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Nucleic Acids Res. 2017 Apr 20;45(7):3663-3673. doi: 10.1093/nar/gkx172.

Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings.

Author information

1
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
2
Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.

Abstract

Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (>50 Mb) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to model chromatin dynamics using Hi-C data. We show that the GNM can identify spatial couplings at multiple scales: it can quantify the correlated fluctuations in the positions of gene loci, find large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with genome-wide experimental measurements. We use the GNM to identify novel cross-correlated distal domains (CCDDs) representing pairs of regions distinguished by their long-range dynamic coupling and show that CCDDs are associated with increased gene co-expression. Together, these results show that GNM provides a mathematically well-founded unified framework for modeling chromatin dynamics and assessing the structural basis of genome-wide observations.

PMID:
28334818
PMCID:
PMC5397156
DOI:
10.1093/nar/gkx172
[Indexed for MEDLINE]
Free PMC Article

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