Modeling population size independent tissue epigenomes by ChIL-seq with single-thin sections

Abstract

Recent advances in omics studies have enabled analysis at the single-cell level; however, methods for analyzing the whole cell of large organs and tissues remain challenging. Here, we developed a method named tsChIL to understand the diverse cellular dynamics at the tissue level using high-depth epigenomic data. tsChIL allowed the analysis of a single tissue section and could reproducibly acquire epigenomic profiles from several types of tissues, 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 of cells in regenerating skeletal muscle tissues, using a statistical model of RNA polymerase II distribution on gene loci. Thus, the integrative analysis by tsChIL can elucidate in vivo cell-type dynamics of tissues.