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
Title: Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data Cord-id: j1ddgc26 Document date: 2019_3_18
ID: j1ddgc26
Snippet: 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 often limited in sample size due to the complexity of the experiments. Here, we present an analytical approach that uses summary-level data from DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs whic
Document: 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 often limited in sample size due to the complexity of the experiments. Here, we present an analytical approach that uses summary-level data from DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provide insights into the role of PAIs in complex trait variation.
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