A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution
Open accessAbstract
Bulk-tissue DNA methylomes represent an average over many different cell types, hampering our understanding of cell-type-specific contributions to disease development. As single-cell methylomics is not scalable to large cohorts of individuals, cost-effective computational solutions are needed, yet current methods are limited to tissues such as blood. Here we leverage the high-resolution nature of tissue-specific single-cell RNA-sequencing datasets to construct a DNA methylation atlas defined for 13 solid tissue types and 40 cell types. We comprehensively validate this atlas in independent bulk and single-nucleus DNA methylation datasets. We demonstrate that it correctly predicts the cell of origin of diverse cancer types and discovers new prognostic associations in olfactory neuroblastoma and stage 2 melanoma. In brain, the atlas predicts a neuronal origin for schizophrenia, with neuron-specific differential DNA methylation enriched for corresponding genome-wide association study risk loci. In summary, the DNA methylation atlas enables the decomposition of 13 different human tissue types at a high cellular resolution, paving the way for an improved interpretation of epigenetic data.
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The unique methylation profile of cells can be used to identify their tissue of origin.
“and therefore the unique methylation profile of cells can be used to identify their tissue of origin [33, 59].”
From Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression (2024) · cites this paper as [59]
The Abstract (page unavailable) describes a DNA methylation atlas for 13 tissues and 40 cell types that predicts the cell of origin of diverse cancers. The ‘DNAm-atlas identifies cell of origin in pancreatic cancer’ section (page unavailable) reports distinguishing ductal from endocrine origins of pancreatic tumors. This supports using methylation data to infer cellular origin in that setting, but it does not establish that an individual cell’s unique methylation profile identifies its tissue of origin. (LLM, conf=0.82)
Experimental — accuracy not yet measuredSome DNA methylation patterns are associated with specific types of cancers and can be used to differentiate between various tumor types.
“it has also been described that some DNA methylation patterns are associated with specific types of cancers and therefore can be used to differentiate between various tumor types [56, 59].”
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- Authors
- Zhu, T., Liu, J., Beck, S., Pan, S., Capper, D., Lechner, M., Thirlwell, C., Breeze, C. E., & Teschendorff, A. E.
- Affiliations
- Shanghai Institute of Nutrition and Health (CN)
- University College London (GB)
- German Cancer Research Center (DE)
- Barts Health NHS Trust (GB)
- Altius Institute for Biomedical Sciences (US)
- Corresponding author
- Breeze, Charles E.
- Teschendorff, Andrew E.
- ORCID
- Venue
- Nature Methods
- Published
- 2022-03
- Volume
- 19
- Issue
- 3
- Pages
- 296-306
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC8916958
- OpenAlex
- W4221136004
- Cited by
- 103
- References
- 99
- Citations by year
- 2026: 14 · 2025: 21 · 2024: 33 · 2023: 26 · 2022: 9
- FWCI
- 7.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Methods (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Science Foundation of China | National Natural Science Foundation of China-Yunnan Joint Fund (31970632)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- cell-type resolution, single-cell RNA sequencing, tumor cell of origin, olfactory neuroblastoma, melanoma, schizophrenia, neuronal origin
- MeSH terms
- Epigenome, Humans, Neurons, CpG Islands, DNA Methylation, Epigenesis, Genetic, Genome-Wide Association Study, Epigenomics
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