Skip to main content
Log in

Single-cell sequencing advances in research on mesenchymal stem/stromal cells

  • Review Article
  • Published:
Human Cell Aims and scope Submit manuscript

Abstract

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

All data that support the fndings of this study are included within the article.

References

  1. Friedenstein AJ, Chailakhjan RK, Lalykina KS. The development of fibroblast colonies in monolayer cultures of guinea-pig bone marrow and spleen cells. Cell Tissue Kinet. 1970;3(4):393–403. https://doi.org/10.1111/j.1365-2184.1970.tb00347.x.

    Article  CAS  PubMed  Google Scholar 

  2. Caplan AI. Mesenchymal stem cells. J Orthop Res. 1991;9(5):641–50. https://doi.org/10.1002/jor.1100090504.

    Article  CAS  PubMed  Google Scholar 

  3. Dominici M, Le Blanc K, Mueller I, et al. Minimal criteria for defining multipotent mesenchymal stromal cells. The international society for cellular therapy position statement. Cytotherapy. 2006. https://doi.org/10.1080/14653240600855905.

    Article  PubMed  Google Scholar 

  4. Ringdén O, Moll G, Gustafsson B, Sadeghi B. Mesenchymal stromal cells for enhancing hematopoietic engraftment and treatment of graft-versus-host disease, hemorrhages and acute respiratory distress syndrome. Front Immunol. 2022;13: 839844. https://doi.org/10.3389/fimmu.2022.839844.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Xiang XN, Zhu SY, He HC, Yu X, Xu Y, He CQ. Mesenchymal stromal cell-based therapy for cartilage regeneration in knee osteoarthritis. Stem Cell Res Ther. 2022;13(1):14. https://doi.org/10.1186/s13287-021-02689-9.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Méndez-Ferrer S, Michurina TV, Ferraro F, et al. Mesenchymal and haematopoietic stem cells form a unique bone marrow niche. Nature. 2010;466(7308):829–34. https://doi.org/10.1038/nature09262.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Naji A, Eitoku M, Favier B, Deschaseaux F, Rouas-Freiss N, Suganuma N. Biological functions of mesenchymal stem cells and clinical implications. Cell Mol Life Sci. 2019;76(17):3323–48. https://doi.org/10.1007/s00018-019-03125-1.

    Article  CAS  PubMed  Google Scholar 

  8. Kabat M, Bobkov I, Kumar S, Grumet M. Trends in mesenchymal stem cell clinical trials 2004–2018: is efficacy optimal in a narrow dose range? Stem Cells Transl Med. 2020;9(1):17–27. https://doi.org/10.1002/sctm.19-0202.

    Article  CAS  PubMed  Google Scholar 

  9. De Luca M, Aiuti A, Cossu G, Parmar M, Pellegrini G, Robey PG. Advances in stem cell research and therapeutic development. Nat Cell Biol. 2019;21(7):801–11. https://doi.org/10.1038/s41556-019-0344-z.

    Article  CAS  PubMed  Google Scholar 

  10. Mönch D, Reinders MEJ, Hoogduijn MJ, Dahlke MH. Mesenchymal stromal cell-based therapy. Cells. 2023;12(4):559. https://doi.org/10.3390/cells12040559.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Panés J, García-Olmo D, Van Assche G, et al. Expanded allogeneic adipose-derived mesenchymal stem cells (Cx601) for complex perianal fistulas in Crohn’s disease: a phase 3 randomised, double-blind controlled trial. Lancet. 2016;388(10051):1281–90. https://doi.org/10.1016/S0140-6736(16)31203-X.

    Article  PubMed  Google Scholar 

  12. Mendicino M, Bailey AM, Wonnacott K, Puri RK, Bauer SR. MSC-based product characterization for clinical trials: an FDA perspective. Cell Stem Cell. 2014;14(2):141–5. https://doi.org/10.1016/j.stem.2014.01.013.

    Article  CAS  PubMed  Google Scholar 

  13. Phinney DG, Kopen G, Isaacson RL, Prockop DJ. Plastic adherent stromal cells from the bone marrow of commonly used strains of inbred mice: variations in yield, growth, and differentiation. J Cell Biochem. 1999;72(4):570–85.

    Article  CAS  PubMed  Google Scholar 

  14. Phinney DG, Kopen G, Righter W, Webster S, Tremain N, Prockop DJ. Donor variation in the growth properties and osteogenic potential of human marrow stromal cells. J Cell Biochem. 1999;75(3):424–36.

    Article  CAS  PubMed  Google Scholar 

  15. Vogel W, Grünebach F, Messam CA, Kanz L, Brugger W, Bühring HJ. Heterogeneity among human bone marrow-derived mesenchymal stem cells and neural progenitor cells. Haematologica. 2003;88(2):126–33.

    PubMed  Google Scholar 

  16. Wagner W, Feldmann RE, Seckinger A, et al. The heterogeneity of human mesenchymal stem cell preparations–evidence from simultaneous analysis of proteomes and transcriptomes. Exp Hematol. 2006;34(4):536–48. https://doi.org/10.1016/j.exphem.2006.01.002.

    Article  CAS  PubMed  Google Scholar 

  17. Wislet-Gendebien S, Poulet C, Neirinckx V, et al. In vivo tumorigenesis was observed after injection of in vitro expanded neural crest stem cells isolated from adult bone marrow. PLoS ONE. 2012;7(10): e46425. https://doi.org/10.1371/journal.pone.0046425.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tang X, Huang Y, Lei J, Luo H, Zhu X. The single-cell sequencing: new developments and medical applications. Cell Biosci. 2019;9:53. https://doi.org/10.1186/s13578-019-0314-y.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6(5):377–82. https://doi.org/10.1038/nmeth.1315.

    Article  CAS  PubMed  Google Scholar 

  20. Kolodziejczyk AA, Kim JK, Svensson V, Marioni JC, Teichmann SA. The technology and biology of single-cell RNA sequencing. Mol Cell. 2015;58(4):610–20. https://doi.org/10.1016/j.molcel.2015.04.005.

    Article  CAS  PubMed  Google Scholar 

  21. Casey MJ, Fliege J, Sánchez-García RJ, MacArthur BD. An information-theoretic approach to single cell sequencing analysis. BMC Bioinformatics. 2023;24(1):311. https://doi.org/10.1186/s12859-023-05424-8.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chen Y, Wang H, Yang Q, et al. Single-cell RNA landscape of the osteoimmunology microenvironment in periodontitis. Theranostics. 2022;12(3):1074–96. https://doi.org/10.7150/thno.65694.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chen H, Wen X, Liu S, et al. Dissecting heterogeneity reveals a unique BAMBIhigh MFGE8high subpopulation of human UC-MSCs. Adv Sci (Weinh). 2022;10(1): e2202510. https://doi.org/10.1002/advs.202202510.

    Article  PubMed  Google Scholar 

  24. Li J, Wang Q, An Y, et al. Integrative single-cell RNA-Seq and ATAC-Seq analysis of mesenchymal stem/stromal cells derived from human placenta. Front Cell Dev Biol. 2022;10: 836887. https://doi.org/10.3389/fcell.2022.836887.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Miyao T, Miyauchi M, Kelly ST, et al. Integrative analysis of scRNA-seq and scATAC-seq revealed transit-amplifying thymic epithelial cells expressing autoimmune regulator. Elife. 2022;11: e73998. https://doi.org/10.7554/eLife.73998.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Zhang P, Dong J, Fan X, et al. Characterization of mesenchymal stem cells in human fetal bone marrow by single-cell transcriptomic and functional analysis. Signal Transduct Target Ther. 2023;8(1):126. https://doi.org/10.1038/s41392-023-01338-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wang W, Zhang M, Ren X, et al. Single-cell dissection of cellular and molecular features underlying mesenchymal stem cell therapy in ischemic acute kidney injury. Mol Ther. 2023;31(10):3067–83. https://doi.org/10.1016/j.ymthe.2023.07.024.

    Article  CAS  PubMed  Google Scholar 

  28. Chen P, Tang S, Li M, et al. Single-cell and spatial transcriptomics decodes wharton’s jelly-derived mesenchymal stem cells heterogeneity and a subpopulation with wound repair signatures. Adv Sci (Weinh). 2023;10(4): e2204786. https://doi.org/10.1002/advs.202204786.

    Article  CAS  PubMed  Google Scholar 

  29. Hao RH, Guo Y, Wang C, et al. Lineage-specific rearrangement of chromatin loops and epigenomic features during adipocytes and osteoblasts commitment. Cell Death Differ. 2022;29(12):2503–18. https://doi.org/10.1038/s41418-022-01035-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Doolittle ML, Saul D, Kaur J, et al. Multiparametric senescent cell phenotyping reveals targets of senolytic therapy in the aged murine skeleton. Nat Commun. 2023;14(1):4587. https://doi.org/10.1038/s41467-023-40393-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wang R, Mao Y, Wang W, et al. Systematic evaluation of colorectal cancer organoid system by single-cell RNA-Seq analysis. Genome Biol. 2022;23(1):106. https://doi.org/10.1186/s13059-022-02673-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zhang L, Dong X, Lee M, Maslov AY, Wang T, Vijg J. Single-cell whole-genome sequencing reveals the functional landscape of somatic mutations in B lymphocytes across the human lifespan. Proc Natl Acad Sci U S A. 2019;116(18):9014–9. https://doi.org/10.1073/pnas.1902510116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhang X, Lian P, Su M, et al. Single-cell transcriptome analysis identifies a unique tumor cell type producing multiple hormones in ectopic ACTH and CRH secreting pheochromocytoma. Elife. 2021;10: e68436. https://doi.org/10.7554/eLife.68436.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Eng CHL, Lawson M, Zhu Q, et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH. Nature. 2019;568(7751):235–9. https://doi.org/10.1038/s41586-019-1049-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Rodriguez J, Ren G, Day CR, Zhao K, Chow CC, Larson DR. Intrinsic dynamics of a human gene reveal the basis of expression heterogeneity. Cell. 2019;176(1–2):213-226.e18. https://doi.org/10.1016/j.cell.2018.11.026.

    Article  CAS  PubMed  Google Scholar 

  36. Macosko EZ, Basu A, Satija R, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell. 2015;161(5):1202–14. https://doi.org/10.1016/j.cell.2015.05.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013;10(11):1096–8. https://doi.org/10.1038/nmeth.2639.

    Article  CAS  PubMed  Google Scholar 

  38. Hashimshony T, Wagner F, Sher N, Yanai I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2012;2(3):666–73. https://doi.org/10.1016/j.celrep.2012.08.003.

    Article  CAS  PubMed  Google Scholar 

  39. Keren-Shaul H, Kenigsberg E, Jaitin DA, et al. MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing. Nat Protoc. 2019. https://doi.org/10.1038/s41596-019-0164-4.

    Article  PubMed  Google Scholar 

  40. Sasagawa Y, Danno H, Takada H, et al. Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads. Genome Biol. 2018;19(1):29. https://doi.org/10.1186/s13059-018-1407-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Natarajan KN. Single-cell tagged reverse transcription (STRT-Seq). Methods Mol Biol. 2019;1979:133–53. https://doi.org/10.1007/978-1-4939-9240-9_9.

    Article  CAS  PubMed  Google Scholar 

  42. From the American Association of Neurological Surgeons (AANS), American Society of Neuroradiology (ASNR), Cardiovascular and Interventional Radiology Society of Europe (CIRSE), Canadian Interventional Radiology Association (CIRA), Congress of Neurological Surgeons (CNS), European Society of Minimally Invasive Neurological Therapy (ESMINT), European Society of Neuroradiology (ESNR), European Stroke Organization (ESO), Society for Cardiovascular Angiography and Interventions (SCAI), Society of Interventional Radiology (SIR), Society of NeuroInterventional Surgery (SNIS), and World Stroke Organization (WSO), Sacks D, Baxter B, et al. Multisociety Consensus Quality Improvement Revised Consensus Statement for Endovascular Therapy of Acute Ischemic Stroke. Int J Stroke. 2018;13(6):612–632. doi:https://doi.org/10.1177/1747493018778713

  43. Deleye L, Tilleman L, Vander Plaetsen AS, Cornelis S, Deforce D, Van Nieuwerburgh F. Performance of four modern whole genome amplification methods for copy number variant detection in single cells. Sci Rep. 2017;7(1):3422. https://doi.org/10.1038/s41598-017-03711-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zong C, Lu S, Chapman AR, Xie XS. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science. 2012;338(6114):1622–6. https://doi.org/10.1126/science.1229164.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Dean FB, Hosono S, Fang L, et al. Comprehensive human genome amplification using multiple displacement amplification. Proc Natl Acad Sci U S A. 2002;99(8):5261–6. https://doi.org/10.1073/pnas.082089499.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Dai X, Cai L, He F. Single-cell sequencing: expansion, integration and translation. Brief Funct Genom. 2022;21(4):280–95. https://doi.org/10.1093/bfgp/elac011.

    Article  CAS  Google Scholar 

  47. Guo H, Zhu P, Guo F, et al. Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing. Nat Protoc. 2015;10(5):645–59. https://doi.org/10.1038/nprot.2015.039.

    Article  CAS  PubMed  Google Scholar 

  48. Luo C, Rivkin A, Zhou J, et al. Robust single-cell DNA methylome profiling with snmC-seq2. Nat Commun. 2018;9(1):3824. https://doi.org/10.1038/s41467-018-06355-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Massarat AR, Sen A, Jaureguy J, et al. Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq. Nucleic Acids Res. 2021;49(14):7986–94. https://doi.org/10.1093/nar/gkab621.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Bartosovic M, Kabbe M, Castelo-Branco G. Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nat Biotechnol. 2021;39(7):825–35. https://doi.org/10.1038/s41587-021-00869-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Rotem A, Ram O, Shoresh N, et al. Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat Biotechnol. 2015;33(11):1165–72. https://doi.org/10.1038/nbt.3383.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wang K, Xiao Z, Yan Y, et al. Simple oligonucleotide-based multiplexing of single-cell chromatin accessibility. Mol Cell. 2021;81(20):4319-4332.e10. https://doi.org/10.1016/j.molcel.2021.09.026.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Angermueller C, Clark SJ, Lee HJ, et al. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat Methods. 2016;13(3):229–32. https://doi.org/10.1038/nmeth.3728.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Hu Y, Huang K, An Q, et al. Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 2016;17:88. https://doi.org/10.1186/s13059-016-0950-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Cao J, Cusanovich DA, Ramani V, et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science. 2018;361(6409):1380–5. https://doi.org/10.1126/science.aau0730.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Plongthongkum N, Diep D, Chen S, Lake BB, Zhang K. Scalable dual-omics profiling with single-nucleus chromatin accessibility and mRNA expression sequencing 2 (SNARE-seq2). Nat Protoc. 2021;16(11):4992–5029. https://doi.org/10.1038/s41596-021-00507-3.

    Article  CAS  PubMed  Google Scholar 

  57. Clark SJ, Argelaguet R, Kapourani CA, et al. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat Commun. 2018;9(1):781. https://doi.org/10.1038/s41467-018-03149-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Budnik B, Levy E, Harmange G, Slavov N. SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. Genome Biol. 2018;19(1):161. https://doi.org/10.1186/s13059-018-1547-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Specht H, Emmott E, Petelski AA, et al. Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2. Genome Biol. 2021;22(1):50. https://doi.org/10.1186/s13059-021-02267-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Mimitou EP, Cheng A, Montalbano A, et al. Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat Methods. 2019;16(5):409–12. https://doi.org/10.1038/s41592-019-0392-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Peterson VM, Zhang KX, Kumar N, et al. Multiplexed quantification of proteins and transcripts in single cells. Nat Biotechnol. 2017;35(10):936–9. https://doi.org/10.1038/nbt.3973.

    Article  CAS  PubMed  Google Scholar 

  62. Huttanus HM, Triola EKH, Velasquez-Guzman JC, et al. Targeted mutagenesis and high-throughput screening of diversified gene and promoter libraries for isolating gain-of-function mutations. Front Bioeng Biotechnol. 2023;11:1202388. https://doi.org/10.3389/fbioe.2023.1202388.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Sobol MS, Kaster AK. Back to basics: a simplified improvement to multiple displacement amplification for microbial single-cell genomics. Int J Mol Sci. 2023;24(5):4270. https://doi.org/10.3390/ijms24054270.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Zhou B, Jin W. Visualization of single cell RNA-seq data using t-SNE in R. Methods Mol Biol. 2020;2117:159–67. https://doi.org/10.1007/978-1-0716-0301-7_8.

    Article  CAS  PubMed  Google Scholar 

  65. Becht E, McInnes L, Healy J, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2018. https://doi.org/10.1038/nbt.4314.

    Article  PubMed  Google Scholar 

  66. Balzer MS, Ma Z, Zhou J, Abedini A, Susztak K. How to get started with single cell RNA sequencing data analysis. J Am Soc Nephrol. 2021;32(6):1279–92. https://doi.org/10.1681/ASN.2020121742.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Luecken MD, Theis FJ. Current best practices in single-cell RNA-seq analysis: a tutorial. Mol Syst Biol. 2019;15(6): e8746. https://doi.org/10.15252/msb.20188746.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Moll G, Ankrum JA, Olson SD, Nolta JA. Improved MSC minimal criteria to maximize patient safety: a call to embrace tissue factor and hemocompatibility assessment of MSC products. Stem Cells Transl Med. 2022;11(1):2–13. https://doi.org/10.1093/stcltm/szab005.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Wang Z, Chai C, Wang R, et al. Single-cell transcriptome atlas of human mesenchymal stem cells exploring cellular heterogeneity. Clin Transl Med. 2021;11(12): e650. https://doi.org/10.1002/ctm2.650.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Freeman BT, Jung JP, Ogle BM. Single-cell rna-seq of bone marrow-derived mesenchymal stem cells reveals unique profiles of lineage priming. PLoS ONE. 2015. https://doi.org/10.1371/journal.pone.0136199.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Xie Z, Yu W, Ye G, et al. Single-cell RNA sequencing analysis of human bone-marrow-derived mesenchymal stem cells and functional subpopulation identification. Exp Mol Med. 2022;54(4):483–92. https://doi.org/10.1038/s12276-022-00749-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Wolock SL, Krishnan I, Tenen DE, et al. Mapping distinct bone marrow niche populations and their differentiation paths. Cell Rep. 2019;28(2):302-311.e5. https://doi.org/10.1016/j.celrep.2019.06.031.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Zhang C, Han X, Liu J, et al. Single-cell transcriptomic analysis reveals the cellular heterogeneity of mesenchymal stem cells. Genom Proteom Bioinform. 2022;20(1):70–86. https://doi.org/10.1016/j.gpb.2022.01.005.

    Article  CAS  Google Scholar 

  74. Cote AJ, McLeod CM, Farrell MJ, et al. Single-cell differences in matrix gene expression do not predict matrix deposition. Nat Commun. 2016;7:10865. https://doi.org/10.1038/ncomms10865.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Liu J, Gan L, Ma B, et al. Alterations in chromatin accessibility during osteoblast and adipocyte differentiation in human mesenchymal stem cells. BMC Med Genomics. 2022;15(1):17. https://doi.org/10.1186/s12920-022-01168-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Sisakhtnezhad S, Heshmati P. Comparative analysis of single-cell RNA sequencing data from mouse spermatogonial and mesenchymal stem cells to identify differentially expressed genes and transcriptional regulators of germline cells. J Cell Physiol. 2018;233(7):5231–42. https://doi.org/10.1002/jcp.26303.

    Article  CAS  PubMed  Google Scholar 

  77. Barrett AN, Fong CY, Subramanian A, et al. Human wharton’s jelly mesenchymal stem cells show unique gene expression compared with bone marrow mesenchymal stem cells using single-cell rna-sequencing. Stem Cells Dev. 2019;28(3):196–211. https://doi.org/10.1089/scd.2018.0132.

    Article  CAS  PubMed  Google Scholar 

  78. Zhou W, Lin J, Zhao K, et al. Single-cell profiles and clinically useful properties of human mesenchymal stem cells of adipose and bone marrow origin. Am J Sports Med. 2019;47(7):1722–33. https://doi.org/10.1177/0363546519848678.

    Article  PubMed  Google Scholar 

  79. Sun C, Wang L, Wang H, et al. Single-cell RNA-seq highlights heterogeneity in human primary Wharton’s jelly mesenchymal stem/stromal cells cultured in vitro. Stem Cell Res Ther. 2020;11(1):149. https://doi.org/10.1186/s13287-020-01660-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Zhao X, Han Y, Liang Y, Nie C, Wang J. RNA-Seq reveals the angiogenesis diversity between the fetal and adults bone mesenchyme stem cell. PLoS ONE. 2016;11(2): e0149171. https://doi.org/10.1371/journal.pone.0149171.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Yang Y, Yang M, Shi D, et al. Single-cell RNA Seq reveals cellular landscape-specific characteristics and potential etiologies for adolescent idiopathic scoliosis. JOR Spine. 2021;4(4): e1184. https://doi.org/10.1002/jsp2.1184.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Shafiee A, Patel J, Hutmacher DW, Fisk NM, Khosrotehrani K. Meso-endothelial bipotent progenitors from human placenta display distinct molecular and cellular identity. Stem Cell Reports. 2018;10(3):890–904. https://doi.org/10.1016/j.stemcr.2018.01.011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Liu Y, Fan X, Wang R, et al. Single-cell RNA-seq reveals the diversity of trophoblast subtypes and patterns of differentiation in the human placenta. Cell Res. 2018;28(8):819–32. https://doi.org/10.1038/s41422-018-0066-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Choi R, Goncalves S, Durante MA, Goldstein BJ. On the in vivo origin of human nasal mesenchymal stem cell cultures. Laryngoscope Investig Otolaryngol. 2020;5(6):975–82. https://doi.org/10.1002/lio2.472.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Gu W, Nowak WN, Xie Y, et al. Single-cell RNA-sequencing and metabolomics analyses reveal the contribution of perivascular adipose tissue stem cells to vascular remodeling. Arterioscler Thromb Vasc Biol. 2019;39(10):2049–66. https://doi.org/10.1161/ATVBAHA.119.312732.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Kameishi S, Umemoto T, Matsuzaki Y, et al. Characterization of rabbit limbal epithelial side population cells using RNA sequencing and single-cell qRT-PCR. Biochem Biophys Res Commun. 2016;473(3):704–9. https://doi.org/10.1016/j.bbrc.2015.10.155.

    Article  CAS  PubMed  Google Scholar 

  87. Karlsen TA, Sundaram AYM, Brinchmann JE. Single-cell RNA sequencing of in vitro expanded chondrocytes: MSC-like cells with no evidence of distinct subsets. Cartilage. 2021. https://doi.org/10.1177/1947603519847746.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Wu H, Qin J, Zhao Q, Lu L, Li C. Microdissection of the bulk transcriptome at single-cell resolution reveals clinical significance and myeloid cells heterogeneity in lung adenocarcinoma. Front Immunol. 2021. https://doi.org/10.3389/fimmu.2021.723908.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Zhang Y, Yi Y, Xiao X, et al. Definitive endodermal cells supply an in vitro source of mesenchymal stem/stromal cells. Commun Biol. 2023;6(1):476. https://doi.org/10.1038/s42003-023-04810-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Zhu R, Yan T, Feng Y, et al. Mesenchymal stem cell treatment improves outcome of COVID-19 patients via multiple immunomodulatory mechanisms. Cell Res. 2021;31(12):1244–62. https://doi.org/10.1038/s41422-021-00573-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Ji F, Liu Y, Shi J, et al. Single-cell transcriptome analysis reveals mesenchymal stem cells in cavernous hemangioma. Front Cell Dev Biol. 2022;10: 916045. https://doi.org/10.3389/fcell.2022.916045.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Anbazhagan M, Geem D, Venkateswaran S, et al. Characterization of intestinal mesenchymal stromal cells from patients with inflammatory bowel disease for autologous cell therapy. Stem Cells Transl Med. 2023;12(2):112–22. https://doi.org/10.1093/stcltm/szad003.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Kosaric N, Srifa W, Bonham CA, et al. Macrophage subpopulation dynamics shift following intravenous infusion of mesenchymal stromal cells. Mol Ther. 2020;28(9):2007–22. https://doi.org/10.1016/j.ymthe.2020.05.022.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was supported by grants from Performance-Based Subsidy for the Key Laboratory of Neurobiological Functioning in Hebei Province (20567622H), Medical Science Research Program of Hebei Province (20210526), and Hebei Province Medical Technology Monitoring Program (GZ2023049).

Author information

Authors and Affiliations

Authors

Contributions

Qingxi Long outlined the review, designed the figures, collected the literature, and wrote the manuscript. Xiaodong Yuan, Pingshu Zhang and Ya Ou provided the necessary financial support. Wen Li and Qi Yan coordinated the revision and manuscript preparation. We analyzed the literature. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xiaodong Yuan.

Ethics declarations

Conflicts of interest

The authors declare no conflicts of interest.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Long, Q., Zhang, P., Ou, Y. et al. Single-cell sequencing advances in research on mesenchymal stem/stromal cells. Human Cell (2024). https://doi.org/10.1007/s13577-024-01076-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13577-024-01076-9

Keywords

Navigation