)
Where d n,b is the observed number of sites at which the \( cU \) epiallele occurs \( b \) times in the sample, and q n,b is the probability that the \( cU \) epiallele occurs b times in the sample at a segregating site under model M . To emphasize the proportion of the two epimutation rates α and β, we use the epimutation bias parameter r via β = r\( \alpha \). Maximum likelihood estimates for the parameters r, \( \alpha \) (thus β) and σ can be obtained by performing a grid search over the parameter space. The model with the highest likelihood is selected.
Note that the mSFS approach is also applicable when using ‘regions’ (i.e. clusters of cytosines) as units of analysis rather than individual cytosines. However, this shift in focus requires that differentially methylated regions (DMRs) can be assumed to exist in two epialleic states (i.e. methylated and unmethylated) and that epimutation events occur at the level of ‘regions’.
Differentially methylated region
Genome-wide methylation level
Histone H3 lysine 9 di-methylation
High-performance liquid chromatography
- K A :
Number of non-synonymous substitutions per non-synonymous sites
- K INT :
- K S :
Number of synonymous substitutions per synonymous sites
Mutation accumulation line
Methylation quantitative trait loci
Methylation site frequency spectrum
Single nucleotide polymorphism
Whole-genome bisulfite sequencing
We thank R.J. Schmitz, C.E. Niederhuth, and C. Alonso for their help in re-analyzing their published data.
FJ and DR acknowledge support from the Technical University of Munich-Institute for Advanced Study funded by the German Excellence Initiative and the European Union Seventh Framework Programme under grant agreement #291763. AT and DZ acknowledge funding from the Deutsche Forschungsgemeinschaft grants TE 809/6-2 and STE 325/14.
AV, DZ, RW, and DR analyzed the data. DZ and AT developed the statistical analysis of the model. FJ wrote the paper with input from all authors. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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