Zhu, Tianyu;
Liu, Jacklyn;
Beck, Stephan;
Pan, Sun;
Capper, David;
Lechner, Matt;
Thirlwell, Chrissie;
... Teschendorff, Andrew E; + view all
(2022)
A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution.
Nature Methods
, 19
pp. 296-306.
10.1038/s41592-022-01412-7.
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Abstract
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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