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Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections
Recent advances in genome‐wide technologies have enabled analyses using small cell numbers of even single cells. However, obtaining tissue epigenomes with cell‐type resolution from large organs and tissues still remains challenging, especially when the available material is limited. Here, we present...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564819/ https://www.ncbi.nlm.nih.gov/pubmed/34730297 http://dx.doi.org/10.15252/msb.202110323 |
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author | Maehara, Kazumitsu Tomimatsu, Kosuke Harada, Akihito Tanaka, Kaori Sato, Shoko Fukuoka, Megumi Okada, Seiji Handa, Tetsuya Kurumizaka, Hitoshi Saitoh, Noriko Kimura, Hiroshi Ohkawa, Yasuyuki |
author_facet | Maehara, Kazumitsu Tomimatsu, Kosuke Harada, Akihito Tanaka, Kaori Sato, Shoko Fukuoka, Megumi Okada, Seiji Handa, Tetsuya Kurumizaka, Hitoshi Saitoh, Noriko Kimura, Hiroshi Ohkawa, Yasuyuki |
author_sort | Maehara, Kazumitsu |
collection | PubMed |
description | Recent advances in genome‐wide technologies have enabled analyses using small cell numbers of even single cells. However, obtaining tissue epigenomes with cell‐type resolution from large organs and tissues still remains challenging, especially when the available material is limited. Here, we present a ChIL‐based approach for analyzing the diverse cellular dynamics at the tissue level using high‐depth epigenomic data. “ChIL for tissues” allows the analysis of a single tissue section and can reproducibly generate epigenomic profiles from several tissue types, based on the distribution of target epigenomic states, tissue morphology, and number of cells. The proposed method enabled the independent evaluation of changes in cell populations and gene activation in cells from regenerating skeletal muscle tissues, using a statistical model of RNA polymerase II distribution on gene loci. Thus, the integrative analyses performed using ChIL can elucidate in vivo cell‐type dynamics of tissues. |
format | Online Article Text |
id | pubmed-8564819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85648192021-11-12 Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections Maehara, Kazumitsu Tomimatsu, Kosuke Harada, Akihito Tanaka, Kaori Sato, Shoko Fukuoka, Megumi Okada, Seiji Handa, Tetsuya Kurumizaka, Hitoshi Saitoh, Noriko Kimura, Hiroshi Ohkawa, Yasuyuki Mol Syst Biol Articles Recent advances in genome‐wide technologies have enabled analyses using small cell numbers of even single cells. However, obtaining tissue epigenomes with cell‐type resolution from large organs and tissues still remains challenging, especially when the available material is limited. Here, we present a ChIL‐based approach for analyzing the diverse cellular dynamics at the tissue level using high‐depth epigenomic data. “ChIL for tissues” allows the analysis of a single tissue section and can reproducibly generate epigenomic profiles from several tissue types, based on the distribution of target epigenomic states, tissue morphology, and number of cells. The proposed method enabled the independent evaluation of changes in cell populations and gene activation in cells from regenerating skeletal muscle tissues, using a statistical model of RNA polymerase II distribution on gene loci. Thus, the integrative analyses performed using ChIL can elucidate in vivo cell‐type dynamics of tissues. John Wiley and Sons Inc. 2021-11-03 /pmc/articles/PMC8564819/ /pubmed/34730297 http://dx.doi.org/10.15252/msb.202110323 Text en © 2021 The Authors Published under the terms of the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Maehara, Kazumitsu Tomimatsu, Kosuke Harada, Akihito Tanaka, Kaori Sato, Shoko Fukuoka, Megumi Okada, Seiji Handa, Tetsuya Kurumizaka, Hitoshi Saitoh, Noriko Kimura, Hiroshi Ohkawa, Yasuyuki Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title | Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title_full | Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title_fullStr | Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title_full_unstemmed | Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title_short | Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections |
title_sort | modeling population size independent tissue epigenomes by chil‐seq with single thin sections |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564819/ https://www.ncbi.nlm.nih.gov/pubmed/34730297 http://dx.doi.org/10.15252/msb.202110323 |
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