Abstract
The purpose of this study was to measure the heterogeneity in human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) and human synovial fluid-derived mesenchymal stem cells (hSF-MSCs) by single-cell RNA-sequencing (scRNA-seq). Using Chromium™ technology, scRNA-seq was performed on hUC-MSCs and hSF-MSCs from samples that passed our quality control checks. In order to identify subgroups and activated pathways, several bioinformatics tools were used to analyse the transcriptomic profiles, including clustering, principle components analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), gene set enrichment analysis, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. scRNA-seq was performed on the two sample sets. In total, there were 104 761 163 reads for the hUC-MSCs and 6 577 715 for the hSF-MSCs, with >60% mapping rate. Based on PCA and t-SNE analyses, we identified 11 subsets within hUC-MSCs and seven subsets within hSF-MSCs. Gene set enrichment analysis determined that there were 533, 57, 32, 44, 10, 319, 731, 1037, 90, 25 and 230 differentially expressed genes (DEGs) in the 11 subsets of hUC-MSCs and 204, 577, 30, 577, 16, 57 and 35 DEGs in the seven subsets of hSF-MSCs. scRNA-seq was not only able to identify subpopulations of hUC-MSCs and hSF-MSCs within the sample sets, but also provided a digital transcript count of hUC-MSCs and hSF-MSCs within a single patient. scRNA-seq analysis may elucidate some of the biological characteristics of MSCs and allow for a better understanding of the multi-directional differentiation, immunomodulatory properties and tissue repair capabilities of MSCs.