Inferring and modeling inheritance of differentially methylated changes across multiple generations

Nucleic Acids Research
Pascal BelleauArnaud Droit

Abstract

High-throughput methylation sequencing enables genome-wide detection of differentially methylated sites (DMS) or regions (DMR). Increasing evidence suggests that treatment-induced DMS can be transmitted across generations, but the analysis of induced methylation changes across multiple generations is complicated by the lack of sound statistical methods to evaluate significance levels. Due to software design, DMS detection was usually made on each generation separately, thus disregarding stochastic effects expected when a large number of DMS is detected in each generation. Here, we present a novel method based on Monte Carlo sampling, methylInheritance, to evaluate that the number of conserved DMS between several generations is associated to an effect inherited from a treatment and not randomness. Moreover, we developed an inheritance simulation package, methInheritSim, to demonstrate the performance of the methylInheritance method and to evaluate the power of different experimental designs. Finally, we applied methylInheritance to a DNA methylation dataset obtained from early-life persistent organic pollutants (POPs) exposed Sprague-Dawley female rats and their descendants through a paternal transmission. The results show that ...Continue Reading

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Datasets Mentioned

BETA
GSE109056

Methods Mentioned

BETA
WGBS
RRBS
bisulfite-seq

Software Mentioned

R package
R
methylInheritance
SAMtools
methInheritSim
custom Perl scripts
methylKit
WGBS
GISAIM
R package methylKit

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