Department of Comparative Biology & Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada.
Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Genomics Proteomics Bioinformatics. 2021 Apr;19(2):172-190. doi: 10.1016/j.gpb.2020.06.010. Epub 2021 Feb 11.
How distinct transcriptional programs are enacted to generate cellular heterogeneity and plasticity, and enable complex fate decisions are important open questions. One key regulator is the cell's epigenome state that drives distinct transcriptional programs by regulating chromatin accessibility. Genome-wide chromatin accessibility measurements can impart insights into regulatory sequences (in)accessible to DNA-binding proteins at a single-cell resolution. This review outlines molecular methods and bioinformatic tools for capturing cell-to-cell chromatin variation using single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) in a scalable fashion. It also covers joint profiling of chromatin with transcriptome/proteome measurements, computational strategies to integrate multi-omic measurements, and predictive bioinformatic tools to infer chromatin accessibility from single-cell transcriptomic datasets. Methodological refinements that increase power for cell discovery through robust chromatin coverage and integrate measurements from multiple modalities will further expand our understanding of gene regulation during homeostasis and disease.
生成细胞异质性和可塑性并实现复杂命运决定的转录程序有何不同,以及哪些因素能促进这些不同的转录程序,这些都是重要的开放性问题。细胞的表观基因组状态是一个关键的调控因子,它通过调节染色质可及性来驱动不同的转录程序。全基因组染色质可及性测量可以深入了解调控序列(是否)可及到 DNA 结合蛋白,分辨率达到单细胞水平。本综述概述了分子方法和生物信息学工具,用于以可扩展的方式使用单细胞转座酶可及染色质测序 (scATAC-seq) 捕获单细胞之间的染色质变化。它还涵盖了与转录组/蛋白质组测量联合进行染色质分析、整合多组学测量的计算策略,以及从单细胞转录组数据集推断染色质可及性的预测性生物信息学工具。通过稳健的染色质覆盖和整合来自多个模态的测量来提高细胞发现能力的方法学改进,将进一步扩展我们对稳态和疾病过程中基因调控的理解。