Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Mapping of variable DNA methylation across multiple cell types defines a dynamic regulatory landscape of the human genome

ABSTRACT: DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Many studies have mapped DNA methylation changes associated with embryogenesis, cell differentiation and cancer at a genome-wide scale. Our understanding of genome-wide DNA methylation changes in a developmental or disease-related context has been steadily growing. However, the investigation of which CpGs are variably methylated in different normal cell or tissue types is still limited. Here we present an in-depth analysis of 54 single-CpG-resolution DNA methylomes of normal human cell types by integrating high-throughput sequencing-based methylation data. We find that the percentage of unmethylated CpGs is relatively fixed regardless of cell type. However, which CpGs are unmethylated is cell-type specific. We categorize the 26 million human autosomal CpGs based on their methylation levels across multiple cell types to identify variably methylated CpGs. Among all the autosomal CpGs, 22.6% exhibit variable DNA methylation across cell types included in our study. These variably methylated CpGs form 66 thousand variably methylated regions (VMRs), encompassing 11% of the genome. By integrating a multitude of genomic data, we found that VMRs enrich for histone modifications indicative of enhancers, suggesting their role as regulatory elements marking cell type specificity. VMRs enrich for transcription factor binding sites in a tissue-dependent manner. Importantly, they enrich for GWAS variants, suggesting VMRs could potentially be implicated in disease and complex traits. Taken together, our results highlight the link among CpG methylation variation, genetic variation and disease risk in a tissue-specific manner for many human cell types. Processed data includes new Samples and 75 Samples from GSE16368 and 2 Samples from GSE51565.

ORGANISM(S): Homo sapiens

SUBMITTER: Daofeng Li

PROVIDER: E-GEOD-69894 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Mapping of Variable DNA Methylation Across Multiple Cell Types Defines a Dynamic Regulatory Landscape of the Human Genome.

Gu Junchen J Stevens Michael M Xing Xiaoyun X Li Daofeng D Zhang Bo B Payton Jacqueline E JE Oltz Eugene M EM Jarvis James N JN Jiang Kaiyu K Cicero Theodore T Costello Joseph F JF Wang Ting T

G3 (Bethesda, Md.) 20160407 4

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Many studies have mapped DNA methylation changes associated with embryogenesis, cell differentiation, and cancer at a genome-wide scale. Our understanding of genome-wide DNA methylation changes in a developmental or disease-related context has been steadily growing. However, the investigation of which CpGs are variably methylated in different normal cell or tissue types is still limited. H ...[more]

PMID: 26888867

Similar Datasets

Project description:Purpose: We characterized genome-wide DNA methylation profiles (methylome) in purified peripheral blood monocytes (PBMs) from 18 healthy postmenopausal Caucasian females aged 50-56 years. Methods: DNA methylome of Human Peripheral Blood Monocytes were generated by methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq), using Illumina GAIIx. The sequence reads that passed quality filters were analyzed using MEDIPS package. Targeted methylation validation analysis was performed by using MassARRAY EpiTYPER assays. Genome-wide gene expression profiles have been obtained for 7 of the 18 subjects by using Affymetrix 1.0 Human Exon ST arrays following the manufacturer's recommended protocols. Results: Using MeDIP-seq,a total of approximately 283 million reads were uniquely aligned to human genome (Build NCBI37, HG19), resulting in average ~16 million uniquely aligned high quality reads per sample. Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. We found that approximately 24% CpG islands (CGIs) were highly methylated in PBMs. Further characterization of CGIs with respect to their relative locations to RefSeq genes revealed that the highly methylated CGIs were largely enriched (~89%) in CGIs located in gene bodies and intergenic regions. By integration of the methylome data with genome-wide PBM gene expression data, we found negative correlation between promoter methylation levels and gene transcription levels when comparing groups of genes with different expression levels, and this relationship was consistently observed across promoters with high to low CpG densities. Furthermore, we observed a modest but significant excess (permutation p<0.0001) of genes showing negative correlation between inter-individual promoter methylation and transcription levels, particularly for genes associated with CpG-rich promoters. Across the 18 individual PBM methylomes, we also identified genomic regions that were constitutively highly methylated in PBMs as well as regions showing large inter-individual variability. Conclusions: This study represents a comprehensive analysis of the PBM methylome and our data provides a valuable resource for future epigenomic and multi-omic studies exploring biological and disease-related regulatory mechanisms in PBMs. DNA methylome of human peripheral blood monocytes were generated by MeDIP-seq, using Illumina GAIIx.

Dataset Information

Mapping of variable DNA methylation across multiple cell types defines a dynamic regulatory landscape of the human genome

Publications

Mapping of Variable DNA Methylation Across Multiple Cell Types Defines a Dynamic Regulatory Landscape of the Human Genome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets