AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants-Reference-Cited by-同舟云学术

AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

Published:2020-10-06 Issue:1 Volume:21 Page:
ISSN:1474-760X
Container-title:Genome Biology
language:en
Short-container-title:Genome Biol

Author:

Shahryary Yadollah,Symeonidi Aikaterini,Hazarika Rashmi R.,Denkena Johanna,Mubeen Talha,Hofmeister Brigitte,van Gurp Thomas,Colomé-Tatché Maria,Verhoeven Koen J.F.,Tuskan Gerald,Schmitz Robert J.,Johannes Frank

Abstract

AbstractStochastic 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.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s13059-020-02161-6.pdf

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