RNA isolation from crossbred bull spermatozoa for analysing differential abundance of sperm specific gene transcripts - Ganguly, Indrajit; Sushil Kumar; Gaur, G K; Singh, Umesh; Mandal, D K; Mahesh Kumar; Bagchi, Indranil; Roy, Bimlendu; Sunil Kumar; Mann, Sandeep; Rani Singh (Journal of Livestock Biodiversity, 2025)
Although mature spermatozoa seem to be transcriptionally inert, however, thousands of mRNA transcripts have been reported to be present inside the mature sperm, being trapped during the course of spermatogenesis. These remnants RNAs may perhaps serve as a potential “markers” of spermatogenesis by virtue of their involvement, directly or indirectly, in the process of fertilization, early embryonic cleavage, and fertility. Gene expression profiling of mammalian sperm is a novel non-invasive tool to evaluate male fertility. RNA isolation from sperm is little tricky in contrast to RNA isolation from testis, and required stringent RNA quality control. The present study demonstrates a comprehensive RNA isolation protocol from crossbred Frieswal (HF X Sahiwal) bull semen, with stringent quality/purity checking, critically required for studying differential abundance of sperm transcripts. Initially, semen samples were subjected to discontinuous (45:90) Percoll gradient centrifugation, explicitly eliminating damaged spermatozoa and contaminating somatic cells. Total RNA was extracted from sperm pellets using heated Tri reagent and an on-column DNase treatment was carried out. The cDNA was synthesized using RT-PCR. The cDNA samples were then amplified by PCR using specific intron spanning primers to rule out contamination, if any, within isolated sperm RNA by g-DNA (PRM1 and DAZL), testicular germ cells like spermatocytes (KIT), epithelial cells (E-cadherin- CDH1) and leucocyte (CD4 and CD45). Further, the presence of transcripts like DazL, PRM1, PRM2, PRM3, TNP1, and TNP2 were also demonstrated in the ejaculated spermatozoa by PCR amplification. This method together with rigorous quality assurance mentioned here are minimum requirement for bias free analysis of differential abundance of sperm transcripts as well as high throughput transcriptomics research.