Description
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.
Human Methylation Atlas Summary consists of the following subtracks:
- All unmethylated regions track displays a comprehensive catalogue of unmethylated
genomic regions identified independently for each of the 39 cell types in the atlas
using a fragment-level analysis, retaining regions where at least 85% of sequenced DNA
fragments covering four or more CpGs are unmethylated.
- Putative enhancers from unmethylated regions track displays a genome-wide catalogue of
putative transcriptional enhancers derived from regions where at least 85% of sequenced
DNA fragments are unmethylated, and that overlap H3K27ac but not H3K4me3 ChIP-seq peaks,
distinguishing distal enhancer elements from active promoters. This track covers 32 of
the 39 cell types, as H3K27ac ChIP-seq data were unavailable for Adipocytes, Bone
Osteoblasts, Erythrocyte Progenitors, Fallopian Epithelium, Gallbladder, Ovary Epithelium,
and Smooth Muscle.
- Top 250 unmethylated regions specific to each cell type track displays the top 250
genomic regions most specifically unmethylated in each of the 39 cell types, identified
using a one-versus-all comparison approach. Some regions are shared across closely related
cell types (for example, Neuron:Oligodend or Colon-Ep:Gastric-Ep:Small-Int-Ep),
indicating they are unmethylated across those cell types but methylated in all others in
the atlas.
Unsupervised clustering of these methylomes recapitulates key elements of tissue ontogeny and
developmental lineage relationships.
Display Conventions and Configuration
Track Colors
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 |
Items in these tracks can be filtered by:
- Cell/Tissue Type - The cell or tissue type associated with each region.
Filter values include the 39 cell types for the All Unmethylated Regions track,
32 cell types for the Putative Enhancers track, and 39 cell types plus combined
cell type groups for the Top 250 Unmethylated Regions track. The default is no
filtering.
Methods
Sample Collection and Sequencing
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. Some cell types showed lower purity, including colon fibroblasts (78%),
smooth muscle cells (82%), endothelial cells (86%), and adipocytes (87%).
Several cell types are absent from the atlas, typically due to limited availability of primary
material. These include osteoblasts, cholangiocytes, cells of the adrenal gland, urethral
epithelium, and haematopoietic stem cells. Subpopulations of interest, such as distinct neuronal or
lymphocyte subtypes, were also not resolved separately.
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.
Processing and Analysis
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.
Data Access
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.
Credits
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.
References
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, Rosenski J, Kaplan T.
wgbstools: a computational suite for DNA methylation sequencing data analysis.
Life Sci Alliance. 2026 Apr;9(4):e202503514.
PMID: 41611450