An integrated single-cell transcriptomic dataset for Mouse cortex

As the central functional hub of the central nervous system, the cerebral cortex has long been a major frontier in neuroscience research. With the increasing maturity and widespread application of single-cell RNA sequencing technologies, multiple studies leveraging this technology have been conducted to systematically decipher the complexity and diversity of cortical cellular composition. However, substantial variations in sequencing platforms, cohort sizes, and sequencing depth have impeded deeper investigation into the functions of cortical cells and their underlying molecular mechanisms. Here we present a comprehensive cortical transcriptome dataset integrating multimodal data from 9 mouse datasets, encompassing 10x and Drop-seq (single-cell/nucleus) profiling. Following rigorous quality control, we systematically analyzed 173,081 high-quality cells, providing a comprehensive characterization of cellular composition, intercellular communication networks, chromatin accessibility, and functional properties. To evaluate the cross-species relevance of our findings, we performed comparative analyses with single-cell datasets of mixed cortical tissues from humans, chimpanzees, bonobos, and macaques (n = 29,353). This integrated resource provides a foundational reference for cortical transcriptomes and a standardized framework for cross-platform integration.