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Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data
Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from coho...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188843/ https://www.ncbi.nlm.nih.gov/pubmed/32345984 http://dx.doi.org/10.1038/s41467-020-15587-0 |
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author | Wu, Yang Qi, Ting Wang, Huanwei Zhang, Futao Zheng, Zhili Phillips-Cremins, Jennifer E. Deary, Ian J. McRae, Allan F. Wray, Naomi R. Zeng, Jian Yang, Jian |
author_facet | Wu, Yang Qi, Ting Wang, Huanwei Zhang, Futao Zheng, Zhili Phillips-Cremins, Jennifer E. Deary, Ian J. McRae, Allan F. Wray, Naomi R. Zeng, Jian Yang, Jian |
author_sort | Wu, Yang |
collection | PubMed |
description | Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ([Formula: see text] ), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation. |
format | Online Article Text |
id | pubmed-7188843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71888432020-05-01 Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data Wu, Yang Qi, Ting Wang, Huanwei Zhang, Futao Zheng, Zhili Phillips-Cremins, Jennifer E. Deary, Ian J. McRae, Allan F. Wray, Naomi R. Zeng, Jian Yang, Jian Nat Commun Article Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ([Formula: see text] ), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation. Nature Publishing Group UK 2020-04-28 /pmc/articles/PMC7188843/ /pubmed/32345984 http://dx.doi.org/10.1038/s41467-020-15587-0 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Wu, Yang Qi, Ting Wang, Huanwei Zhang, Futao Zheng, Zhili Phillips-Cremins, Jennifer E. Deary, Ian J. McRae, Allan F. Wray, Naomi R. Zeng, Jian Yang, Jian Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title | Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title_full | Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title_fullStr | Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title_full_unstemmed | Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title_short | Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
title_sort | promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188843/ https://www.ncbi.nlm.nih.gov/pubmed/32345984 http://dx.doi.org/10.1038/s41467-020-15587-0 |
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