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

Genome Biology

Brigitte Hofmeister¹  Johanna Denkena²  Maria Colomé-Tatché³  Koen J.F. Verhoeven⁴  Thomas van Gurp⁴  Aikaterini Symeonidi⁵  Talha Mubeen⁶  Yadollah Shahryary⁶  Frank Johannes⁶  Rashmi R. Hazarika⁶  Robert J. Schmitz⁷  Gerald Tuskan⁸ 

[1] Institute of Bioinformatics, 120 East Green Street, 30602, Athens, USA;Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany;Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany;European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, A. Deusinglaan 1, 9713 AV, Groningen, Netherlands;TUM School of Life Sciences Weihenstephan, Technical University of Munich, Emil-Erlenmeyer-Forum 2, 85354, Freising, Germany;Netherlands Institute of Ecology (NIOO-KNAW), Department of Terrestrial Ecology, Wageningen, Wageningen, The Netherlands;Technical University of Munich, Department of Plant Sciences, Liesel-Beckmann-Str. 2, 85354, Freising, Germany;Technical University of Munich, Department of Plant Sciences, Liesel-Beckmann-Str. 2, 85354, Freising, Germany;Technical University of Munich, Institute for Advanced Study, Lichtenbergstr. 2a, 85748, Garching, Germany;Technical University of Munich, Institute for Advanced Study, Lichtenbergstr. 2a, 85748, Garching, Germany;Department of Genetics, The University of Georgia, 120 East Green Street, 30602, Athens, USA;The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, USA;

关键词: Epimutation;    DNA methylation;    Plants;    Trees;    Epigenetics;    Epimutation rate;    Evolution;    Molecular clock;    Epigenetic clock;    Bioinformatics software tool;    R/Bioconductor package;   

DOI  :  10.1186/s13059-020-02161-6

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY