TY - JOUR
T1 - Modeling population size independent tissue epigenomes by ChIL-seq with single thin sections
AU - Maehara, Kazumitsu
AU - Tomimatsu, Kosuke
AU - Harada, Akihito
AU - Tanaka, Kaori
AU - Sato, Shoko
AU - Fukuoka, Megumi
AU - Okada, Seiji
AU - Handa, Tetsuya
AU - Kurumizaka, Hitoshi
AU - Saitoh, Noriko
AU - Kimura, Hiroshi
AU - Ohkawa, Yasuyuki
N1 - Funding Information:
Computations were carried out using the computer resources offered under the category of Intensively Promoted Projects by the Research Institute for Information Technology at Kyushu University. We appreciate the technical assistance from The Research Support Center, Research Center for Human Disease Modeling, Kyushu University Graduate School of Medical Sciences. We thank Mitchell Arico from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript. This work was in part supported by JST PRESTO JPMJPR2026 to K.M., JPMJPR19K7 to A.H., JST CREST JPMJCR16G1 to Y.O., H. Ku., and H. Ki.; JST ERATO JPMJER1901 to H. Ku.; MEXT/JSPS KAKENHI JP19H04970, JP19H03158, JP20H05393, and JP21H05755 to K.M.; JP18K19432, JP19H03211, JP19H05425, JP20H05368, JP21H00430 and JP21H05292 to A.H.; JP18H05534 and JP20H00449 to H. Ku.; JP18H04802, JP18H05527, JP19H05244, JP20K21398, JP20H00456, and JP20H04846 to Y.O.; JP18H05527 and JP17H01417 to H. Ki.; AMED JP20ek0109489h0001 to Y.O., AMED BINDS JP19am0101076 and JP20am0101076 to H. Ku.; JP19am0101105 to H. Ki.
Funding Information:
Computations were carried out using the computer resources offered under the category of Intensively Promoted Projects by the Research Institute for Information Technology at Kyushu University. We appreciate the technical assistance from The Research Support Center, Research Center for Human Disease Modeling, Kyushu University Graduate School of Medical Sciences. We thank Mitchell Arico from Edanz ( https://jp.edanz.com/ac ) for editing a draft of this manuscript. This work was in part supported by JST PRESTO JPMJPR2026 to K.M., JPMJPR19K7 to A.H., JST CREST JPMJCR16G1 to Y.O., H. Ku., and H. Ki.; JST ERATO JPMJER1901 to H. Ku.; MEXT/JSPS KAKENHI JP19H04970, JP19H03158, JP20H05393, and JP21H05755 to K.M.; JP18K19432, JP19H03211, JP19H05425, JP20H05368, JP21H00430 and JP21H05292 to A.H.; JP18H05534 and JP20H00449 to H. Ku.; JP18H04802, JP18H05527, JP19H05244, JP20K21398, JP20H00456, and JP20H04846 to Y.O.; JP18H05527 and JP17H01417 to H. Ki.; AMED JP20ek0109489h0001 to Y.O., AMED BINDS JP19am0101076 and JP20am0101076 to H. Ku.; JP19am0101105 to H. Ki.
Publisher Copyright:
© 2021 The Authors Published under the terms of the CC BY 4.0 license
PY - 2021/11
Y1 - 2021/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85120003718&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85120003718&partnerID=8YFLogxK
U2 - 10.15252/msb.202110323
DO - 10.15252/msb.202110323
M3 - Article
AN - SCOPUS:85120003718
VL - 17
JO - Molecular Systems Biology
JF - Molecular Systems Biology
SN - 1744-4292
IS - 11
M1 - e10323
ER -