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Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease

Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expres...

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Autores principales: Hou, Lei, Xiong, Xushen, Park, Yongjin, Boix, Carles, James, Benjamin, Sun, Na, He, Liang, Patel, Aman, Zhang, Zhizhuo, Molinie, Benoit, Van Wittenberghe, Nicholas, Steelman, Scott, Nusbaum, Chad, Aguet, François, Ardlie, Kristin G., Kellis, Manolis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562256/
https://www.ncbi.nlm.nih.gov/pubmed/37770633
http://dx.doi.org/10.1038/s41588-023-01509-5
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author Hou, Lei
Xiong, Xushen
Park, Yongjin
Boix, Carles
James, Benjamin
Sun, Na
He, Liang
Patel, Aman
Zhang, Zhizhuo
Molinie, Benoit
Van Wittenberghe, Nicholas
Steelman, Scott
Nusbaum, Chad
Aguet, François
Ardlie, Kristin G.
Kellis, Manolis
author_facet Hou, Lei
Xiong, Xushen
Park, Yongjin
Boix, Carles
James, Benjamin
Sun, Na
He, Liang
Patel, Aman
Zhang, Zhizhuo
Molinie, Benoit
Van Wittenberghe, Nicholas
Steelman, Scott
Nusbaum, Chad
Aguet, François
Ardlie, Kristin G.
Kellis, Manolis
author_sort Hou, Lei
collection PubMed
description Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE–gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP–ARE–gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.
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spelling pubmed-105622562023-10-11 Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease Hou, Lei Xiong, Xushen Park, Yongjin Boix, Carles James, Benjamin Sun, Na He, Liang Patel, Aman Zhang, Zhizhuo Molinie, Benoit Van Wittenberghe, Nicholas Steelman, Scott Nusbaum, Chad Aguet, François Ardlie, Kristin G. Kellis, Manolis Nat Genet Article Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE–gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP–ARE–gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia. Nature Publishing Group US 2023-09-28 2023 /pmc/articles/PMC10562256/ /pubmed/37770633 http://dx.doi.org/10.1038/s41588-023-01509-5 Text en © The Author(s) 2023 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 Article
Hou, Lei
Xiong, Xushen
Park, Yongjin
Boix, Carles
James, Benjamin
Sun, Na
He, Liang
Patel, Aman
Zhang, Zhizhuo
Molinie, Benoit
Van Wittenberghe, Nicholas
Steelman, Scott
Nusbaum, Chad
Aguet, François
Ardlie, Kristin G.
Kellis, Manolis
Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title_full Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title_fullStr Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title_full_unstemmed Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title_short Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
title_sort multitissue h3k27ac profiling of gtex samples links epigenomic variation to disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562256/
https://www.ncbi.nlm.nih.gov/pubmed/37770633
http://dx.doi.org/10.1038/s41588-023-01509-5
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