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PHi-C: deciphering Hi-C data into polymer dynamics
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 metho...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671433/ https://www.ncbi.nlm.nih.gov/pubmed/33575580 http://dx.doi.org/10.1093/nargab/lqaa020 |
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author | Shinkai, Soya Nakagawa, Masaki Sugawara, Takeshi Togashi, Yuichi Ochiai, Hiroshi Nakato, Ryuichiro Taniguchi, Yuichi Onami, Shuichi |
author_facet | Shinkai, Soya Nakagawa, Masaki Sugawara, Takeshi Togashi, Yuichi Ochiai, Hiroshi Nakato, Ryuichiro Taniguchi, Yuichi Onami, Shuichi |
author_sort | Shinkai, Soya |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7671433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76714332021-02-10 PHi-C: deciphering Hi-C data into polymer dynamics Shinkai, Soya Nakagawa, Masaki Sugawara, Takeshi Togashi, Yuichi Ochiai, Hiroshi Nakato, Ryuichiro Taniguchi, Yuichi Onami, Shuichi NAR Genom Bioinform Methods Article 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. Oxford University Press 2020-03-31 /pmc/articles/PMC7671433/ /pubmed/33575580 http://dx.doi.org/10.1093/nargab/lqaa020 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Article Shinkai, Soya Nakagawa, Masaki Sugawara, Takeshi Togashi, Yuichi Ochiai, Hiroshi Nakato, Ryuichiro Taniguchi, Yuichi Onami, Shuichi PHi-C: deciphering Hi-C data into polymer dynamics |
title | PHi-C: deciphering Hi-C data into polymer dynamics |
title_full | PHi-C: deciphering Hi-C data into polymer dynamics |
title_fullStr | PHi-C: deciphering Hi-C data into polymer dynamics |
title_full_unstemmed | PHi-C: deciphering Hi-C data into polymer dynamics |
title_short | PHi-C: deciphering Hi-C data into polymer dynamics |
title_sort | phi-c: deciphering hi-c data into polymer dynamics |
topic | Methods Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671433/ https://www.ncbi.nlm.nih.gov/pubmed/33575580 http://dx.doi.org/10.1093/nargab/lqaa020 |
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