To characterize the transcriptional profile of ischemic stroke (IS) and analyze the characteristics of specific cell subpopulations by single-cell sequencing (scRNA-seq). Methods: The public scRNA-seq dataset GSE174574 of IS mouse brain tissues and ipsilateral hemisphere (sham) tissues was obtained from the Gene Expression Omnibus (GEO) database. Samples of three IS lesions and three sham tissues were integrated respectively. Following filtering and quality control, batch effects were corrected using the Harmony method for downstream analysis. UMAP was used to generate cell subpopulation clusters, with annotations completed by SingleR and manual methods. Differential expression analysis and GSVA functional enrichment analysis were then performed. The Monocle2 algorithm was used to evaluate the evolutionary state and developmental trajectory of the cells. The CellChat algorithm was used to characterize cellular communication. Results: After rigorous quality control, a total of 29 920 cells from three IS samples were included. UMAP dimensionality reduction identified 22 cell subpopulations, of which 10 were annotated. Endothelial cells and macrophages were more prevalent in the IS samples. For the sham group, 27259 cells were included, resulting in 18 cell subpopulations, with 9 annotated. Compared to the IS group, the sham group had a significantly higher proportion of microglia, whereas the proportions of macrophages, monocytes, and epithelial cells were lower. Further analysis of IS samples showed that astrocytes could be divided into seven subpopulations (C0～C6), with a significant positive correlation in C0～C3 group. The C0 group developed earlier, while the C4 and C5 groups developed later. Oligodendrocytes could be divided into six cell subpopulations (C0～C5), with C3 developing earlier and C2 developing later. Signal transduction between oligodendrocytes mainly occurred via the PSAP pathway, with closer interactions between C0 and C1 groups and other oligodendrocyte subgroups. Immune cells included granulocytes, macrophages, monocytes and natural killer (NK) cells. Granulocytes and monocytes mediated macrophage tolerance and antiviral immune responses, while NK cells were less responsive to endogenous stimuli. Trajectory analysis showed that granulocytes and monocytes were in the early stage of immune cell development while NK cells and macrophages were in the later stages. Intercellular signaling pathways included CCL, SPP1, and CXCL pathways, with the CCL pathway being the largest proportion. Monocytes exhibited more interactions with other cells, while NK cells showed fewer interactions. Conclusion: This study characterized the transcriptional profile of IS and the relationships between various cell subpopulations at single-cell resolution. Comparison with sham samples revealed the specific characteristics and important roles of astrocytes, oligodendrocytes, and various immune cells in the progression of IS under the brain's inflammatory microenvironment. Immune cell subpopulations accounted for a large proportion of all cells, exhibiting multiple functions in immune regulation, anti-inflammatory response, and homeostasis.