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...

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Published inNature communications Vol. 11; no. 1; p. 2061
Main Authors 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
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 28.04.2020
Nature Publishing Group UK
Nature Portfolio
Subjects
Chromatin
Chromatin - genetics
Crohn Disease - genetics
Data Analysis
Deoxyribonucleic acid
DNA
DNA methylation
DNA Methylation - genetics
DNA Replication - genetics
Enhancers
Epigenomics
Gene expression
Gene Expression Regulation
Gene mapping
Gene regulation
Genetic analysis
Genome-Wide Association Study
Humans
Measurement methods
Peripheral blood
Polymorphism, Single Nucleotide - genetics
Promoter Regions, Genetic
Quantitative trait loci
Quantitative Trait Loci - genetics
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Summary: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.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-15587-0