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

Author:

Salviato Elisa1ORCID,Djordjilović Vera2,Hariprakash Judith Mary1,Tagliaferri Ilario1,Pal Koustav1,Ferrari Francesco13ORCID

Affiliation:

1. IFOM, the FIRC Institute of Molecular Oncology, Milan 20139, Italy

2. Department of Economics, Ca’ Foscari University of Venice, Venice 30100, Italy

3. Institute of Molecular Genetics “Luigi Luca Cavalli-Sforza”, National Research Council, Pavia 27100, Italy

Abstract

Abstract 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 hierarchy of structural domains which define chromatin three-dimensional (3D) architecture. Here we introduce a change of perspective 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 map of ETG pairs 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.

Funder

AIRC

AIRC 2015 Start-up

Publisher

Oxford University Press (OUP)

Subject

Genetics

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