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 Colome-Tatch; Koen J. F. Verhoeven; Gerald Tuskan; Robert J. Schmitz; Frank Johannes

doi:10.1186/s13059-020-02161-6

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 Colome-Tatch, Koen J. F. Verhoeven, Gerald Tuskan, Robert J. Schmitz, Frank Johannes

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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 language	English
Article number	260
Number of pages	22
Journal	Genome Biology
Volume	21
Issue number	1
DOIs	https://doi.org/10.1186/s13059-020-02161-6
Publication status	Published - 6-Oct-2020

Keywords

Epimutation
DNA methylation
Plants
Trees
Epigenetics
Epimutation rate
Evolution
Molecular clock
Epigenetic clock
Bioinformatics software tool
R
Bioconductor package
MUTATIONS
PATTERNS
EPIGENOME
MEIOSIS
MAPS

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Shahryary, Y., Symeonidi, A., Hazarika, R. R., Denkena, J., Mubeen, T., Hofmeister, B., van Gurp, T., Colome-Tatch, M., Verhoeven, K. J. F., Tuskan, G., Schmitz, R. J., & Johannes, F. (2020). AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants. Genome Biology, 21(1), Article 260. https://doi.org/10.1186/s13059-020-02161-6

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

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.",

keywords = "Epimutation, DNA methylation, Plants, Trees, Epigenetics, Epimutation rate, Evolution, Molecular clock, Epigenetic clock, Bioinformatics software tool, R, Bioconductor package, MUTATIONS, PATTERNS, EPIGENOME, MEIOSIS, MAPS",

author = "Yadollah Shahryary and Aikaterini Symeonidi and Hazarika, {Rashmi R.} and Johanna Denkena and Talha Mubeen and Brigitte Hofmeister and {van Gurp}, Thomas and Maria Colome-Tatch and Verhoeven, {Koen J. F.} and Gerald Tuskan and Schmitz, {Robert J.} and Frank Johannes",

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month = oct,

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doi = "10.1186/s13059-020-02161-6",

language = "English",

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journal = "Genome Biology",

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Shahryary, Y, Symeonidi, A, Hazarika, RR, Denkena, J, Mubeen, T, Hofmeister, B, van Gurp, T, Colome-Tatch, M, Verhoeven, KJF, Tuskan, G, Schmitz, RJ & Johannes, F 2020, 'AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants', Genome Biology, vol. 21, no. 1, 260. https://doi.org/10.1186/s13059-020-02161-6

TY - JOUR

T1 - AlphaBeta

T2 - computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

AU - Shahryary, Yadollah

AU - Symeonidi, Aikaterini

AU - Hazarika, Rashmi R.

AU - Denkena, Johanna

AU - Mubeen, Talha

AU - Hofmeister, Brigitte

AU - van Gurp, Thomas

AU - Colome-Tatch, Maria

AU - Verhoeven, Koen J. F.

AU - Tuskan, Gerald

AU - Schmitz, Robert J.

AU - Johannes, Frank

PY - 2020/10/6

Y1 - 2020/10/6

N2 - 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.

AB - 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.

KW - Epimutation

KW - DNA methylation

KW - Plants

KW - Trees

KW - Epigenetics

KW - Epimutation rate

KW - Evolution

KW - Molecular clock

KW - Epigenetic clock

KW - Bioinformatics software tool

KW - R

KW - Bioconductor package

KW - MUTATIONS

KW - PATTERNS

KW - EPIGENOME

KW - MEIOSIS

KW - MAPS

U2 - 10.1186/s13059-020-02161-6

DO - 10.1186/s13059-020-02161-6

M3 - Article

SN - 1474-760X

VL - 21

JO - Genome Biology

JF - Genome Biology

IS - 1

M1 - 260

ER -

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

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