PHi-C: deciphering Hi-C data into polymer dynamics

Soya Shinkai; Masaki Nakagawa; Takeshi Sugawara; Yuichi Togashi; Hiroshi Ochiai; Ryuichiro Nakato; Yuichi Taniguchi; Shuichi Onami

doi:10.1093/nargab/lqaa020

PHi-C: deciphering Hi-C data into polymer dynamics

NAR Genom Bioinform. 2020 Mar 31;2(2):lqaa020. doi: 10.1093/nargab/lqaa020. eCollection 2020 Jun.

Authors

Soya Shinkai^{1

2}, Masaki Nakagawa^{2

3}, Takeshi Sugawara^{2

4}, Yuichi Togashi^{2

5

6}, Hiroshi Ochiai^{5

7}, Ryuichiro Nakato⁸, Yuichi Taniguchi^{7

9}, Shuichi Onami¹

Affiliations

¹ Laboratory for Developmental Dynamics, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan.
² Research Center for the Mathematics on Chromatin Live Dynamics, Hiroshima University, Higashi-Hiroshima 739-8530, Japan.
³ Graduate School of Information Science and Technology, Osaka University, Suita 565-0871, Japan.
⁴ Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
⁵ Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima 739-8526, Japan.
⁶ Laboratory for Cell Field Structure, RIKEN Center for Biosystems Dynamics Research, Higashi-Hiroshima 739-0046, Japan.
⁷ PRESTO, Japan Science and Technology Agency, Kawaguchi 332-0012, Japan.
⁸ Institute for Quantitative Biosciences, The University of Tokyo, Tokyo 113-0032, Japan.
⁹ Laboratory for Cell Systems Control, RIKEN Center for Biosystems Dynamics Research, Suita 565-0874, Japan.

Abstract

Genomes are spatiotemporally organized within the cell nucleus. Genome-wide chromosome conformation capture (Hi-C) technologies have uncovered the 3D genome organization. Furthermore, live-cell imaging experiments have revealed that genomes are functional in 4D. Although computational modeling methods can convert 2D Hi-C data into population-averaged static 3D genome models, exploring 4D genome nature based on 2D Hi-C data remains lacking. Here, we describe a 4D simulation method, PHi-C (polymer dynamics deciphered from Hi-C data), that depicts 4D genome features from 2D Hi-C data by polymer modeling. PHi-C allows users to interpret 2D Hi-C data as physical interaction parameters within single chromosomes. The physical interaction parameters can then be used in the simulations and analyses to demonstrate dynamic characteristics of genomic loci and chromosomes as observed in live-cell imaging experiments. PHi-C is available at https://github.com/soyashinkai/PHi-C.