Transcriptomic Profiling of Buffalo Spermatozoa Reveals Dysregulation of Functionally Relevant mRNAs in Low-Fertile Bulls

Although, it is known that spermatozoa harbor a variety of RNAs that may influence embryonic development, little is understood about sperm transcriptomic differences in relation to fertility, especially in buffaloes. In the present study, we compared the differences in sperm functional attributes and transcriptomic profile between high- and low-fertile buffalo bulls. Sperm membrane and acrosomal integrity were lower (P < 0.05), while protamine deficiency and lipid peroxidation were higher (P < 0.05) in low- compared to high-fertile bulls. Transcriptomic analysis using mRNA microarray technology detected a total of 51,282 transcripts in buffalo spermatozoa, of which 4,050 transcripts were differentially expressed, and 709 transcripts were found to be significantly dysregulated (P < 0.05 and fold change >1) between high- and low-fertile bulls. Majority of the dysregulated transcripts were related to binding activity, transcription, translation, and metabolic processes with primary localization in the cell nucleus, nucleoplasm, and in cytosol. Pathways related to MAPK signaling, ribosome pathway, and oxidative phosphorylation were dysregulated in low-fertile bull spermatozoa. Using bioinformatics analysis, we observed that several genes related to sperm functional attributes were significantly downregulated in low-fertile bull spermatozoa. Validation of the results of microarray analysis was carried out using real-time qPCR expression analysis of selected genes (YBX1, ORAI3, and TFAP2C). The relative expression of these genes followed the same trend in both the techniques. Collectively, this is the first study to report the transcriptomic profile of buffalo spermatozoa and to demonstrate the dysregulation of functionally relevant transcripts in low-fertile bull spermatozoa. The results of the present study open up new avenues for understanding the etiology for poor fertility in buffalo bulls and to identify fertility biomarkers.