Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

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Dades bibliogràfiques
Publicat a:	Nature Reviews. Molecular Cell Biology vol. 26, no. 1 (Jan 2025), p. 11
Publicat:	Nature Publishing Group
Matèries:	Transcriptomes Spatial analysis Plastic properties Embryonic growth stage Microenvironments Embryogenesis Cell culture Phenotypes Stem cells Tumorigenesis Computer applications Data integration Transcriptomics Biological research Immunology Deep learning Hierarchies Immune response Data analysis Ecotypes Spatial data Gene expression Tissues Plasticity Plastic foam Software Biology Spatial discrimination learning Cancer Datasets Machine learning Artificial intelligence Annotations Neighborhoods Environmental
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Descripció
Resum:	Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.Single-cell and spatial transcriptomics are transforming our understanding of cell plasticity and tissue diversity. This Review discusses technical and computational advancements and challenges in characterizing cell states and tissues during embryogenesis, tumorigenesis and immune responses, and the application of these tools to the clinic.
ISSN:	1471-0072 1471-0080
DOI:	10.1038/s41580-024-00768-2
Font:	Health & Medical Collection