Extensive de novo activity stabilizes epigenetic inheritance of CG methylation in Arabidopsis transposons

Improved inference of population histories by integrating genomic and epigenomic data

“…As expected from [18], for all 10 individual full methylomes we reject the hypothesis of a binomial distribution of methylated and unmethylated sites along the genomes, suggesting the existence of region effect methylation (yielding DMRs) meaning that CG are more likely to be methylated if in a highly methylated region, and conversely for unmethylated CG. This is consistent with the autocorrelations in mCG found in [18, 11, 43]. As a first measure of methylated region length, we test the independence between two annotated CG methylation given a minimum genomic distance between them (within one genome).…”

“…Our epimutation model cannot fully describe the observed diversity of epimutations along the genome [18], meaning that the epimutation processes may indeed be more complex than expected [18,25,11,43]. We observe non-independence be-tween annotated methylation sites spanning genomic regions larger than the span of the underlying genealogy (determined by recombination events) which no model can currently describe.…”

“…Our model-based approach provides strong evidence that DMRs cannot simply emerge from spontaneous site-level epimutations that arise according to a Poisson processes along genome. Instead, stochastic changes in region-level methylation states must be the outcome of spontaneous methylation and demethylation events that operate at both the site-and region-level (as corroborated by [54,11,43]).…”

“…Overall, our results demonstrate that our approach can be used in different cases. If the epimutations/genomic markers evolutionary mechanisms are not well understood [54,11,43], our approach provides inference tools to study the markers' rates and distribution process along the genome, without requiring additional experimental data. If the evolution of epimutations/genomic markers are well understood (including a measure of the mutation rates) and can be modeled to described the observed intra-population diversity, these can be integrated to improve the SMC performance.…”

“…Our model-based approach provides strong evidence that DMRs cannot simply emerge from spontaneous site-level epimutations that arise according to a Poisson processes along genome. Instead, stochastic changes in region-level methylation states must be the outcome of spontaneous methylation and demethylation events that operate at both the site- and region-level (as corroborated by [54, 11, 43]). Our epimutation model cannot fully describe the observed diversity of epimutations along the genome [18], meaning that the epimutation processes may indeed be more complex than expected [18, 25, 11, 43].…”