Dataset Information

MetMap enables genome-scale Methyltyping for determining methylation states in populations.

ABSTRACT: The ability to assay genome-scale methylation patterns using high-throughput sequencing makes it possible to carry out association studies to determine the relationship between epigenetic variation and phenotype. While bisulfite sequencing can determine a methylome at high resolution, cost inhibits its use in comparative and population studies. MethylSeq, based on sequencing of fragment ends produced by a methylation-sensitive restriction enzyme, is a method for methyltyping (survey of methylation states) and is a site-specific and cost-effective alternative to whole-genome bisulfite sequencing. Despite its advantages, the use of MethylSeq has been restricted by biases in MethylSeq data that complicate the determination of methyltypes. Here we introduce a statistical method, MetMap, that produces corrected site-specific methylation states from MethylSeq experiments and annotates unmethylated islands across the genome. MetMap integrates genome sequence information with experimental data, in a statistically sound and cohesive Bayesian Network. It infers the extent of methylation at individual CGs and across regions, and serves as a framework for comparative methylation analysis within and among species. We validated MetMap's inferences with direct bisulfite sequencing, showing that the methylation status of sites and islands is accurately inferred. We used MetMap to analyze MethylSeq data from four human neutrophil samples, identifying novel, highly unmethylated islands that are invisible to sequence-based annotation strategies. The combination of MethylSeq and MetMap is a powerful and cost-effective tool for determining genome-scale methyltypes suitable for comparative and association studies.

SUBMITTER: Singer M

PROVIDER: S-EPMC2924245 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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MetMap enables genome-scale Methyltyping for determining methylation states in populations.

Singer Meromit M Boffelli Dario D Dhahbi Joseph J Schönhuth Alexander A Schroth Gary P GP Martin David I K DI Pachter Lior L

PLoS computational biology 20100819 8

The ability to assay genome-scale methylation patterns using high-throughput sequencing makes it possible to carry out association studies to determine the relationship between epigenetic variation and phenotype. While bisulfite sequencing can determine a methylome at high resolution, cost inhibits its use in comparative and population studies. MethylSeq, based on sequencing of fragment ends produced by a methylation-sensitive restriction enzyme, is a method for methyltyping (survey of methylati ...[more]

PMID: 20856582

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Project description:Cross-talk between DNA methylation and histone modifications drives the establishment of composite epigenetic signatures and is traditionally studied using correlative rather than direct approaches. Here we present sequential ChIP-bisulfite-sequencing (ChIP- BS-seq) as an approach to quantitatively assess DNA methylation patterns associated with chromatin modifications or chromatin-associated factors directly. A chromatin- immunoprecipitation (ChIP)-capturing step is used to obtain a restricted representation of the genome occupied by the epigenetic feature of interest, for which a single-base resolution DNA methylation map is then generated. When applied to H3 lysine 27 tri- methylation (H3K27me3), we found that H3K27me3 and DNA methylation are compatible throughout most of the genome, except for CpG islands, where these two marks are mutually exclusive. Further ChIP-BS-seq-based analysis in Dnmt triple- knock-out (TKO) embryonic stem cells revealed that total loss of CpG methylation is associated with alteration of H3K27me3 levels throughout the genome: H3K27me3 in localized peaks is decreased while broad local enrichments (BLOCs) of H3K27me3 are formed. At an even broader scale, these BLOCs correspond to regions of high DNA methylation in wild-type ES cells, suggesting that DNA methylation prevents H3K27me3 deposition locally and at megabase scale. Our strategy provides an unique way of investigating global interdependencies between DNA methylation and other chromatin features. ChIP (chromatin immunoprecipitation) is followed by bisulfite conversion and deep sequencing to directly assess DNA methylation levels in captured chromatin fragments (ChIP-BS-seq). We used ChIP-BS-seq to study the potential global cross-talk between H3K27me3 and DNA methylation, which are both linked to repression. First, we used capturing of methylated DNA, followed by bisulfite-deep sequencing (MethylCap-BS-seq). Genomic DNA isolated from normal and tumor colon tissues was used for MethylCap-BS-seq as well as for conventional MethylCap-seq experiments. Second, we performed ChIP-BS-seq on H3K27me3, using HCT116 colon carcinoma cells. Third, to further study the relevance of the observations, we generated genome-wide profiles for H3K27me3 and DNA methylation by conventional ChIP-seq and MethylCap-seq, and RNA-seq, respectively. Finally, we performed H3K27me3-ChIP-BS-seq and MethylCap-seq on wild-type mouse ES cells as well as Dnmt-triple-knockout (TKO) mouse ES cells.

Dataset Information

MetMap enables genome-scale Methyltyping for determining methylation states in populations.

Publications

MetMap enables genome-scale Methyltyping for determining methylation states in populations.

Similar Datasets

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