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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...

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Autores principales: Maehara, Kazumitsu, Tomimatsu, Kosuke, Harada, Akihito, Tanaka, Kaori, Sato, Shoko, Fukuoka, Megumi, Okada, Seiji, Handa, Tetsuya, Kurumizaka, Hitoshi, Saitoh, Noriko, Kimura, Hiroshi, Ohkawa, Yasuyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
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.
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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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