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

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.

SUBMITTER: Shinkai S

PROVIDER: S-EPMC7671433 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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

Shinkai Soya S Nakagawa Masaki M Sugawara Takeshi T Togashi Yuichi Y Ochiai Hiroshi H Nakato Ryuichiro R Taniguchi Yuichi Y Onami Shuichi S

NAR genomics and bioinformatics 20200331 2

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 ...[more]

PMID: 33575580

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