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Comparing 3D genome organization in multiple species using Phylo-HMRF

View ORCID ProfileYang Yang, Yang Zhang, Bing Ren, Jesse Dixon, View ORCID ProfileJian Ma
doi: https://doi.org/10.1101/552505
Yang Yang
1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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Yang Zhang
1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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Bing Ren
2Ludwig 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
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Jesse Dixon
3Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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Jian Ma
1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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  • For correspondence: jianma@cs.cmu.edu
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Abstract

Recent developments in whole-genome mapping approaches for the chromatin interactome (such as Hi-C) have offered new insights into 3D genome organization. However, our knowledge of the evolutionary patterns of 3D genome structures in mammalian species remains surprisingly limited. In particular, there are no existing phylogenetic-model based methods to analyze chromatin interactions as continuous features across different species. Here we develop a new probabilistic model, named phylogenetic hidden Markov random field (Phylo-HMRF), to identify evolutionary patterns of 3D genome structures based on multi-species Hi-C data by jointly utilizing spatial constraints among genomic loci and continuous-trait evolutionary models. The effectiveness of Phylo-HMRF is demonstrated in both simulation evaluation and application to real Hi-C data. 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 organization correlate with features of genome structure and function, including long-range interactions, topologically-associating domains (TADs), and replication timing patterns. This work provides a new framework that utilizes general types of spatial constraints to identify evolutionary patterns of continuous genomic features and has the potential to reveal the evolutionary principles of 3D genome organization.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 19, 2019.
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Comparing 3D genome organization in multiple species using Phylo-HMRF
Yang Yang, Yang Zhang, Bing Ren, Jesse Dixon, Jian Ma
bioRxiv 552505; doi: https://doi.org/10.1101/552505
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Comparing 3D genome organization in multiple species using Phylo-HMRF
Yang Yang, Yang Zhang, Bing Ren, Jesse Dixon, Jian Ma
bioRxiv 552505; doi: https://doi.org/10.1101/552505

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