Published online Oct 26, 2019. doi: 10.4252/wjsc.v11.i10.722
Peer-review started: May 8, 2019
First decision: August 1, 2019
Revised: August 12, 2019
Accepted: September 11, 2019
Article in press: September 11, 2019
Published online: October 26, 2019
Stem cells (SCs) with their self-renewal and pluripotent differentiation potential, show great promise for therapeutic applications to some refractory diseases such as stroke, Parkinsonism, myocardial infarction, and diabetes. Furthermore, as seed cells in tissue engineering, SCs have been applied widely to tissue and organ regeneration. However, previous studies have shown that SCs are heterogeneous and consist of many cell subpopulations. Owing to this heterogeneity of cell states, gene expression is highly diverse between cells even within a single tissue, making precise identification and analysis of biological properties difficult, which hinders their further research and applications. Therefore, a defined understanding of the heterogeneity is a key to research of SCs. Traditional ensemble-based sequencing approaches, such as microarrays, reflect an average of expression levels across a large population, which overlook unique biological behaviors of individual cells, conceal cell-to-cell variations, and cannot understand the heterogeneity of SCs radically. The development of high throughput single cell RNA sequencing (scRNA-seq) has provided a new research tool in biology, ranging from identification of novel cell types and exploration of cell markers to the analysis of gene expression and predicating developmental trajectories. scRNA-seq has profoundly changed our understanding of a series of biological phenomena. Currently, it has been used in research of SCs in many fields, particularly for the research of heterogeneity and cell subpopulations in early embryonic development. In this review, we focus on the scRNA-seq technique and its applications to research of SCs.
Core tip: Single cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to explore cellular heterogeneity, provide new insights based on gene expression profiles of individual cells, reveal new cell subpopulations and predict developmental trajectories. It has been used in research of stem cells (SCs) in many fields, especially the study of heterogeneity and cell subpopulations in early embryonic development. This review aims to provide an overview of the applications of scRNA-seq to research of SCs.