Statistical Methods for Interrogating Promoter-Enhancer Interactions Originating from Repetitive Regions Using Hi-C Data

• Activity Number: 605 - Recent Statistical Advance in Functional Genomics
• Type: Topic Contributed
• Date/Time: Thursday, August 3, 2017 : 8:30 AM to 10:20 AM
• Sponsor: ENAR
• Author(s): Sunduz Keles* and Ye Zheng
• Companies: University of Wisconsin-Madison and University of Wisconsin
• Keywords: Hi-C ; hierarchical modeling ; 3D genome

Abstract

A series of recently developed chromatin conformation capture-based assays (3C, 4C, 5C and Hi-C) enabled the study of three-dimensional chromosomal structures and elucidated long-range genomic interactions between loci. However, current analysis pipelines of these data discard reads aligning to multiple locations (multi-reads) and, hence, underestimate inter-chromosomal interactions involving repetitive regions. We study this problem in depth and develop a hierarchical model for read allocation. Effective use of multi-reads leads to significant increase in the reproducibility of Hi-C data analysis and identifies novel promoter-enhancer interactions, most notably pertaining ZNF genes.