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Cell Syst. 2019 Jun 26;8(6):494-505.e14. doi: 10.1016/j.cels.2019.05.011.

Comparing 3D Genome Organization in Multiple Species Using Phylo-HMRF.

Author information

1
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
2
Ludwig Institute for Cancer Research, Department of Cellular and Molecular Medicine, Moores Cancer Center and Institute of Genomic Medicine, UCSD School of Medicine, La Jolla, CA 92093, USA.
3
Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
4
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: jianma@cs.cmu.edu.

Abstract

Recent whole-genome mapping approaches for the chromatin interactome have offered new insights into 3D genome organization. However, our knowledge of the evolutionary patterns of 3D genome in mammals remains limited. In particular, there are no existing phylogenetic-model-based methods to analyze chromatin interactions as continuous features. Here, we develop phylogenetic hidden Markov random field (Phylo-HMRF) to identify evolutionary patterns of 3D genome based on multi-species Hi-C data by jointly utilizing spatial constraints among genomic loci and continuous-trait evolutionary models. We used Phylo-HMRF to uncover cross-species 3D genome patterns based on Hi-C data from the same cell type in four primate species (human, chimpanzee, bonobo, and gorilla). The identified evolutionary patterns of 3D genome correlate with features of genome structure and function. This work provides a new framework to analyze multi-species continuous genomic features with spatial constraints and has the potential to help reveal the evolutionary principles of 3D genome organization.

KEYWORDS:

3D genome organization; comparative genomics; phylogenetic hidden Markov random field

PMID:
31229558
PMCID:
PMC6706282
[Available on 2020-06-26]
DOI:
10.1016/j.cels.2019.05.011
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