Choi Yoon Ha, Kim Jong Kyoung
Department of New Biology, DGIST, Daegu 42988, Korea.
Mol Cells. 2019 Mar 31;42(3):189-199. doi: 10.14348/molcells.2019.2446. Epub 2019 Feb 12.
Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeo-statically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. A major question in analyzing scRNA-seq data is how to account for the observed cell-to-cell variability. In this review, we provide an overview of scRNA-seq protocols, computational approaches for dissecting cellular heterogeneity, and future directions of single-cell transcriptomic analysis.
即使在细胞的同质群体中,基因表达的细胞间变异性也存在。剖析生物系统内的这种细胞异质性是理解生物系统如何发育、稳态调节以及对外部扰动作出反应的先决条件。单细胞RNA测序(scRNA-seq)通过提供数万个单个细胞的全基因组分子图谱,允许对细胞异质性进行定量和无偏的表征。分析scRNA-seq数据中的一个主要问题是如何解释观察到的细胞间变异性。在本综述中,我们概述了scRNA-seq方案、剖析细胞异质性的计算方法以及单细胞转录组分析的未来方向。