Biomolecules · 2026
Analytical Methods and Application of Single-Cell and Single-Nucleus Transcriptomics in the Study of Ischemic Stroke.
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Mu Changqing, Ding Yuchuan, Weiss Alexander, Rosenfeld Sydni, Li Fengwu, Geng Xiaokun
Аннотация
BACKGROUND: Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, with complex and heterogeneous pathophysiological processes. Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) has been increasingly applied to investigate cellular heterogeneity at high resolutions.
METHODS: We systematically searched PubMed, Web of Science, and Embase to identify studies that applied sc/snRNA-seq in ischemic stroke research. Based on the retrieved literature, we summarized the bioinformatic analytical methods and application strategies reported in these studies, focusing on how sc/snRNA-seq has been utilized across different research contexts.
RESULTS: The application of sc/snRNA-seq in ischemic stroke has expanded rapidly across species and sample types. A wide range of downstream bioinformatic analyses have been employed, including clustering, differential expression analysis, trajectory inference, gene regulatory network analysis, and cell-cell communication analysis. These approaches have been applied to investigate diverse biological processes in ischemic stroke. In addition, these analytical strategies have been extended to multiple biological contexts, including extracerebral tissues, stroke-related modifiers, and their associated complications. Furthermore, integrative analytical approaches that combine multiple datasets, bulk transcriptomics, and other omics data have been increasingly utilized. Advances in temporal and spatial resolutions have enabled analyses across different stages and anatomical regions.
CONCLUSIONS: This review systematically summarizes the analytical methods and application strategies of sc/snRNA-seq in ischemic stroke. These approaches provide a structured perspective for understanding the application of single-cell technologies in this field. Future studies may benefit from standardized designs and coordinated analytical strategies to facilitate more systematic investigations.
METHODS: We systematically searched PubMed, Web of Science, and Embase to identify studies that applied sc/snRNA-seq in ischemic stroke research. Based on the retrieved literature, we summarized the bioinformatic analytical methods and application strategies reported in these studies, focusing on how sc/snRNA-seq has been utilized across different research contexts.
RESULTS: The application of sc/snRNA-seq in ischemic stroke has expanded rapidly across species and sample types. A wide range of downstream bioinformatic analyses have been employed, including clustering, differential expression analysis, trajectory inference, gene regulatory network analysis, and cell-cell communication analysis. These approaches have been applied to investigate diverse biological processes in ischemic stroke. In addition, these analytical strategies have been extended to multiple biological contexts, including extracerebral tissues, stroke-related modifiers, and their associated complications. Furthermore, integrative analytical approaches that combine multiple datasets, bulk transcriptomics, and other omics data have been increasingly utilized. Advances in temporal and spatial resolutions have enabled analyses across different stages and anatomical regions.
CONCLUSIONS: This review systematically summarizes the analytical methods and application strategies of sc/snRNA-seq in ischemic stroke. These approaches provide a structured perspective for understanding the application of single-cell technologies in this field. Future studies may benefit from standardized designs and coordinated analytical strategies to facilitate more systematic investigations.