In the research of SCs, scRNA-seq is mainly used to identify cell subpopulations, analyze rare cell types, and describe developmental trajectories and regulatory networks.
Identification of cell subpopulations
One major application for scRNA-seq is research of stem cell heterogeneity. By acquiring unbiased samples of SCs from a tissue and generating transcriptomes for each cell, clustering cells is performed based on their expression data. Established clustering and dimension reduction methods, such as hierarchical clustering analysis, K-means, and principal components analysis, are usually applied to group cell subpopulations. The principle is that cells are sorted according to their expression levels of genes quantified by unique molecular identifiers. Cluster information is then overlaid on cells in two to three-dimensional t-distributed stochastic neighbor embedding plots that are used to visualize cell subpopulations. Performing statistical analysis to identify significantly differentially expressed genes between subpopulations to define cell markers assists in best discriminating different clusters, purifying, and distinguishing some cell subpopulations of interest. To functionally characterize the clustered subpopulations, functional annotation of differentially expressed genes is an indispensable step to analyze transcriptome data.
As an effective tool for research on heterogeneity of SCs, scRNA-seq is commonly applied to cancer SCs, adult SCs, and induced pluripotent SCs.
Cancer is regarded as one of the most complex and heterogeneous diseases, and cancer SCs are a major source for the formation, metastasis, and drug resistance of tumor. Intratumoral heterogeneity indicates a diverse pathological potential among cancer SCs, which increases the difficulty in targeting therapy of cancer. Therefore, the heterogeneity of cancer SCs needs to be urgently addressed in cancer research, diagnosis, and treatment. The genetic information and differences in the expression and control of genes among individual cells can be detected by scRNA-seq, making it possible to understand intra-tumoral heterogeneity, map different clones in tumors, and analyze cancer SCs, which is informative for cancer research. Recent studies employing scRNA-seq for cancer research have investigated breast cancer[24,25], lung cancer[26,27], renal cell cancer, glioblastoma[29,30], and hepatocellular carcinoma.
Adult SCs, residinge in almost all tissues of the body, have a self-renewal capacity and multi-lineage differentiation potential under certain conditions. They are presently a research focus in the stem cell field. Among all types of adult SCs, adipose-derived mesenchymal stromal/stem cells (ADSCs) have received increasing interest for immune and hematopoietic modulation, anti-inflammation effects, pro-angiogenesis properties, and tissue repair and restoration, owing to their relative ease of harvest, abundance, and multi-lineage differentiation[32,33]. Numerous studies have demonstrated that ADSCs are heterogeneous populations consisting of various cell subtypes. Accurately delineating subpopulations by functional properties or surface marker expression is necessary to promote their further translation to clinical benefits. Schwalie et al revealed three distinct subpopulations of ADSCs and adipose precursor cells in subcutaneous adipose tissue using scRNA-seq. They demonstrated that one of these subpopulations, CD142+ ABCG1+cells, suppress adipocyte formation in vivo and in vitro in a paracrine manner. Furthermore, they showed that the mechanism of this action possibly involved Spink2, Rtp3, Vit, and/or Fgf12 genes. These findings suggested a potentially critical role for CD142+ ABCG1+ cells in modulating the plasticity and metabolic signature of distinct adipose cell-containing systems. Other studies on heterogeneity of adult SCs using scRNA-seq have investigated hematopoietic SCs and neural SCs[37,38].
Induced pluripotent SCs are capable of unlimited self-renewal and can give rise to specialized cell types based on stepwise changes in their transcriptional networks. The research has indicated that gene expression is highly heterogeneous between induced pluripotent SCs, and the heterogeneity of cell states has not been described at a global transcriptional level. Nguyen et al used scRNA-seq to study the heterogenous states of human induced pluripotent SCs represented in pluripotent cultures at the transcriptional level. Four independent subpopulations of cells were identified and defined. Next, cell trajectories of transition between pluripotency states were defined. In their study, the largest dataset of single cell transcriptional profiling of undifferentiated human induced pluripotent SCs was provided, which increased our understanding of the complexity of pluripotent SCs.
Analysis of rare cell types
The second area that benefits immensely from scRNA-seq is the analysis of rare cell types. Commonly used approaches, such as microarrays and the NGS approach of high throughput RNA sequencing, are limited to large populations of cells. In cases where samples are available in only trace quantities, each of which can have a distinct function and role, the transcriptome can hardly be profiled by sequencing using these techniques. scRNA-seq can be used to characterize hidden subpopulations of rare cell types and measure gene expression in individual cells, overcoming the limitation of the cell sample size during traditional transcriptome analysis. Although a limited number of cells can influence the results, it has been demonstrated that 30 cells is the minimum sample size to sufficiently analyze the complexity of large cell subpopulations. In the early human embryo, only a very small number of embryonic cells and embryonic SCs can be isolated, which makes it difficult to study the gene regulatory network controlling human embryonic development by traditional methods. The problem has been solved by the development of scRNA-seq. Yan et al analyzed 124 individual cells from human preimplantation embryos and human embryonic SCs at various passages using scRNA-seq. The number of maternally expressed genes was 22687, which was significantly more than 9735 maternal genes detected previously by cDNA microarray. The results provided a comprehensive framework of the transcriptome landscapes of human early embryos and embryonic SCs. Additionally, scRNA-seq is used in the research of trace quantities of cancer SCs.
Description of developmental trajectories and regulatory networks
Another important application of scRNA-seq is the description of developmental trajectories and identification of gene regulatory networks. Mapping the pathway of differentiation and elucidating the underlying molecular controls are major goals in the development of stem cell technologies. scRNA-seq can be used to study the molecular dynamics of various cell types during development, map developmental trajectories, and reveal cell fate changes. During these processes, proliferative progenitor cells and stationary cells are detected, cell states that exist only transiently or during discrete time windows are identified, dynamic changes in the gene expression lineage of different cell types are recorded, and visualization of developmental trajectories is ultimately achieved. The application of SCs to the description of developmental trajectories and regulatory networks has been reported in many studies. Hematopoietic SCs, branching into all blood cell lineages of erythrocytes, leukocytes, and lymphocytes, must follow a highly controlled route. The molecular networks that control stem cell fate decisions, such as cell division or quiescence and differentiation or self-renewal, are still unclear. The chronological developmental trajectories of single hematopoietic cells from SCs to mature cells have not been described. Bendall et al provided a comprehensive analysis of human B lymphopoiesis and constructed developmental trajectories from hematopoietic SCs through to naive B cells using scRNA-seq expression data, laying the foundation to apply this approach to other tissues. Muscle SCs activate, divide, and give rise to muscle progenitors when injuries occur. scRNA-seq was applied to capture the transcriptional state of individual muscle SCs and primary myoblasts. Dell'Orso et al reported the homeostatic and developmental dynamic trajectories of regenerative adult muscle SCs and primary myoblasts, and described the relative transcriptional changes relative to metabolic pathways. In addition, other studies of developmental differentiation and gene regulation networks of SCs using scRNA-seq have focused on human pluripotent stem cell differentiation pathways, molecular trajectories of the early progenitors during human cord blood hematopoiesis, and developmental dynamics of adult hippocampal quiescent neural SCs.
In addition to the above applications to research of SCs, scRNA-seq can be used in the identification of cellular states such as the stage or speed of the cell cycle.