SCAN: a cross-species single-cell transcriptome resource for domestic animals—revealing divergent spermatogenesis in avian and mammalian systems

BACKGROUND: Despite the astonishing growth of livestock single-cell transcriptome data, its full potential is severely limited by the lack of specialized functional databases and annotation tools. The ability to systematically integrate, standardize, and deeply interpret livestock single-cell data remains very limited. RESULTS: This study constructed SCAN, a high-quality resource platform integrating over 2.1 million single-cell datasets from six livestock species (Sus scrofa, Gallus gallus, Bos taurus, Bos grunniens, Ovis aries, and Oryctolagus cuniculus) and a representative model organism (Danio rerio). This dataset covers 33 tissue types and 155 cell types, providing differential gene expression profiles for each cell type. Based on this platform, we developed standardized analysis pipelines and visualization tools, and established a livestock marker gene library and a high-quality chicken single-cell annotation reference dataset (CARD). In addition, to demonstrate the utility of the platform, we used SCAN to perform a cross-species single-cell comparison of spermatogenesis between avian and mammalian species. The analysis showed that the early stages of spermatogenesis were relatively conserved across species, whereas differences increased at the later stages; chicken SPT and sperm were significantly enriched in catabolism-related pathways. These observations suggest that the late stages of chicken spermatogenesis may employ a metabolic strategy distinct from that of mammals, but the underlying mechanisms remain to be validated by functional experiments. CONCLUSIONS: This study provides a unified and standardized resource platform (SCAN) for livestock single-cell data, greatly facilitating data access, cell annotation, and downstream biological exploration, thereby enabling downstream biological discovery-as exemplified by the spermatogenesis study presented in this research. The SCAN database is freely and permanently available at http://www.scanimalsdb.bio-zz.cn .