The 3D Genome Structure of Single Cells

被引:34
|
作者
Zhou, Tianming [1 ]
Zhang, Ruochi [1 ]
Ma, Jian [1 ]
机构
[1] Carnegie Mellon Univ, Sch Comp Sci, Computat Biol Dept, Pittsburgh, PA 15213 USA
来源
ANNUAL REVIEW OF BIOMEDICAL DATA SCIENCE, VOL 4 | 2021年 / 4卷
基金
美国国家卫生研究院;
关键词
nuclear organization; 3D genome; chromatin interaction; single-cell Hi-C; dimensionality reduction; imputation; hypergraph representation learning; HI-C DATA; CHROMATIN INTERACTION; READ ALIGNMENT; ORGANIZATION; ARCHITECTURE; PRINCIPLES; DYNAMICS; DOMAINS;
D O I
10.1146/annurev-biodatasci-020121-084709
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The spatial organization of the genome in the cell nucleus is pivotal to cell function. However, how the 3D genome organization and its dynamics influence cellular phenotypes remains poorly understood. The very recent development of single-cell technologies for probing the 3D genome, especially single-cell Hi-C (scHi-C), has ushered in a new era of unveiling cell-to-cell variability of 3D genome features at an unprecedented resolution. Here, we review recent developments in computational approaches to the analysis of scHi-C, including data processing, dimensionality reduction, imputation for enhancing data quality, and the revealing of 3D genome features at single-cell resolution. While much progress has been made in computational method development to analyze single-cell 3D genomes, substantial future work is needed to improve data interpretation and multimodal data integration, which are critical to reveal fundamental connections between genome structure and function among heterogeneous cell populations in various biological contexts.
引用
收藏
页码:21 / 41
页数:21
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