DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2–5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.
Bibliographical noteFunding Information:
We thank H. Cedar and N. Friedman for insightful discussions. We also thank members of the Dor, Kaplan and Rosenfeld laboratories. This work was supported by grants from GRAIL, Alzheimer’s Drug Discovery Foundation, Human Islet Research Network (nos. HIRN UC4DK116274 and UC4DK104216), the Ernest and Bonnie Beutler Research Program of Excellence in Genomic Medicine, The Alex U Soyka pancreatic cancer fund, The Israel Science Foundation, the Waldholtz/Pakula family, the Robert M. and Marilyn Sternberg Family Charitable Foundation, the Helmsley Charitable Trust and DON Foundation (to Y.D.), Israel Science Foundation (no. 1250/18 to T.K.) and the Center for Interdisciplinary Data Science Research (to T.K., Y.D. and B.G.). N.L. was supported by CIDR Data Science and Leibniz fellowships. Y.D. holds the Walter and Greta Stiel Chair and Research Grant in Heart Studies.
This work was supported by GRAIL, Inc. G.C., J.B., A.A., O.V. and A.J. are employees, shareholders and/or founders at GRAIL, Inc. J.M., J.M., I.F.-F., R.S., Y.D., B.G. and T.K. have filed patents on cfDNA analysis technology. The remaining authors declare no competing interests.
© 2023, The Author(s).