Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory network

A growing amount of evidence in literature suggests that germline sequence variants and somatic mutations in non-coding distal regulatory elements may be crucial for defining disease risk and prognostic stratification of patients, in genetic disorders as well as in cancer. Their functional interpretation is challenging because genome-wide enhancer-target gene (ETG) pairing is an open problem in genomics. The solutions proposed so far do not account for the most updated knowledge on chromatin three-dimensional (3D) architecture, which is organized in a hierarchy of structural domains. Here we introduce a paradigm shift based on the definition of multi-scale structural chromatin domains, integrated in a statistical framework to define ETG pairs. In this work i) we develop a computational and statistical framework to reconstruct a comprehensive ETG regulatory network leveraging functional genomics data; ii) we demonstrate that the incorporation of chromatin 3D architecture information improves ETG pairing accuracy; and iii) we use multiple experimental datasets to extensively benchmark our method against previous solutions for the genome-wide reconstruction of ETG pairs. This solution will facilitate the annotation and interpretation of sequence variants in distal non-coding regulatory elements. We expect this to be especially helpful in clinically oriented applications of whole genome sequencing in cancer and undiagnosed genetic diseases research.