AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants - Yadollah Shahryary; Aikaterini Symeonidi; Rashmi R. Hazarika; Johanna Denkena; Talha Mubeen; Brigitte Hofmeister; Thomas van Gurp; Maria Colomé-Tatché; Koen J.F. Verhoeven; Gerald Tuskan; Robert J. Schmitz; Frank Johannes (Genome Biology, 2020)
Abstract 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.