2.1 Ethics statement

This study was conducted using protocols approved by the Ethical Committee of the Shenzhen People's Hospital. Informed consents were obtained from all participants.

2.2 Isolation and culture of hUC-MSCs

Under sterile conditions, UC units (8-10 cm) were collected from the puerpera of full-term deliveries and were immediately saved in cold saline (0°C). The blood vessels and outer membrane were removed by surgical blades, and the Wharton jelly (WJ) tissue was cut using eye scissors. The minced tissues were then placed in a 10-cm culture dish at 1-cm intervals and were maintained in culture medium (MesenGro Medium supplemented with 10% FBS, 1% penicillin-streptomycin and 10% MesenGro Supplement) at 37°C with 5% CO₂ and 90% RH. After 48 hours, the medium was removed to eliminate non-adherent cells and replaced with fresh medium. The complete culture medium was changed every 3 days. We selected distinct cell subpopulations, and we assumed that these subpopulations were efficient and sustainable. Colonies smaller than 2 mm in diameter were ignored. The clustered hUC-MSCs were digested with trypsin and resuspended with complete culture medium at a density of 2.0 × 10⁴ cells/cm² into a 25-mm² vented culture bottle. The CD90⁺ hUC-MSCs were collected by immunomagnetic beads and were identified under more stringent measures. After approximately three generations, the hUC-MSCs were sterilely obtained to prepare a monoplast suspension of more than 6.0 × 10⁵ cells, with a survival rate >90% and cell diameter <30 μm. The hUC-MSCs samples were then sent to GENERGY BIO (Shanghai, China) for scRNA-seq analysis.

2.3 Isolation and culture of hSF-MSCs

The samples were collected during arthroscopic procedures from patients suffering from an intra-articular ligament injury of the knee joint. Isotonic saline solution was injected into the joint, the knee was moved several times, and then, SF (50-100 mL) mixed with saline solution was collected in γ-sterilized centrifuge tubes. Within 1-4 hours, the fluid was filtered with a cell strainer (40 μm nylon) to remove debris. The filtered fluid was gathered in γ-sterilized centrifuge tubes and centrifuged at 405 g for 10 minutes at room temperature. The cell pellet was resuspended in culture medium (MesenGro Medium supplemented with 10% FBS, 1% penicillin-streptomycin and 10% MesenGro Supplement) and plated in 100-mm dishes after centrifugation. After 48 hours, the medium was withdrawn to remove non-adherent cells and replaced with fresh medium. The complete culture medium was changed every 3 days. We selected distinct cell subpopulations and assumed that these units were efficient and sustainable. The colonies smaller than 2 mm in diameter were discarded using a cell scraper (Corning Inc). Then, the distinct cell subpopulation was digested in cloning cylinders (Sigma-Aldrich) and used to inoculate a new dish as passage 1. Passage 3 (P3) cells were used for the scRNA-seq analysis.

2.4 The scRNA-seq analysis

The hUC-MSCs and hSF-MSCs samples were sent to GENERGY BIO for scRNA-seq analysis (Figure 1) by following previously published protocols.29, 31 Briefly, cell counting was performed using a Countess^® II Automated Cell Counter and cell concentration was adjusted to 1.0 × 10⁶ cells/mL. Cellular suspensions were placed on a Chromium™ Single-Cell Instrument (10 × Genomics) to obtain single-cell Gel bead in EMulsion (GEM). ScRNA-seq libraries were prepared using the Chromium™ Single-Cell Bead and Library Kit. cDNA was sheared to 200 bp using a Covaris M220 (Covaris). Sequencing libraries were constructed using the Chromium™ Single-Cell Library Kit, following these steps: end repair and A-tailing, adapter ligation, post-ligation cleanup with SPRIselect, and sample index PCR and cleanup. The barcode sequencing libraries were quantified using qPCR.

The Cell Ranger Single-Cell Software Suite was used to perform sample demultiplexing, barcode processing and single-cell gene counting. First, sample demultiplexing was performed to generate FASTQs for the paired-end Read1 and Read2. Second, Chromium™ barcodes and unique molecular identifiers (UMIs) were filtered. Third, PCR was marked if read pairs matched with a barcode sequence, a UMI tag and a gene ID. Cell barcodes were determined based on the distribution of UMI counts. The number of reads that provided valid information was determined based on whether the reads had the following four characteristics: valid barcodes, a valid UMI, a cell barcode and the ability to be confidently mapped to exons. Sequencing data could be combined by counting non-duplicated reads and subsampled to obtain a given number of UMI counts per cell.

The gene-cell-barcode matrix was concatenated. Only genes with at least one UMI count detected in at least one cell were used. Unique molecular identifier normalization was performed by first dividing UMI counts, followed by multiplication by the median total UMI counts across all cells. Each gene was normalized such that its mean signal was 0, and standard deviation was 1. Principle components analysis was run on the normalized gene-barcode matrix. The normalized UMI counts of each gene were used to show expression of a marker in a t-SNE plot.

To identify genes that were enriched in a specific cluster, the mean expression of each gene was calculated across all cells in the cluster. Each gene from the cluster was then compared to the median expression of the same gene in all other cell clusters. Genes were ranked based on their expression difference, and the top 10 enriched genes from each cluster were selected. For hierarchical clustering, pair-wise correlation between each cluster was calculated, and centred expression of each gene was used to generate a heat map. Gene Ontology and KEGG term information was downloaded from the UniProtKB database. Both GO and KEGG terms with a P-value < .05 were considered to be significantly enriched.

2.5 Statistical analysis

Data are available at http://support.10×genomics.com/single-cell/datasets, and the analysis code is available at https://github.com/10×Genomics/single-cell-3prime-paper.

3.1 The scRNA-seq profiles of hUC-MSCs and hSF-MSCs by 10 × Genomics

For our scRNA analysis, we obtained 1597 cells and 1259 cells from hUC-MSCs and hSF-MSCs samples, respectively (Table 1). The sequencing saturation for hUC-MSCs and hSF-MSCs samples was 43.4% and 18.1%, respectively (Table 1). In hUC-MSCs, 17 317 genes were detected, with a median of 18 304 UMI Counts per cell, and an average of 65 598 reads per cell (Table 1). There were 104 761 163 reads from hUC-MSCs, of which, 86.2% had valid barcodes (Table 1). After mapping to the human genome, 78.2% of the reads mapped confidently to the transcriptome, with 81.8% of those reads mapping to exonic regions, 5.9% to intronic regions and 2.1% to intergenic regions (Table 1). In hSF-MSCs, 16 996 genes were detected, with a median of 12 609 UMI Counts per cell, and an average of 52 245 reads per cell (Table 1). There were 6 577 715 reads from hSF-MSCs, with 70.4% of those reads containing valid barcodes (Table 1). After mapping to the human genome, 60.4% of those reads mapped confidently to transcriptome, with 63.1% of those reads mapping to exonic regions, 8.1% to intronic regions and 2.6% to intergenic regions (Table 1).

3.2 Subpopulation discovery in hUC-MSCs and hSF-MSCs samples

The Chromium™ single-cell technology can also be used for scRNA-seq of primary cells. We isolated more than 1000 cells from hUC-MSCs and hSF-MSCs. Gene-cell matrices from hUC-MSCs and hSF-MSCs were concatenated, and PCA was performed to reduce dimensionality before performing clustering and t-SNE analysis. Based on our PCA and t-SNE results, there were 11 clusters present in hUC-MSCs and 7 in hSF-MSCs (Figures 2 and 3).

3.3 The DEG profile of hUC-MSCs and hSF-MSCs samples

By comparing gene expression profiles between subpopulations in hUC-MSCs, we identified 533 DEGs in cluster 1 (76 up-regulated and 457 down-regulated), 57 in cluster 2 (12 up-regulated and 45 down-regulated), 32 in cluster 3 (28 up-regulated and four down-regulated), 44 in cluster 4 (41 up-regulated and three down-regulated), 10 in cluster 5 (seven up-regulated and three down-regulated), 319 in cluster 6 (286 up-regulated and 31 down-regulated), 731 in cluster 7 (53 up-regulated and 678 down-regulated), 1037 in cluster 8 (424 up-regulated and 613 down-regulated), 90 in cluster 9 (89 up-regulated and one down-regulated), 25 in cluster 10 (24 up-regulated and one down-regulated) and 230 in cluster 11 (31 up-regulated and 199 down-regulated) (Tables 2 and 3). In hSF-MSCs, there were 204 DEGs in cluster 1 (185 up-regulated and 19 down-regulated), 577 in cluster 2 (129 up-regulated and 448 down-regulated), 30 in cluster 3 (20 up-regulated and 10 down-regulated), 577 in cluster 4 (43 up-regulated and 534 down-regulated), 16 in cluster 5 (14 up-regulated and two down-regulated), 57 in cluster 6 (51 up-regulated and down down-regulated) and 35 in cluster 7 (32 up-regulated and three down-regulated) (Tables 2 and 4).

3.4 GO function analysis of hUC-MSCs and hSF-MSCs samples

The three main categories for GO function analysis are biological process, cellular component and molecular function. As shown in Figure 4, the DEGs found in hUC-MSCs were significantly enriched in the following biological processes and molecular functions: cholesterol biosynthesis, calcium-transporting ATPase activity, corticosterone response, cholesterol biosynthesis, collagen trimer, cyclin-dependent protein kinase, DNA metabolism, double-stranded RNA binding, glutathione peroxidase activity, growth factor activity, heparin binding, integrin binding, macromolecular complex binding, MHC class I protein binding, negative regulation of cargo loading, PCNA-p21 complex, platelet-derived growth factor binding, protein binding, protein folding, peptide biosynthetic process, protein complex binding, protein targeting to ER, post-transcriptional regulation of gene expression, regulation of apoptotic process, regulation of cell death, regulation of cellular amino acid metabolism, RNA binding, RNA splicing, ribonucleoprotein complex, secondary alcohol biosynthetic process, SREBP-SCAP-Insig complex, SRP-dependent cotranslational protein, translation, structural molecule activity, transcription factor activity, transcription corepressor activity and unfolded protein binding. Additionally, GO term analysis showed that many of the DEGs function in the extracellular exosome, extracellular matrix, extracellular vesicles, membrane-bounded vesicles, Lewy bodies, myelin sheath and nucleus, and as structural components in the ribosome and cytoskeleton.

In hSF-MSCs, the cluster 1 DEGs were primarily associated with mitotic cell cycle control and processes, protein binding and RNA binding, and were enriched in membrane-enclosed lumen and organelle lumen (Figure 5A). The DEGs of cluster 2 were primarily related to SRP-dependent cotranslational protein targeting, protein targeting to ER and structural molecule activity, and a significant amount is found in cytosolic ribosomes and ribosomal structures (Figure 5B). The DEGs of cluster 3 function in wound healing, vasculature development, platelet-derived growth factor binding, formation of collagen trimers and extracellular matrix structure (Figure 5C). The DEGs of cluster 4 were related to responding to organic substances, anatomical structure morphogenesis and protein binding and RNA binding, and many of them are found in adherens junctions and anchoring junctions (Figure 5D). The DEGs of cluster 5 were associated with the regulation of cell migration, SREBP-SCAP-Insig complex, CXCR chemokine receptor binding and chemokine activity, with many of the DEGs localizing to the extracellular space (Figure 5E). The DEGs of cluster 6 were primarily related to extracellular matrix organization, extracellular structure organization, growth factor binding and glycosaminoglycan binding (Figure 5F). The DEGs of cluster 7 were primarily associated with the negative regulation of ryanodine, regulation of cellular amino acid, glutathione disulphide oxidoreductase and peptide disulphide oxidoreductase and a significant number of the DEGs localized to extracellular exosome, extracellular vesicle (Figure 5G).

3.5 KEGG analysis of hUC-MSCs and hSF-MSCs samples

According to KEGG analysis, the DEGs in hUC-MSC were mainly enriched in Alzheimer's disease, amoebiasis, antigen process and presentation, bladder cancer, cell cycle, chemical carcinogenesis, DNA replication, ECM-receptor interactions, factor-regulated calcium absorption, focal adhesions, gap junctions, glioma, glutathione metabolism, Hippo signalling pathway, Hunting's disease, Huntington's disease, xenobiotics metabolism, mineral absorption, nicotinate metabolism, oocyte meiosis, oxidative phosphorylation, p53 signalling pathway, Parkinson's disease, pathogenic Escherichia infection, PI3K-Akt signalling pathway, progesterone oocyte maturation, protein digestion and absorption, protein processing, pyruvate metabolism, and terpenoid backbone biosynthesis, and function in the phagosome, proteasome, ribosome and spliceosome (Figure 6).

In hSF-MSCs, the DEGs in cluster 1 were primarily involved in the spliceosome, cell cycle, p53 signalling pathway, RNA degradation and pathogenic Escherichia infection (Figure 7A). The DEGs of cluster 2 were associated with the ribosome, Parkinson's disease, oxidative phosphorylation, Huntington's disease and Alzheimer's disease (Figure 7B). The cluster 3 DEGs were primarily related to amoebiasis, ECM-receptor interactions, focal adhesions, bacterial invasion of epithelial cells and protein digestion and absorption (Figure 7C). Differentially expressed genes from cluster 4 were primarily associated with the spliceosome, ribosome and focal adhesions, as well as regulation of actin cytoskeleton, and PI3K-Akt signalling (Figure 7D). In cluster 5, the DEGs were primarily connected to chemokine signalling, Legionellosis, Salmonella infection, TNF signalling and cytokine-cytokine receptor interactions (Figure 7E). The DEGs of cluster 6 were primarily associated with Hippo signalling, proteoglycans expressed in cancer cells, focal adhesions, ECM-receptor interactions and p53 signalling (Figure 7F). The DEGs of cluster 7 were primarily related to the proteasome and phagosome, as well as pathogenic Escherichia infection, gap junction formation and ubiquinone biosynthesis (Figure 7G).