Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
Vera Pancaldi, Enrique Carrillo-de-Santa-Pau, Biola Maria Javierre,, David Juan, Peter Fraser, Mikhail Spivakov, Alfonso Valencia, Daniel Rico

TL;DR
This paper introduces a novel chromatin assortativity measure to integrate epigenomic data with 3D genome structure, revealing key proteins and marks mediating chromatin contacts in mouse embryonic stem cells.
Contribution
It presents a new network-based approach to analyze chromatin interactions by combining epigenomic features with 3D genome data, highlighting the role of RNAPII and Polycomb proteins.
Findings
Polycomb proteins show high chromatin assortativity in promoter networks.
Active RNAPII correlates with higher assortativity in promoter interactions.
Distinct epigenomic features characterize different types of chromatin contacts.
Abstract
Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. We use high-resolution Promoter Capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features to the topology of four chromatin interaction networks and identify features localized in connected areas of the…
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Taxonomy
TopicsGenomics and Chromatin Dynamics · Epigenetics and DNA Methylation · Bioinformatics and Genomic Networks
