Background Plants can transmit somatic mutations and epimutations to offspring, which in turn can affect fitness. Knowledge of the rate at which these variations arise is necessary to understand how plant development contributes to local adaption in an ecoevolutionary context, particularly in long-lived perennials. Results Here, we generate a new high-quality reference genome from the oldest branch of a wild Populus trichocarpa tree with two dominant stems which have been evolving independently for 330 years. By sampling multiple, age-estimated branches of this tree, we use a multi-omics approach to quantify age-related somatic changes at the genetic, epigenetic, and transcriptional level. We show that the per-year somatic mutation and epimutation rates are lower than in annuals and that transcriptional variation is mainly independent of age divergence and cytosine methylation. Furthermore, a detailed analysis of the somatic epimutation spectrum indicates that transgenerationally heritable epimutations originate mainly from DNA methylation maintenance errors during mitotic rather than during meiotic cell divisions. Conclusion Taken together, our study provides unprecedented insights into the origin of nucleotide and functional variation in a long-lived perennial plant.

Failure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called “spontaneous epimutations”. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phenotypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutation events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as a way to identify the epigenetic basis of complex traits.

Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.

1Introduction: Heritable changes in cytosine methylation can arise stochastically in plant 2 genomes independently of DNA sequence alterations. These so-called 'spontaneous epimuta-3 tions' appear to be a byproduct of imperfect DNA methylation maintenance during mitotic or 4 meitotic cell divisions. Accurate estimates of the rate and spectrum of these stochastic events 5 are necessary to be able to quantify how epimutational processes shape methylome diversity 6 in the context of plant evolution, development and aging. 7 8Method: Here we describe AlphaBeta, a computational method for estimating epimutation 9 rates and spectra from pedigree-based high-throughput DNA methylation data. The ap-10 proach requires that the topology of the pedigree is known, which is typically the case in the 11 experimental construction of mutation accumulation lines (MA-lines) in sexually or clonally 12 reproducing species. However, this method also works for inferring somatic epimutation rates 13 in long-lived perennials, such as trees, using leaf methylomes and coring data as input. In 14 this case, we treat the tree branching structure as an intra-organismal phylogeny of somatic 15 lineages and leverage information about the epimutational history of each branch. 17Results: To illustrate the method, we applied AlphaBeta to multi-generational data from 18 selfing-and asexually-derived MA-lines in Arabidopsis and dandelion, as well as to intra-19 generational leaf methylome data of a single poplar tree. Our results show that the epimu-20 tation landscape in plants is deeply conserved across angiosperm species, and that heritable 21 epimutations originate mainly during somatic development, rather than from DNA methy-22 lation reinforcement errors during sexual reproduction. Finally, we also provide the first 23 evidence that DNA methylation data, in conjunction with statistical epimutation models, can 24 be used as a molecular clock for age-dating trees. 25 26 Conclusion: AlphaBeta faciliates unprecedented quantitative insights into epimutational 27 processes in a wide range of plant systems. Software implementing our method is available 28 as a Bioconductor R package at Introduction 34 Cytosine methylation is an important chromatin modification and a pervasive feature 35 of most plant genomes. It has major roles in the silencing of transposable elements 36 (TEs) and repeat sequences, and is also involved in the regulation of some genes [1]. 37Plants methylate cytosines at symmetrical CG and CHG sites, but also extensively at 38 asymmetrical CHH sites, where H= A, T, C. The molecular pathways that establish 39 and maintain methylation in these three sequence contexts are well-characterized [2], 40 2/45 and are broadly conserved across plant species [3] [4] [5] [6] [7]. Despite its tight 41 regulation, the methylation status of individual cytosines or of clusters of cytosines is 42 not always faithfully maintained across cell divisions. As a result, cytosine methylation 43 is sometimes gained or lost in a stochastic fashion, a phenomeno...

Failure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called 'spontaneous epimutations'. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phentoypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutational events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as away to identify the epigenetic basis of adaptive traits.