Methylation profiling by high throughput sequencing
Summary
DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing of 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.
Overall design
To portray the genome-wide patterns of DNA methylation across a variety of cell types, we obtained 205 samples of freshly isolated healthy adult tissue samples from 137 consented donors undergoing a variety of surgical procedures (ages 3-83). We dissociated tissue samples into single cell suspensions, and used lineage-specific antibodies to cell type specific surface markers to FACS purify cell populations covering 39 primary cell-types. The purity of cell types was confirmed using RT-qPCR for cell type specific gene expression markers, and assessing known tissue-specific methylation markers when possible (Methods, Supplemental Fig. S1). We then subjected cell type-specific genomic DNA to WGBS and sequenced at a mean depth of >30X, using 150bp-long paired-end reads, with an average fragment size of 174bp.
**Raw fastq files are available at the European Genome-phenome Archive (EGA) under study accession number: EGAS00001006791**
Please note that the records have been updated with the processed data generated with the *hg38* reference on May 17, 2022.
Please note that the GSM6810003-GSM6810048 records have been updated with the processed data generated with the *hg38* reference on Aug 20, 2024
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