+The Human Methylation Atlas tracks display genome-wide DNA methylation profiles from +deep whole-genome bisulfite sequencing (WGBS) of 39 primary human cell types +sorted from 205 healthy tissue samples. This comprehensive resource enables fragment-level +analysis across thousands of unique markers, providing a detailed reference for +cell-type-specific methylation patterns. +
+ ++The atlas comprises two track sets: +
+ ++DNA methylation patterns are highly reproducible across individuals of the same cell type +(>99.5% identical), reflecting the robustness of cell identity programs. Unsupervised +clustering of these methylomes recapitulates key elements of tissue ontogeny and +developmental lineage relationships. +
+ ++Signal tracks display methylation beta values on a 0-1 scale, where 0 indicates fully +unmethylated CpGs and 1 indicates fully methylated CpGs. A value of -1 indicates +missing data. For optimal comparison across cell types, set the vertical viewing range +to 0-1 with auto-scale off. +
+ ++Merged signal tracks aggregate data across biological replicates for each cell type. +Individual replicate tracks are available for detailed analysis. +
+ ++Tracks are colored by tissue/cell type category as follows: +
+ +| Color | Cell Type(s) |
|---|---|
| Neurons | |
| Oligodendrocytes | |
| Thyroid Epithelium | |
| Prostate Epithelium | |
| Bladder Epithelium | |
| Heart Cardiomyocytes | |
| Smooth Muscle | |
| Heart Fibroblasts | |
| Skeletal Muscle | |
| Erythrocyte Progenitors | |
| Blood Granulocytes | |
| Blood Monocytes/Macrophages | |
| Blood T Cells | |
| Blood B Cells | |
| Blood NK Cells | |
| Pancreas Beta Cells | |
| Pancreas Alpha Cells | |
| Pancreas Delta Cells | |
| Pancreas Duct Cells | |
| Pancreas Acinar Cells | |
| Colon Epithelium | |
| Colon Fibroblasts | |
| Small Intestine Epithelium | |
| Gastric Epithelium | |
| Gallbladder | |
| Liver Hepatocytes | |
| Lung Bronchus Epithelium | |
| Lung Alveolar Epithelium | |
| Kidney Epithelium | |
| Endothelial | |
| Breast Basal Epithelium | |
| Breast Luminal Epithelium | |
| Fallopian Epithelium | |
| Ovary Epithelium | |
| Adipocytes | |
| Epidermal Keratinocytes | |
| Dermal Fibroblasts | |
| Bone Osteoblasts | |
| Head Neck Epithelium |
+Primary human cells were isolated from freshly dissociated adult healthy tissues using +fluorescence-activated cell sorting (FACS), yielding high-purity preparations across major +cell lineages. A total of 205 samples representing 77 primary cell types were collected from +137 consenting donors and merged into 39 cell type groups based on methylation similarity. +Average sample purity exceeded 90% as determined by flow cytometry, gene expression, and +DNA methylation analysis. +
+ ++Whole-genome bisulfite sequencing was performed using 150 bp paired-end reads at an average +sequencing depth of 30× (minimum 6.62×). Libraries were prepared using the +Accel-NGS Methyl-Seq DNA library preparation kit and sequenced on the Illumina NovaSeq 6000 +platform. +
+ ++Reads were mapped to the human genome (hg38) using bwa-meth, deduplicated with Sambamba, +and processed into per-CpG methylation calls. The genome was segmented into 7.1 million +non-overlapping methylation blocks using a multi-channel dynamic programming algorithm +that identifies regions of homogeneous methylation across samples. +
+ ++Cell-type-specific differentially methylated regions were identified using a one-versus-all +comparison approach. Regions uniquely unmethylated in specific cell types were found to be +enriched for transcriptional enhancers and tissue-specific transcription factor binding motifs. +
+ ++Data processing was performed using +wgbstools, an open-source +computational suite for DNA methylation sequencing data representation, visualization, +and analysis. +
+ ++The raw data for these tracks can be explored interactively using the +Table Browser or the +Data Integrator. +For automated analysis, the data may also be queried from our +REST API. +
+ ++The complete dataset, including all WGBS data files and processed methylation calls, +is available from GEO accession +GSE186458. +
+ ++For questions regarding the data, please contact +Prof. Tommy Kaplan at the Hebrew +University of Jerusalem. +
+ ++Data generation and analysis were performed at the Hebrew University of Jerusalem by the +Dor, Kaplan, and Glaser laboratories and collaborators. Sample collection involved +collaboration with Hadassah Medical Center, Oregon Health & Science University, +Karolinska Institute, and University of Alberta. +
+ ++Track development and UCSC Genome Browser integration by the +UCSC Genome Browser Group. +
+ ++Loyfer N, Magenheim J, Peretz A, Cann G, Bredno J, Klochendler A, Fox-Fisher I, +Shabi-Porat S, Hecht M, Pelet T et al. + +A DNA methylation atlas of normal human cell types. +Nature. 2023 Jan;613(7943):355-364. +PMID: 36599988 +
+ ++Loyfer N, Magenheim J, Dor Y, Kaplan T. + +wgbstools: a computational suite for DNA methylation sequencing data representation, +visualization, and analysis. +bioRxiv. 2024. +
+