Single-Cell Transcriptomics in Spinal Cord Studies: Progress and Perspectives

Single-cell RNA sequencing (scRNA-seq) has revolutionized neuroscience by enabling the analysis of cellular heterogeneity and dynamic molecular processes at single-cell resolution. In spinal cord research, scRNA-seq provides critical insights into cell type diversity, developmental trajectories, and pathological mechanisms. This review summarizes recent progress in applying scRNA-seq to spinal cord development, injury, and neurodegenerative diseases, and discusses current challenges and future directions. Relevant studies were retrieved from PubMed and Web of Science, focusing on key applications of scRNA-seq, including advances in spatial transcriptomics and mul-ti-omics integration. scRNA-seq has enabled the identification of distinct spinal cord cell populations and revealed gene regulatory networks driving development. In injury models, it has uncovered the temporal dynamics of immune and glial responses, alongside potential regenerative processes. In neurodegenerative conditions, scRNA-seq has highlighted cell-specific vulnerabilities and molecular changes. Inte-gration with spatial transcriptomics and computational tools, such as machine learning, has further improved the resolution of spinal cord biology. However, challenges remain in data complexity, sample acquisition, and clinical translation. Single-cell tran-scriptomics is a powerful approach to understanding spinal cord biology. Its integration with emerging technologies will advance both basic research and clinical applications, supporting personalized and regenerative therapies. Addressing technical and analyt-ical barriers is essential to fully realize the potential of scRNA-seq in spinal cord science.