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 (Corresponding author), Frank Johannes (Corresponding author)

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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.

Original languageEnglish
Article number260
JournalGenome Biology
Volume21
Issue number1
DOIs
Publication statusPublished - 06 Oct 2020

Keywords

  • Bioinformatics software tool
  • DNA methylation
  • Epigenetic clock
  • Epigenetics
  • Epimutation
  • Epimutation rate
  • Evolution
  • Molecular clock
  • Plants
  • R/Bioconductor package
  • Trees
  • international
  • Plan_S-Compliant_OA

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