Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections. Issue 11 (3rd November 2021) - Maehara, Kazumitsu; Tomimatsu, Kosuke; Harada, Akihito; Tanaka, Kaori; Sato, Shoko; Fukuoka, Megumi; Okada, Seiji; Handa, Tetsuya; Kurumizaka, Hitoshi; Saitoh, Noriko; Kimura, Hiroshi; Ohkawa, Yasuyuki
Abstract: 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. SYNOPSIS: "ChIL for tissues" allows obtaining epigenome information from a single‐thin tissue section with high sensitivity. A statistical model of RNApolII distribution is combined with ChIL to analyze cell‐type‐specific transcriptional states in a tissue. Highly sensitive epigenomic analyses are performed from a single 3 mm × 3 mm × 10 μm frozen section. ChIL is a dissociation‐free method and therefore reduces loss of cells and avoids inducing stress on cells. A statistical model of traveling ratio allows comprehensive screening of genes with changes in transcriptional state. The model can extract two types of information at the same time: cell number and transcriptinal activity of genes. Abstract : "ChIL for tissues" allows obtaining epigenome information from a single‐thin tissue section with high sensitivity. A statistical model of RNApolII distribution is combined with ChIL to analyze cell‐type‐specific transcriptional states in a tissue.