Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Yang Wu, Ting Qi, Huanwei Wang, Futao Zhang, Zhili Zheng, Jennifer E. Phillips-Cremins, Ian J. Deary, Allan F. McRae, Naomi R. Wray, Jian Zeng and Jian Yang ()
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Yang Wu: The University of Queensland
Ting Qi: The University of Queensland
Huanwei Wang: The University of Queensland
Futao Zhang: The University of Queensland
Zhili Zheng: The University of Queensland
Jennifer E. Phillips-Cremins: University of Pennsylvania
Ian J. Deary: University of Edinburgh
Allan F. McRae: The University of Queensland
Naomi R. Wray: The University of Queensland
Jian Zeng: The University of Queensland
Jian Yang: The University of Queensland

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract 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 ($$n = 1980$$n=1980), 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.

Date: 2020
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DOI: 10.1038/s41467-020-15587-0

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