PT  - JOURNAL ARTICLE
AU  - Patrick Hüther
AU  - Jörg Hagmann
AU  - Adam Nunn
AU  - Ioanna Kakoulidou
AU  - Rahul Pisupati
AU  - David Langenberger
AU  - Detlef Weigel
AU  - Frank Johannes
AU  - Sebastian J. Schultheiss
AU  - Claude Becker
TI  - MethylScore, a pipeline for accurate and context-aware identification of differentially methylated regions from population-scale plant WGBS data
AID  - 10.1101/2022.01.06.475031
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.01.06.475031
4099  - http://biorxiv.org/content/early/2022/01/06/2022.01.06.475031.short
4100  - http://biorxiv.org/content/early/2022/01/06/2022.01.06.475031.full
AB  - Whole-genome bisulfite sequencing (WGBS) is the standard method for profiling DNA methylation at single-nucleotide resolution. Many WGBS-based studies aim to identify biologically relevant loci that display differential methylation between genotypes, treatment groups, tissues, or developmental stages. Over the years, different tools have been developed to extract differentially methylated regions (DMRs) from whole-genome data. Often, such tools are built upon assumptions from mammalian data and do not consider the substantially more complex and variable nature of plant DNA methylation. Here, we present MethylScore, a pipeline to analyze WGBS data and to account for plant-specific DNA methylation properties. MethylScore processes data from genomic alignments to DMR output and is designed to be usable by novice and expert users alike. It uses an unsupervised machine learning approach to segment the genome by classification into states of high and low methylation, substantially reducing the number of necessary statistical tests while increasing the signal-to-noise ratio and the statistical power. We show how MethylScore can identify DMRs from hundreds of samples and how its data-driven approach can stratify associated samples without prior information. We identify DMRs in the A. thaliana 1001 Genomes dataset to unveil known and unknown genotype-epigenotype associations. MethylScore is an accessible pipeline for plant WGBS data, with unprecedented features for DMR calling in small- and large-scale datasets; it is built as a Nextflow pipeline and its source code is available at https://github.com/Computomics/MethylScore.Competing Interest StatementThe authors declare the following competing interests: JH is currently an employee of Computomics GmbH. S.J.S. is currently the CEO of and holds shares in Computomics GmbH. A.N. is currently an employee of ecSeq Bioinformatics GmbH. D.L. is currently the CEO of and holds shares in ecSeq Bioinformatics GmbH.