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  • Review Article
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Single-cell atlases: shared and tissue-specific cell types across human organs

Nature Reviews Genetics volume 23, pages 395–410 (2022)Cite this article

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Abstract

The development of single-cell and spatial transcriptomics methods was instrumental in the conception of the Human Cell Atlas initiative, which aims to generate an integrated map of all cells across the human body. These technology advances are bringing increasing depth and resolution to maps of human organs and tissues, as well as our understanding of individual human cell types. Commonalities as well as tissue-specific features of primary and supportive cell types across human organs are beginning to emerge from these human tissue maps. In this Review, we highlight key biological insights obtained from cross-tissue studies into epithelial, fibroblast, vascular and immune cells based on single-cell gene expression data in humans and contrast it with mechanisms reported in mice.

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Fig. 1: Future avenues arising from single-cell cross-tissue comparisons.
Fig. 2: Shared and specialized features of epithelial glands.
Fig. 3: Universal and specialized fibroblasts found across human organs.
Fig. 4: Vasculature heterogeneity shared by or unique to organs.
Fig. 5: Features of immune cells across tissues.

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References

  1. Regev, A. et al. The Human Cell Atlas. eLife 6, e27041 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Lindeboom, R. G. H., Regev, A. & Teichmann, S. A. Towards a human cell atlas: taking notes from the past. Trends Genet. 37, 625–630 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Meizlish, M. L., Franklin, R. A., Zhou, X. & Medzhitov, R. Tissue homeostasis and inflammation. Annu. Rev. Immunol. 39, 557–581 (2021).

    Article  CAS  PubMed  Google Scholar 

  4. Gillich, A. et al. Capillary cell-type specialization in the alveolus. Nature 586, 785–789 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Plasschaert, L. W. et al. A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte. Nature 560, 377–381 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Park, J.-E. et al. A cell atlas of human thymic development defines T cell repertoire formation. Science 367, eaay3224 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Miragaia, R. J. et al. Single-cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation. Immunity 50, 493–504.e7 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sun, W. et al. snRNA-seq reveals a subpopulation of adipocytes that regulates thermogenesis. Nature 587, 98–102 (2020).

    Article  CAS  PubMed  Google Scholar 

  9. Trapnell, C. Defining cell types and states with single-cell genomics. Genome Res. 25, 1491–1498 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Luecken, M. D. & Theis, F. J. Current best practices in single-cell RNA-seq analysis: a tutorial. Mol. Syst. Biol. 15, e8746 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Andrews, T. S., Kiselev, V. Y., McCarthy, D. & Hemberg, M. Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data. Nat. Protoc. 16, 1–9 (2021).

    Article  CAS  PubMed  Google Scholar 

  12. Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Swanson, E. et al. Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. eLife 10, e63632 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Gomes, T., Teichmann, S. A. & Talavera-López, C. Immunology driven by large-scale single-cell sequencing. Trends Immunol. 40, 1011–1021 (2019).

    Article  CAS  PubMed  Google Scholar 

  15. Wang, F. et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J. Mol. Diagn. 14, 22–29 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).

    Article  PubMed  CAS  Google Scholar 

  17. Lee, J. H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kleshchevnikov, V. et al. Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics. Preprint at bioRxiv https://doi.org/10.1101/2020.11.15.378125 (2020).

    Article  Google Scholar 

  19. Stuart, T. et al. Comprehensive integration of single cell data. Cell 177, 1888–1902 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Andersson, A. et al. Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography. Commun. Biol. 3, 565 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  21. He, S. et al. Single-cell transcriptome profiling of an adult human cell atlas of 15 major organs. Genome Biol. 21, 294 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Han, X. et al. Construction of a human cell landscape at single-cell level. Nature 581, 303–309 (2020).

    Article  CAS  PubMed  Google Scholar 

  23. Eraslan, G. et al. Single-nucleus cross-tissue molecular reference maps to decipher disease gene function. Preprint at bioRxiv https://doi.org/10.1101/2021.07.19.452954 (2021).

    Article  Google Scholar 

  24. The Tabula Sapiens Consortium, Quake, S. R. The Tabula Sapiens: a single cell transcriptomic atlas of multiple organs from individual human donors. Preprint at bioRxiv https://doi.org/10.1101/2021.07.19.452956 (2021).

    Article  Google Scholar 

  25. Domínguez Conde, C. et al. Cross-tissue immune cell analysis reveals tissue-specific adaptations and clonal architecture in humans. Preprint at bioRxiv https://doi.org/10.1101/2021.04.28.441762 (2021).

    Article  Google Scholar 

  26. Karlsson, M. et al. A single–cell type transcriptomics map of human tissues. Sci. Adv. 7, eabh2169 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Sungnak, W. et al. SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes. Nat. Med. 26, 681–687 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Buechler, M. B. et al. Cross-tissue organization of the fibroblast lineage. Nature 593, 575–579 (2021). The first single-cell cross-tissue study focused on fibroblasts and their common and specific tissue distribution and transcriptional profiles in both mice and humans.

    Article  CAS  PubMed  Google Scholar 

  29. Osumi-Sutherland, D. et al. Cell types and ontologies of the Human Cell Atlas. Nat. Cell Biol. 23, 1129–1135 (2021).

    Article  CAS  PubMed  Google Scholar 

  30. Sirugo, G., Williams, S. M. & Tishkoff, S. A. The missing diversity in human genetic studies. Cell 177, 1080 (2019).

    Article  CAS  PubMed  Google Scholar 

  31. Chen, S. et al. hECA: the cell-centric assembly of a cell atlas. Preprint at bioRxiv https://doi.org/10.1101/2021.07.21.453289 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Gao, H. et al. A general framework for representing and annotating multifaceted cell heterogeneity in Human Cell Atlas. Preprint at bioRxiv https://doi.org/10.1101/2021.09.09.459281 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Watanabe, K., Mirkov, M. U., de Leeuw, C. A., van den Heuvel, M. P. & Posthuma, D. Genetic mapping of cell type specificity for complex traits. Nat. Commun. 10, 3222 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Calderon, D. et al. Inferring relevant cell types for complex traits by using single-cell gene expression. Am. J. Hum. Genet. 101, 686–699 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Gómez-Gálvez, P. et al. Scutoids are a geometrical solution to three-dimensional packing of epithelia. Nat. Commun. 9, 2960 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Polari, L. et al. Keratin intermediate filaments in the colon: guardians of epithelial homeostasis. Int. J. Biochem. Cell Biol. 129, 105878 (2020).

    Article  CAS  PubMed  Google Scholar 

  37. Litviňuková, M. et al. Cells of the adult human heart. Nature 588, 466–472 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Elmentaite, R. et al. Cells of the human intestinal tract mapped across space and time. Nature 597, 250–255 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Huang, N. et al. SARS-CoV-2 infection of the oral cavity and saliva. Nat. Med. 27, 892–903 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Nguyen, Q. H. et al. Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity. Nat. Commun. 9, 2028 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Trzpis, M. et al. Spatial and temporal expression patterns of the epithelial cell adhesion molecule (EpCAM/EGP-2) in developing and adult kidneys. Nephron Exp. Nephrol. 107, e119–e131 (2007).

    Article  CAS  PubMed  Google Scholar 

  42. Wu, H. et al. Comparative analysis and refinement of human PSC-derived kidney organoid differentiation with single-cell transcriptomics. Cell Stem Cell 23, 869–881.e8 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Stewart, B. J. et al. Spatiotemporal immune zonation of the human kidney. Science 365, 1461–1466 (2019). This paper illustrates the principle of immune zonation by demonstrating the specific position of phagocyte subsets across the kidney pseudo-depth.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Miao, Z. et al. Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets. Nat. Commun. 12, 2277 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Muto, Y. et al. Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney. Nat. Commun. 12, 2190 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Yu, Z. et al. Single-cell transcriptomic map of the human and mouse bladders. J. Am. Soc. Nephrol. 30, 2159–2176 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. He, H. et al. Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis. J. Allergy Clin. Immunol. 145, 1615–1628 (2020).

    Article  CAS  PubMed  Google Scholar 

  48. Cheng, J. B. et al. Transcriptional programming of normal and inflamed human epidermis at single-cell resolution. Cell Rep. 25, 871–883 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Oulès, B. et al. Contribution of GATA6 to homeostasis of the human upper pilosebaceous unit and acne pathogenesis. Nat. Commun. 11, 5067 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Bannier-Hélaouët, M. et al. Exploring the human lacrimal gland using organoids and single-cell sequencing. Cell Stem Cell 28, 1221–1232.e7 (2021).

    Article  PubMed  CAS  Google Scholar 

  51. Song, E.-A. C. et al. Genetic and scRNA-seq analysis reveals distinct cell populations that contribute to salivary gland development and maintenance. Sci. Rep. 8, 14043 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Baron, M. et al. A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure. Cell Syst. 3, 346–360.e4 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Peng, J. et al. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Res. 29, 725–738 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Saeki, K. et al. Mammary cell gene expression atlas links epithelial cell remodeling events to breast carcinogenesis. Commun. Biol. 4, 660 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Madissoon, E. et al. scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation. Genome Biol. 21, 1 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Madissoon, E. et al. A spatial multi-omics atlas of the human lung reveals a novel immune cell survival niche. Preprint at bioRxiv https://doi.org/10.1101/2021.11.26.470108 (2021).

    Article  Google Scholar 

  57. Zhang, P. et al. Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer. Cell Rep. 30, 4317 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Busslinger, G. A. et al. Human gastrointestinal epithelia of the esophagus, stomach, and duodenum resolved at single-cell resolution. Cell Rep. 34, 108819 (2021).

    Article  CAS  PubMed  Google Scholar 

  59. Garcia-Alonso, L. et al. Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro. Nat. Genet. 53, 1698–1711 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Gerbe, F. et al. Intestinal epithelial tuft cells initiate type 2 mucosal immunity to helminth parasites. Nature 529, 226–230 (2016).

    Article  CAS  PubMed  Google Scholar 

  61. von Moltke, J., Ji, M., Liang, H.-E. & Locksley, R. M. Tuft-cell-derived IL-25 regulates an intestinal ILC2-epithelial response circuit. Nature 529, 221–225 (2016).

    Article  CAS  Google Scholar 

  62. Howitt, M. R. et al. Tuft cells, taste-chemosensory cells, orchestrate parasite type 2 immunity in the gut. Science 351, 1329–1333 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Goldfarbmuren, K. C. et al. Dissecting the cellular specificity of smoking effects and reconstructing lineages in the human airway epithelium. Nat. Commun. 11, 2485 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Deprez, M. et al. A single-cell atlas of the human healthy airways. Am. J. Respir. Crit. Care Med. 202, 1636–1645 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Travaglini, K. J. et al. A molecular cell atlas of the human lung from single-cell RNA sequencing. Nature 587, 619–625 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Vieira Braga, F. A. et al. A cellular census of human lungs identifies novel cell states in health and in asthma. Nat. Med. 25, 1153–1163 (2019).

    Article  CAS  PubMed  Google Scholar 

  67. Elmentaite, R. et al. Single-cell sequencing of developing human gut reveals transcriptional links to childhood Crohn’s disease. Dev. Cell 55, 771–783.e5 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Martin, J. C. et al. Single-cell analysis of crohn’s disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy. Cell 178, 1493–1508.e20 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Smillie, C. S. et al. Intra- and inter-cellular rewiring of the human colon during ulcerative colitis. Cell 178, 714–730.e22 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Bautista, J. L. et al. Single-cell transcriptional profiling of human thymic stroma uncovers novel cellular heterogeneity in the thymic medulla. Nat. Commun. 12, 1096 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Deckmann, K. et al. Bitter triggers acetylcholine release from polymodal urethral chemosensory cells and bladder reflexes. Proc. Natl Acad. Sci. USA 111, 8287–8292 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Schütz, B. et al. Distribution pattern and molecular signature of cholinergic tuft cells in human gastro-intestinal and pancreatic-biliary tract. Sci. Rep. 9, 17466 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  73. Haber, A. L. et al. A single-cell survey of the small intestinal epithelium. Nature 551, 333–339 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Bjerknes, M. et al. Origin of the brush cell lineage in the mouse intestinal epithelium. Dev. Biol. 362, 194–218 (2012).

    Article  CAS  PubMed  Google Scholar 

  75. Yamashita, J., Ohmoto, M., Yamaguchi, T., Matsumoto, I. & Hirota, J. Skn-1a/Pou2f3 functions as a master regulator to generate Trpm5-expressing chemosensory cells in mice. PLoS ONE 12, e0189340 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Gerbe, F. et al. Distinct ATOH1 and Neurog3 requirements define tuft cells as a new secretory cell type in the intestinal epithelium. J. Cell Biol. 192, 767–780 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Montoro, D. T. et al. A revised airway epithelial hierarchy includes CFTR-expressing ionocytes. Nature 560, 319–324 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Koliaraki, V., Prados, A., Armaka, M. & Kollias, G. The mesenchymal context in inflammation, immunity and cancer. Nat. Immunol. 21, 974–982 (2020).

    Article  CAS  PubMed  Google Scholar 

  79. Davidson, S. et al. Fibroblasts as immune regulators in infection, inflammation and cancer. Nat. Rev. Immunol. 21, 704–717 (2021).

    Article  PubMed  CAS  Google Scholar 

  80. Krishnamurty, A. T. & Turley, S. J. Lymph node stromal cells: cartographers of the immune system. Nat. Immunol. 21, 369–380 (2020).

    Article  CAS  PubMed  Google Scholar 

  81. Takeda, A. et al. Single-cell survey of human lymphatics unveils marked endothelial cell heterogeneity and mechanisms of homing for neutrophils. Immunity 51, 561–572.e5 (2019). This study exemplifies the application of single-cell genomics to identify the diversity and spatial distribution or functional zonation of lymphatic endothelial cells within human lymph nodes.

    Article  CAS  PubMed  Google Scholar 

  82. Kapoor, V. N. et al. Gremlin 1 fibroblastic niche maintains dendritic cell homeostasis in lymphoid tissues. Nat. Immunol. 22, 571–585 (2021). This paper describes human lymph node fibroblast subsets at single-cell resolution and defines interactions of dendritic cells and GREM1+ FDCs in T cell zones, which are required for proper T cell function.

    Article  CAS  PubMed  Google Scholar 

  83. Fletcher, A. L. et al. Lymph node fibroblastic reticular cells directly present peripheral tissue antigen under steady-state and inflammatory conditions. J. Exp. Med. 207, 689–697 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Prados, A. et al. Fibroblastic reticular cell lineage convergence in Peyer’s patches governs intestinal immunity. Nat. Immunol. 22, 510–519 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Alexandre, Y. O. et al. A diverse fibroblastic stromal cell landscape in the spleen directs tissue homeostasis and immunity. Sci. Immunol. 7, eabj0641 (2022).

    Article  CAS  PubMed  Google Scholar 

  86. Bellomo, A. et al. Reticular fibroblasts expressing the transcription factor WT1 define a stromal niche that maintains and replenishes splenic red pulp macrophages. Immunity 53, 127–142.e7 (2020).

    Article  CAS  PubMed  Google Scholar 

  87. Kinchen, J. et al. Structural remodeling of the human colonic mesenchyme in inflammatory bowel disease. Cell 175, 372–386.e17 (2018). This paper defines stromal populations in healthy human colon at the single-cell level and reports a specific stromal subtype expanded in ulcerative colitis.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Tsukui, T. et al. Collagen-producing lung cell atlas identifies multiple subsets with distinct localization and relevance to fibrosis. Nat. Commun. 11, 1920 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Wang, W. et al. Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle. Nat. Med. 26, 1644–1653 (2020).

    Article  CAS  PubMed  Google Scholar 

  90. Li, H. et al. Low/negative expression of PDGFR-α identifies the candidate primary mesenchymal stromal cells in adult human bone marrow. Stem Cell Rep. 3, 965–974 (2014).

    Article  CAS  Google Scholar 

  91. Wolock, S. L. et al. Mapping distinct bone marrow niche populations and their differentiation paths. Cell Rep. 28, 302–311.e5 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Tikhonova, A. N. et al. The bone marrow microenvironment at single-cell resolution. Nature 569, 222–228 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Baccin, C. et al. Combined single-cell and spatial transcriptomics reveal the molecular, cellular and spatial bone marrow niche organization. Nat. Cell Biol. 22, 38–48 (2020).

    Article  CAS  PubMed  Google Scholar 

  94. Dolgalev, I. & Tikhonova, A. N. Connecting the dots: resolving the bone marrow niche heterogeneity. Front. Cell Dev. Biol. 9, 622519 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  95. Baryawno, N. et al. A cellular taxonomy of the bone marrow stroma in homeostasis and leukemia. Cell 177, 1915–1932.e16 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Krausgruber, T. et al. Structural cells are key regulators of organ-specific immune responses. Nature 583, 296–302 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Lee, J.-H. et al. Anatomically and functionally distinct lung mesenchymal populations marked by Lgr5 and Lgr6. Cell 170, 1149–1163.e12 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Bahar Halpern, K. et al. Lgr5+ telocytes are a signaling source at the intestinal villus tip. Nat. Commun. 11, 1936 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Mizoguchi, F. et al. Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis. Nat. Commun. 9, 789 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Croft, A. P. et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570, 246–251 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Zhang, F. et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat. Immunol. 20, 928–942 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Reynolds, G. et al. Developmental cell programs are co-opted in inflammatory skin disease. Science 371, eaba6500 (2021). This study shows the relevance of fetal-like endothelial cell expansion in inflamed human skin and defined cell–cell interactions with immune subsets.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Ramachandran, P. et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature 575, 512–518 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Dobie, R. et al. Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis. Cell Rep. 29, 1832–1847.e8 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Purcell, J. W. et al. LRRC15 is a novel mesenchymal protein and stromal target for antibody–drug conjugates. Cancer Res. 78, 4059–4072 (2018).

    Article  CAS  PubMed  Google Scholar 

  106. Korsunsky, I. et al. Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases. Preprint at bioRxiv https://doi.org/10.1101/2021.01.11.426253 (2021).

    Article  Google Scholar 

  107. Dominguez, C. X. et al. Single-cell RNA sequencing reveals stromal evolution into LRRC15 myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov. 10, 232–253 (2020).

    Article  CAS  PubMed  Google Scholar 

  108. Augustin, H. G. & Koh, G. Y. Organotypic vasculature: from descriptive heterogeneity to functional pathophysiology. Science 357, eaal2379 (2017).

    Article  PubMed  CAS  Google Scholar 

  109. Aird, W. C. Phenotypic heterogeneity of the endothelium: I. Structure, function, and mechanisms. Circ. Res. 100, 158–173 (2007).

    Article  CAS  PubMed  Google Scholar 

  110. Ribatti, D., Nico, B., Vacca, A., Roncali, L. & Dammacco, F. Endothelial cell heterogeneity and organ specificity. J. Hematother Stem Cell Res. 11, 81–90 (2002).

    Article  PubMed  Google Scholar 

  111. Nolan, D. J. et al. Molecular signatures of tissue-specific microvascular endothelial cell heterogeneity in organ maintenance and regeneration. Dev. Cell 26, 204–219 (2013).

    Article  CAS  PubMed  Google Scholar 

  112. Schupp, J. C. et al. Integrated single-cell atlas of endothelial cells of the human lung. Circulation 144, 286–302 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Pasut, A., Becker, L. M., Cuypers, A. & Carmeliet, P. Endothelial cell plasticity at the single-cell level. Angiogenesis 24, 311–326 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  114. Aird, W. C. Phenotypic heterogeneity of the endothelium: II. Representative vascular beds. Circ. Res. 100, 174–190 (2007).

    Article  CAS  PubMed  Google Scholar 

  115. Dumas, S. J. et al. Phenotypic diversity and metabolic specialization of renal endothelial cells. Nat. Rev. Nephrol. 17, 441–464 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Risau, W. Differentiation of endothelium. FASEB J. 9, 926–933 (1995).

    Article  CAS  PubMed  Google Scholar 

  117. Young, M. D. et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361, 594–599 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Kalucka, J. et al. Single-cell transcriptome atlas of murine endothelial cells. Cell 180, 764–779.e20 (2020). This study constructs a single-cell endothelial mouse cell atlas and characterizes inter- and intra-tissue endothelial cell heterogeneity.

    Article  CAS  PubMed  Google Scholar 

  119. Smith, J. M., Meinkoth, J. H., Hochstatter, T. & Meyers, K. M. Differential distribution of von Willebrand factor in canine vascular endothelium. Am. J. Vet. Res. 57, 750–755 (1996).

    CAS  PubMed  Google Scholar 

  120. Kawanami, O. et al. Mosaic-like distribution of endothelial cell antigens in capillaries and juxta-alveolar microvessels in the normal human lung. Pathol. Int. 50, 136–141 (2000).

    Article  CAS  PubMed  Google Scholar 

  121. Almet, A. A., Cang, Z., Jin, S. & Nie, Q. The landscape of cell-cell communication through single-cell transcriptomics. Curr. Opin. Syst. Biol. 26, 12–23 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Deane, H. W. A cytological study of storage and secretion in the developing liver of the mouse. Anat. Rec. 88, 161–173 (1944).

    Article  CAS  Google Scholar 

  123. Wälchli, T. et al. Molecular atlas of the human brain vasculature at the single-cell level. Preprint at bioRxiv https://doi.org/10.1101/2021.10.18.464715 (2021).

    Article  Google Scholar 

  124. Xiang, M. et al. A single-cell transcriptional roadmap of the mouse and human lymph node lymphatic vasculature. Front. Cardiovasc. Med. 7, 52 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Jalkanen, S. & Salmi, M. Lymphatic endothelial cells of the lymph node. Nat. Rev. Immunol. 20, 566–578 (2020).

    Article  CAS  PubMed  Google Scholar 

  126. Brazovskaja, A. et al. Cell atlas of the regenerating human liver after portal vein embolization. Preprint at bioRxiv https://doi.org/10.1101/2021.06.03.444016 (2021).

    Article  Google Scholar 

  127. Ben-Moshe, S. & Itzkovitz, S. Spatial heterogeneity in the mammalian liver. Nat. Rev. Gastroenterol. Hepatol. 16, 395–410 (2019).

    Article  PubMed  Google Scholar 

  128. Brosch, M. et al. Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control. Nat. Commun. 9, 4150 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  129. Dumas, S. J. et al. Single-cell RNA sequencing reveals renal endothelium heterogeneity and metabolic adaptation to water deprivation. J. Am. Soc. Nephrol. 31, 118–138 (2020).

    Article  CAS  PubMed  Google Scholar 

  130. McEnerney, L. et al. Dual modulation of human hepatic zonation via canonical and non-canonical Wnt pathways. Exp. Mol. Med. 49, e413 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Rocha, A. S. et al. The angiocrine factor rspondin3 is a key determinant of liver zonation. Cell Rep. 13, 1757–1764 (2015).

    Article  CAS  PubMed  Google Scholar 

  132. Pepper, M. S. & Skobe, M. Lymphatic endothelium: morphological, molecular and functional properties. J. Cell Biol. 163, 209–213 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Vanlandewijck, M. & Betsholtz, C. Single-cell mRNA sequencing of the mouse brain vasculature. Methods Mol. Biol. 1846, 309–324 (2018). This study uncovers the zonation of endothelial and mural cells along the arteriovenous axis in the mouse brain.

    Article  CAS  PubMed  Google Scholar 

  134. MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  135. Dogra, P. et al. Tissue determinants of human NK cell development, function, and residence. Cell 180, 749–763.e13 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Meng, W. et al. An atlas of B-cell clonal distribution in the human body. Nat. Biotechnol. 35, 879–884 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Yudanin, N. A. et al. Spatial and temporal mapping of human innate lymphoid cells reveals elements of tissue specificity. Immunity 50, 505–519.e4 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Thome, J. J. C. et al. Spatial map of human T cell compartmentalization and maintenance over decades of life. Cell 159, 814–828 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Masopust, D. & Soerens, A. G. Tissue-resident T cells and other resident leukocytes. Annu. Rev. Immunol. 37, 521–546 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Poon, M. M. L. & Farber, D. L. The whole body as the system in systems immunology. iScience 23, 101509 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Bian, Z. et al. Deciphering human macrophage development at single-cell resolution. Nature 582, 571–576 (2020).

    Article  CAS  PubMed  Google Scholar 

  142. Jaitin, D. A. et al. Lipid-associated macrophages control metabolic homeostasis in a trem2-dependent manner. Cell 178, 686–698.e14 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Deczkowska, A., Weiner, A. & Amit, I. The physiology, pathology, and potential therapeutic applications of the TREM2 signaling pathway. Cell 181, 1207–1217 (2020).

    Article  CAS  PubMed  Google Scholar 

  144. Katzenelenbogen, Y. et al. Coupled scRNA-seq and intracellular protein activity reveal an immunosuppressive role of TREM2 in cancer. Cell 182, 872–885.e19 (2020).

    Article  CAS  PubMed  Google Scholar 

  145. Soares, M. P. & Hamza, I. Macrophages and iron metabolism. Immunity 44, 492–504 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Korolnek, T. & Hamza, I. Macrophages and iron trafficking at the birth and death of red cells. Blood 125, 2893–2897 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Popescu, D.-M. et al. Decoding human fetal liver haematopoiesis. Nature 574, 365–371 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Miller, J. C. et al. Deciphering the transcriptional network of the dendritic cell lineage. Nat. Immunol. 13, 888–899 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Maier, B. et al. A conserved dendritic-cell regulatory program limits antitumour immunity. Nature 580, 257–262 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Fergusson, J. R. et al. Maturing human CD127+ CCR7+ PDL1+ dendritic cells express AIRE in the absence of tissue restricted antigens. Front. Immunol. 9, 2902 (2018).

    Article  CAS  PubMed  Google Scholar 

  151. Poliani, P. L. et al. Human peripheral lymphoid tissues contain autoimmune regulator-expressing dendritic cells. Am. J. Pathol. 176, 1104–1112 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Gardner, J. M. et al. Deletional tolerance mediated by extrathymic Aire-expressing cells. Science 321, 843–847 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Gardner, J. M. et al. Extrathymic Aire-expressing cells are a distinct bone marrow-derived population that induce functional inactivation of CD4+ T cells. Immunity 39, 560–572 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Wang, J. et al. Single-cell multiomics defines tolerogenic extrathymic Aire-expressing populations with unique homology to thymic epithelium. Sci. Immunol. 6, eabl5053 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Lavin, Y. et al. Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment. Cell 159, 1312–1326 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. James, K. R. et al. Distinct microbial and immune niches of the human colon. Nat. Immunol. 21, 343–353 (2020). This paper showcases the power of single-cell genomics to identify tissue adaptation programmes between the gut and associated lymphoid tissue as well as patterns of B cell receptor repertoires across regions of the colon.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Szabo, P. A. et al. Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease. Nat. Commun. 10, 4706 (2019). This paper exemplifies the power of analysing matched tissue and blood samples to determine the dynamics of an in vivo immune response to a viral infection.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  158. Buggert, M. et al. The identity of human tissue-emigrant CD8+ T cells. Cell 183, 1946–1961.e15 (2020).

    Article  CAS  PubMed  Google Scholar 

  159. Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. King, H. W. et al. Single-cell analysis of human B cell maturation predicts how antibody class switching shapes selection dynamics. Sci. Immunol. 6, eabe6291 (2021).

    Article  CAS  PubMed  Google Scholar 

  161. Low, J. S. et al. Clonal analysis of immunodominance and cross-reactivity of the CD4 T cell response to SARS-CoV-2. Science 372, 1336–1341 (2021).

    Article  CAS  PubMed  Google Scholar 

  162. Eberhardt, C. S. et al. Functional HPV-specific PD-1+ stem-like CD8 T cells in head and neck cancer. Nature 597, 279–284 (2021).

    Article  CAS  PubMed  Google Scholar 

  163. Kim, D., Lee, J., Lee, S., Park, J. & Lee, D. Predicting unintended effects of drugs based on off-target tissue effects. Biochem. Biophys. Res. Commun. 469, 399–404 (2016).

    Article  CAS  PubMed  Google Scholar 

  164. Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014.e22 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019).

    Article  CAS  PubMed  Google Scholar 

  166. Agarwal, D. et al. A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders. Nat. Commun. 11, 4183 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  167. Maynard, K. R. et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nat. Neurosci. 24, 425–436 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Pollen, A. A. et al. Molecular identity of human outer radial glia during cortical development. Cell 163, 55–67 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Darmanis, S. et al. A survey of human brain transcriptome diversity at the single cell level. Proc. Natl Acad. Sci. USA 112, 7285–7290 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Lake, B. B. et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Trevino, A. E. et al. Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution. Cell 184, 5053–5069.e23 (2021).

    Article  CAS  PubMed  Google Scholar 

  172. Velmeshev, D. et al. Single-cell genomics identifies cell type-specific molecular changes in autism. Science 364, 685–689 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Menon, M. et al. Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration. Nat. Commun. 10, 4902 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  174. Yan, W. et al. Cell atlas of the human fovea and peripheral retina. Sci. Rep. 10, 9802 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Shekhar, K. et al. Comprehensive classification of retinal bipolar neurons by single-cell transcriptomics. Cell 166, 1308–1323.e30 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Lukowski, S. W. et al. A single-cell transcriptome atlas of the adult human retina. EMBO J. 38, e100811 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  177. Drokhlyansky, E. et al. The human and mouse enteric nervous system at single-cell resolution. Cell 182, 1606–1622.e23 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. Bergmann, O. et al. Dynamics of cell generation and turnover in the human heart. Cell 161, 1566–1575 (2015).

    Article  CAS  PubMed  Google Scholar 

  179. Tucker, N. R. et al. Transcriptional and cellular diversity of the human heart. Circulation 142, 466–482 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Santos, M. D. et al. Single-nucleus RNA-seq and FISH reveal coordinated transcriptional activity in mammalian myofibers. Nat. Commun. 11, 5102 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  181. Petrany, M. J. et al. Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers. Nat. Commun. 11, 6374 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. De Micheli, A. J., Spector, J. A., Elemento, O. & Cosgrove, B. D. A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations. Skelet. Muscle 10, 19 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  183. Hu, P. et al. Dissecting cell-type composition and activity-dependent transcriptional state in mammalian brains by massively parallel single-nucleus RNA-seq. Mol. Cell 68, 1006–1015.e7 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Young, M. D. & Behjati, S. SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data. Gigascience 9, giaa151 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  185. Fleming, S. J., Marioni, J. C. & Babadi, M. CellBender remove-background: a deep generative model for unsupervised removal of background noise from scRNA-seq datasets. Preprint at bioRxiv https://doi.org/10.1101/791699 (2019).

    Article  Google Scholar 

  186. Wolock, S. L., Lopez, R. & Klein, A. M. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst. 8, 281–291.e9 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  187. McGinnis, C. S., Murrow, L. M. & Gartner, Z. J. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Cell Syst. 8, 329–337.e4 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. DePasquale, E. A. K. et al. DoubletDecon: deconvoluting doublets from single-cell RNA-sequencing data. Cell Rep. 29, 1718–1727.e8 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Tran, H. T. N. et al. A benchmark of batch-effect correction methods for single-cell RNA sequencing data. Genome Biol. 21, 12 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  190. Argelaguet, R., Cuomo, A. S. E., Stegle, O. & Marioni, J. C. Computational principles and challenges in single-cell data integration. Nat. Biotechnol. 39, 1202–1215 (2021).

    Article  CAS  PubMed  Google Scholar 

  191. Luecken, M. D. et al. Benchmarking atlas-level data integration in single-cell genomics. Nat. Methods 19, 41–50 (2022).

    Article  CAS  PubMed  Google Scholar 

  192. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  193. Polański, K. et al. BBKNN: fast batch alignment of single cell transcriptomes. Bioinformatics 36, 964–965 (2020).

    PubMed  Google Scholar 

  194. Gayoso, A. et al. scvi-tools: a library for deep probabilistic analysis of single-cell omics data. Preprint at bioRxiv https://doi.org/10.1101/2021.04.28.441833 (2021).

    Article  Google Scholar 

  195. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  196. Shao, X. et al. scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data. iScience 23, 100882 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Kimmel, J. C. & Kelley, D. R. Semi-supervised adversarial neural networks for single-cell classification. Genome Res. 31, 1781–1793 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank A. Maartens for providing feedback on writing; V. Kedlian, V. Kleshchevnikov, A. Oliver, E. Madissoon, K. Kanemaru, N. Kumasaka, B. Stewart and R. Bartolome-Casado for proofreading gene markers and cell types listed in Supplementary Table 2.

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Authors and Affiliations

  1. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK

    Rasa Elmentaite, Cecilia Domínguez Conde, Lu Yang & Sarah A. Teichmann

  2. Theory of Condensed Matter, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK

    Sarah A. Teichmann

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The authors contributed equally to all aspects of the article.

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S.A.T. has consulted or been a member of scientific advisory boards at Roche, Genentech, Biogen, GlaxoSmithKline, Qiagen and ForeSite Labs and is an equity holder of Transition Bio. The other authors declare no competing interests.

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Supplementary information

Glossary

Cell state

Intermediate, hybrid or transitional state acquired by the cell types in various contexts that is reflected in the transcriptional profile and function of the cell.

Primary cells

A category of cell types that perform the main functions of the tissue (for example, epithelial cells in barrier organs such as lung or gut, myocytes in skeletal or cardiac muscle, neurons in brain).

Supportive cells

A category of cells that provide functional and structural support for primary cells (for example, vascular cells, fibroblasts and immune cells).

V(D)J gene enrichment and sequencing

The process whereby immune receptor V, D and J, or V and J gene segments are selectively amplified from the single-cell RNA-sequencing data.

Clonal expansion

In the adaptive immune context, the process by which daughter B or T cells with unique antigen receptor specificity arise from a parent cell.

Cell ontologies

Structured and controlled ways of classifying cell types that aim to capture the full diversity of cell types and states present in an organism.

Zonation

Gradual transcriptional or phenotypic change of cells along a spatial axis.

Somatic hypermutation

A cellular mechanism by which B cells accumulate point mutations in both the heavy and light chains of antibody V regions.

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Elmentaite, R., Domínguez Conde, C., Yang, L. et al. Single-cell atlases: shared and tissue-specific cell types across human organs. Nat Rev Genet 23, 395–410 (2022). https://doi.org/10.1038/s41576-022-00449-w

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