Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex
Author(s) -
Sepideh Babaei,
Ahmed Mahfouz,
Marc Hulsman,
Boudewijn P. F. Lelieveldt,
Jeroen de Ridder,
Marcel J. T. Reinders
Publication year - 2015
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1004221
Subject(s) - chromatin , chia pet , gene expression , computational biology , regulation of gene expression , biology , gene , topology (electrical circuits) , nucleus , genetics , microbiology and biotechnology , chromatin remodeling , mathematics , combinatorics
The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).
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