[Expression of the Ces5a gene in the rat testis].

OBJECTIVE: To study the expression of the Ces5a gene in the development of the rat testis. METHODS: Using RT-PCR, Western blot, immunohistochemistry and HE staining, we determined the mRNA transcription level, protein expression and localization of the Ces5a gene in the testes of three litters of rats at different postnatal (PN) days. RESULTS: The expression of Ces5a mRNA was found in the testis tissue of the rats at 2－65 PN days, low at 2－12 days, decreased to the lowest level at 14－16 days (P < 0.05), but significantly increased at 20－35 days (P < 0.05), and elevated to the highest level at 40－65 days (P < 0.05). The expression of the Ces5a protein was also observed in the testis tissue of the rats at 2－65 PN, low at 2－12 days, with no significant change at 14－16 days (P > 0.05), but markedly increased at 20－35 days (P < 0.05), and again with no significant change at 40－65 days (P > 0.05). The Ces5a protein was expressed in the spermatogonia, spermatocytes and round sperm cells. CONCLUSIONS: The Ces5a gene may be involved in the proliferation and meiosis of rat spermatogonia and play a special role in round spermatogenesis and sperm deformation.

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.