Ruyu Shi, Huaijun Chen, Wenting Zhang, Rehana K Leak, Dequan Lou, Kong Chen, Jun Chen
{"title":"单细胞RNA测序在中风和创伤性脑损伤:转录组学分析的当前成就、挑战和未来展望。","authors":"Ruyu Shi, Huaijun Chen, Wenting Zhang, Rehana K Leak, Dequan Lou, Kong Chen, Jun Chen","doi":"10.1177/0271678X241305914","DOIUrl":null,"url":null,"abstract":"<p><p>Single-cell RNA sequencing (scRNA-seq) is a high-throughput transcriptomic approach with the power to identify rare cells, discover new cellular subclusters, and describe novel genes. scRNA-seq can simultaneously reveal dynamic shifts in cellular phenotypes and heterogeneities in cellular subtypes. Since the publication of the first protocol on scRNA-seq in 2009, this evolving technology has continued to improve, through the use of cell-specific barcodes, adoption of droplet-based systems, and development of advanced computational methods. Despite induction of the cellular stress response during the tissue dissociation process, scRNA-seq remains a popular technology, and commercially available scRNA-seq methods have been applied to the brain. Recent advances in spatial transcriptomics now allow the researcher to capture the positional context of transcriptional activity, strengthening our knowledge of cellular organization and cell-cell interactions in spatially intact tissues. A combination of spatial transcriptomic data with proteomic, metabolomic, or chromatin accessibility data is a promising direction for future research. Herein, we provide an overview of the workflow, data analyses methods, and pros and cons of scRNA-seq technology. We also summarize the latest achievements of scRNA-seq in stroke and acute traumatic brain injury, and describe future applications of scRNA-seq and spatial transcriptomics.</p>","PeriodicalId":15325,"journal":{"name":"Journal of Cerebral Blood Flow and Metabolism","volume":" ","pages":"271678X241305914"},"PeriodicalIF":4.9000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11626557/pdf/","citationCount":"0","resultStr":"{\"title\":\"Single-cell RNA sequencing in stroke and traumatic brain injury: Current achievements, challenges, and future perspectives on transcriptomic profiling.\",\"authors\":\"Ruyu Shi, Huaijun Chen, Wenting Zhang, Rehana K Leak, Dequan Lou, Kong Chen, Jun Chen\",\"doi\":\"10.1177/0271678X241305914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Single-cell RNA sequencing (scRNA-seq) is a high-throughput transcriptomic approach with the power to identify rare cells, discover new cellular subclusters, and describe novel genes. scRNA-seq can simultaneously reveal dynamic shifts in cellular phenotypes and heterogeneities in cellular subtypes. Since the publication of the first protocol on scRNA-seq in 2009, this evolving technology has continued to improve, through the use of cell-specific barcodes, adoption of droplet-based systems, and development of advanced computational methods. Despite induction of the cellular stress response during the tissue dissociation process, scRNA-seq remains a popular technology, and commercially available scRNA-seq methods have been applied to the brain. Recent advances in spatial transcriptomics now allow the researcher to capture the positional context of transcriptional activity, strengthening our knowledge of cellular organization and cell-cell interactions in spatially intact tissues. A combination of spatial transcriptomic data with proteomic, metabolomic, or chromatin accessibility data is a promising direction for future research. Herein, we provide an overview of the workflow, data analyses methods, and pros and cons of scRNA-seq technology. 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Single-cell RNA sequencing in stroke and traumatic brain injury: Current achievements, challenges, and future perspectives on transcriptomic profiling.
Single-cell RNA sequencing (scRNA-seq) is a high-throughput transcriptomic approach with the power to identify rare cells, discover new cellular subclusters, and describe novel genes. scRNA-seq can simultaneously reveal dynamic shifts in cellular phenotypes and heterogeneities in cellular subtypes. Since the publication of the first protocol on scRNA-seq in 2009, this evolving technology has continued to improve, through the use of cell-specific barcodes, adoption of droplet-based systems, and development of advanced computational methods. Despite induction of the cellular stress response during the tissue dissociation process, scRNA-seq remains a popular technology, and commercially available scRNA-seq methods have been applied to the brain. Recent advances in spatial transcriptomics now allow the researcher to capture the positional context of transcriptional activity, strengthening our knowledge of cellular organization and cell-cell interactions in spatially intact tissues. A combination of spatial transcriptomic data with proteomic, metabolomic, or chromatin accessibility data is a promising direction for future research. Herein, we provide an overview of the workflow, data analyses methods, and pros and cons of scRNA-seq technology. We also summarize the latest achievements of scRNA-seq in stroke and acute traumatic brain injury, and describe future applications of scRNA-seq and spatial transcriptomics.
期刊介绍:
JCBFM is the official journal of the International Society for Cerebral Blood Flow & Metabolism, which is committed to publishing high quality, independently peer-reviewed research and review material. JCBFM stands at the interface between basic and clinical neurovascular research, and features timely and relevant research highlighting experimental, theoretical, and clinical aspects of brain circulation, metabolism and imaging. The journal is relevant to any physician or scientist with an interest in brain function, cerebrovascular disease, cerebral vascular regulation and brain metabolism, including neurologists, neurochemists, physiologists, pharmacologists, anesthesiologists, neuroradiologists, neurosurgeons, neuropathologists and neuroscientists.