RT Journal Article
SR Electronic
T1 Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.08.29.458098
DO 10.1101/2021.08.29.458098
A1 Brittany Baur
A1 Jacob Schreiber
A1 Junha Shin
A1 Shilu Zhang
A1 Yi Zhang
A1 Mohith Manjunath
A1 Jun S. Song
A1 William Stafford Noble
A1 Sushmita Roy
YR 2021
UL http://biorxiv.org/content/early/2021/08/30/2021.08.29.458098.abstract
AB Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants are typically unknown. Furthermore, a regulatory variant might influence a particular gene’s expression in a cell type or tissue-specific manner. Cell-type specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offers a powerful framework for understanding the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of model cell lines. To address this challenge, we have developed L-HiC-Reg, a Random Forests based regression method to predict high- resolution contact counts in new cell lines, and a network-based framework to identify candidate cell line-specific gene networks targeted by a set of variants from a Genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenome Consortium cell lines, which we used to interpret regulatory SNPs in the NHGRI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including Schizophrenia, Coronary Artery Disease (CAD) and Crohn’s disease. In CAD, we found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and associated network-based analysis pipeline offers a powerful resource to leverage long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.Competing Interest StatementThe authors have declared no competing interest.