Abstract

DNA methylation is a widespread epigenetic modification that plays an essential role in gene expression through transcriptional regulation and chromatin remodeling. The emergence of whole genome bisulfite sequencing (WGBS) represents an important milestone in the detection of DNA methylation. Characterization of differential methylated regions (DMRs) is fundamental as well for further functional analysis. In this study, we present swDMR (http://sourceforge.net/projects/swdmr/) for the comprehensive analysis of DMRs from whole genome methylation profiles by a sliding window approach. It is an integrated tool designed for WGBS data, which not only implements accessible statistical methods to perform hypothesis test adapted to two or more samples without replicates, but false discovery rate was also controlled by multiple test correction. Downstream analysis tools were also provided, including cluster, annotation and visualization modules. In summary, based on WGBS data, swDMR can produce abundant information of differential methylated regions. As a convenient and flexible tool, we believe swDMR will bring us closer to unveil the potential functional regions involved in epigenetic regulation.

Highlights

  • DNA methylation, catalyzed by DNA methyltransferases (DNMTs), occurs primarily on carbon 5 position of cytosine bases and plays a pivotal role in transcriptional regulation, chromosome stability, genomic imprinting, X-inactivation and tissue differentiation[1,2,3,4,5]

  • To facilitate the identification of differential methylated regions (DMRs) from those methylomes without replicates, we developed swDMR which integrates multiple statistical methods based on a sliding window approach to suffice easy detection, annotation and visualization of DMRs from whole genome bisulfite sequencing (WGBS) across multiple samples

  • Dispersion shrinkage estimate Gamma-Poisson or Beta-Binomial distributions Smoothing t-test Beta-binomial Expectation maximization (EM) algorithm to fit to a bimodal normal distribution Beta-Binomial hierarchical model Design for targeted BS data (RRBS) Combined hotspot and entropy theory Use HMM model to identify DMR. doi:10.1371/journal.pone.0132866.t001

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Summary

Introduction

DNA methylation, catalyzed by DNA methyltransferases (DNMTs), occurs primarily on carbon 5 position of cytosine bases and plays a pivotal role in transcriptional regulation, chromosome stability, genomic imprinting, X-inactivation and tissue differentiation[1,2,3,4,5]. Evidence suggests that regions of methylated DNA are correlated with the expression of several tissuespecific genes[4] and shown influences on activating coding regions across the genome[6, 7]. Aberrant DNA methylation was reported to be implicated in the etiology of various diseases

A New Approach to Identify Differentially Methylated Regions
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