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Updated: Jan 29, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
Spatiotemporal dynamics of spermatogenesis: insights from high-resolution spatial transcriptomics and pseudotime
Han Liang1, Jianlong Sun1, Zaoxu Xu1
1Shenzhen Salus BioMed Co., Ltd., Shenzhen, Guangdong, China.
None:
The molecular basis of spermatogenesis, which is a tightly regulated spatiotemporal process in testicular seminiferous tubules where germ cell differentiation and somatic-germ cell interactions drive sperm production, remains incompletely understood. Histological staining techniques lack molecular resolution, while scRNA-seq loses spatial context. Conventional spatial transcriptomics (approx. 100 μm resolution) is too coarse-grained for testicular cells (10-20 μm in diameter), leading to mixed-cell signals. In this study, we used Salus-STS high-resolution spatial transcriptomics (∼1 μm resolution) and Salus Cellbins Algorithm to characterize the spatial transcriptomic profile of mouse testes at single-cell level. Integrating the spatial data with scRNA-seq via RCTD annotated major cell subtypes, whose distributions aligned with histology. Pseudotime and spatial gradient analyses revealed a basement membrane-to-lumen developmental axis, with luminal genes (e.g., Prm2) enriched in sperm maturation and basal genes (e.g., mt-Nd4) linked to mitochondrial metabolism-validated by PPI and GO analyses. The biological relevance of these marker genes is underscored by the fact that mutations in Prm2 and mt-Nd4 are known to be associated with human male infertility, highlighting their potential diagnostic value. This work enables high-resolution dissection of spermatogenesis' spatiotemporal dynamics, providing insights into male reproductive biology.
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