CscoreTool-M infers 3D sub-compartment probabilities within cell population

Abstract Motivation Computational inference of genome organization based on Hi-C sequencing has greatly aided the understanding of chromatin and nuclear organization in three dimensions (3D). However, existing computational methods fail to address the cell population heterogeneity. Here we describe...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) Vol. 39; no. 5
Main Authors: Zheng, Xiaobin, Tran, Joseph R, Zheng, Yixian
Format: Journal Article
Language:English
Published: England Oxford University Press 04.05.2023
Subjects:
Chromatin
Chromosomes
Genome
Genomics - methods
Original Paper
Probability
ISSN:1367-4811, 1367-4803, 1367-4811
Online Access:Get full text
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Summary:Abstract Motivation Computational inference of genome organization based on Hi-C sequencing has greatly aided the understanding of chromatin and nuclear organization in three dimensions (3D). However, existing computational methods fail to address the cell population heterogeneity. Here we describe a probabilistic-modeling-based method called CscoreTool-M that infers multiple 3D genome sub-compartments from Hi-C data. Results The compartment scores inferred using CscoreTool-M represents the probability of a genomic region locating in a specific sub-compartment. Compared to published methods, CscoreTool-M is more accurate in inferring sub-compartments corresponding to both active and repressed chromatin. The compartment scores calculated by CscoreTool-M also help to quantify the levels of heterogeneity in sub-compartment localization within cell populations. By comparing proliferating cells and terminally differentiated non-proliferating cells, we show that the proliferating cells have higher genome organization heterogeneity, which is likely caused by cells at different cell-cycle stages. By analyzing 10 sub-compartments, we found a sub-compartment containing chromatin potentially related to the early-G1 chromatin regions proximal to the nuclear lamina in HCT116 cells, suggesting the method can deconvolve cell cycle stage-specific genome organization among asynchronously dividing cells. Finally, we show that CscoreTool-M can identify sub-compartments that contain genes enriched in housekeeping or cell-type-specific functions. Availability and implementation https://github.com/scoutzxb/CscoreTool-M.
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ISSN:1367-4811
1367-4803
1367-4811
DOI:10.1093/bioinformatics/btad314