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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...

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Autores principales: Zhu, Tianyu, Liu, Jacklyn, Beck, Stephan, Pan, Sun, Capper, David, Lechner, Matt, Thirlwell, Chrissie, Breeze, Charles E., Teschendorff, Andrew E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
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.
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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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