Abstract
BackgroundDNA methylation is an important type of epigenetic modification involved in gene regulation. Although strong DNA methylation at promoters is widely recognized to be associated with transcriptional repression, many aspects of DNA methylation remain not fully understood, including the quantitative relationships between DNA methylation and expression levels, and the individual roles of promoter and gene body methylation.ResultsHere we present an integrated analysis of whole-genome bisulfite sequencing and RNA sequencing data from human samples and cell lines. We find that while promoter methylation inversely correlates with gene expression as generally observed, the repressive effect is clear only on genes with a very high DNA methylation level. By means of statistical modeling, we find that DNA methylation is indicative of the expression class of a gene in general, but gene body methylation is a better indicator than promoter methylation. These findings are general in that a model constructed from a sample or cell line could accurately fit the unseen data from another. We further find that promoter and gene body methylation have minimal redundancy, and either one is sufficient to signify low expression. Finally, we obtain increased modeling power by integrating histone modification data with the DNA methylation data, showing that neither type of information fully subsumes the other.ConclusionOur results suggest that DNA methylation outside promoters also plays critical roles in gene regulation. Future studies on gene regulatory mechanisms and disease-associated differential methylation should pay more attention to DNA methylation at gene bodies and other non-promoter regions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0408-0) contains supplementary material, which is available to authorized users.
Highlights
DNA methylation is an important type of epigenetic modification involved in gene regulation
Data and global patterns We obtained whole-methylome bisulfite sequencing data at single-base resolution from peripheral blood mononuclear cells (PBMCs) of three individuals in a family trio: Father (F), Mother (M) and Daughter (D) from our previous study (Lee HM et al, Discovery of type 2 diabetes genes using a multiomic analysis in a family trio, submitted)
As two of the three samples in our study were obtained from individuals with T2D (Lee HM et al, Discovery of type 2 diabetes genes using a multiomic analysis in a family trio, submitted), our results indicated that our data were able to capture relevant information related to the physiological status of the samples
Summary
DNA methylation is an important type of epigenetic modification involved in gene regulation. Various high-throughput methods have been invented for large-scale detection of methylation events [8,12,13,14] These methods differ in the way genomic regions enriched for methylated or unmethylated DNA are identified, and how genomic locations of these regions or their sequences are determined. The former includes the use of methylation-sensitive restriction enzyme digestion [15,16], immunoprecipitation [17,18,19], affinity capture [20,21], and bisulfite conversion of unmethylated cytosines to uracils [2,3,4,22]. These methods have been extensively compared in terms of their genomic coverage, resolution, cost, consistency and context-specific bias [23,24]
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