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A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution
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 c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916958/ https://www.ncbi.nlm.nih.gov/pubmed/35277705 http://dx.doi.org/10.1038/s41592-022-01412-7 |
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author | Zhu, Tianyu Liu, Jacklyn Beck, Stephan Pan, Sun Capper, David Lechner, Matt Thirlwell, Chrissie Breeze, Charles E. Teschendorff, Andrew E. |
author_facet | Zhu, Tianyu Liu, Jacklyn Beck, Stephan Pan, Sun Capper, David Lechner, Matt Thirlwell, Chrissie Breeze, Charles E. Teschendorff, Andrew E. |
author_sort | Zhu, Tianyu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8916958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89169582022-03-25 A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution Zhu, Tianyu Liu, Jacklyn Beck, Stephan Pan, Sun Capper, David Lechner, Matt Thirlwell, Chrissie Breeze, Charles E. Teschendorff, Andrew E. Nat Methods Resource 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. Nature Publishing Group US 2022-03-11 2022 /pmc/articles/PMC8916958/ /pubmed/35277705 http://dx.doi.org/10.1038/s41592-022-01412-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Resource Zhu, Tianyu Liu, Jacklyn Beck, Stephan Pan, Sun Capper, David Lechner, Matt Thirlwell, Chrissie Breeze, Charles E. Teschendorff, Andrew E. A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title | A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title_full | A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title_fullStr | A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title_full_unstemmed | A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title_short | A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
title_sort | pan-tissue dna methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916958/ https://www.ncbi.nlm.nih.gov/pubmed/35277705 http://dx.doi.org/10.1038/s41592-022-01412-7 |
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