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Chromatin is separated into functional domains distinguished by combinatorial patterns of post-translational histone modifications and DNA methylation. Recent studies examining multiple histone modifications have found numerous chromatin states with distinct profiles of chromatin marks and functional enrichments. There are data showing coordinate regulation between DNAme and H3K27me3, which are both involved in the establishment and maintenance of epigenetic gene silencing, but the data are conflicting. Multiple studies have presented evidence to support the theory that PRC2 and DNAme cooperate to achieve silencing, or alternatively that H3K27me3 and DNAme act antagonistically. Here we examine the effect loss of either PRC2 or DNA methyltransferase activity has on the placement of the reciprocal mark in mouse ES cells. We find that DNAme is acting globally to antagonize the placement of H3K27me3, in accordance with recently published results. At least 471,011 domains in the mouse genome acquire H3K27me3 when DNAme is diminished. Of these 466,563 have been shown to be fully methylated in wildtype ES cells, indicating the effects of DNAme on H3K27me3 are direct. In a reciprocal experiment, we examine the effect loss of PRC2 has on the placement of DNAme. In contrast to the global antagonism DNAme has on the placement of H3K27me3, loss of H3K27me3 has a modest effect on DNAme, with only 4% of genes undergoing changes in DNAme, including 861 showing increases and 552 showing losses of overall DNAme. We anticipate that integrating genomic datasets where the effect of loss of a particular epigenetic mark has on the placement of other marks will help elucidate the rules governing epigenetic regulation and what role coordinate regulation of epigenetic marks plays in development and disease.
Pubmed ID: 23326524
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You can easily align, visualize and quantify bisulfite sequence data for CpG methylation analysis.
View all literature mentionsSet of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.
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