It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
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 (), 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.
Promoter-anchored chromatin interaction (PAI) is a mechanism by which gene expression is regulated, but methods to measure PAIs are costly and currently not scalable. Here, the authors develop an approach by which PAIs can be predicted using summary-level data from methylation QTL studies.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details







1 The University of Queensland, Institute for Molecular Bioscience, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537)
2 The University of Queensland, Institute for Molecular Bioscience, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537); Wenzhou Medical University, Institute for Advanced Research, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
3 University of Pennsylvania, Department of Bioengineering, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972)
4 University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988); University of Edinburgh, Department of Psychology, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
5 The University of Queensland, Institute for Molecular Bioscience, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537); The University of Queensland, Queensland Brain Institute, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537)