Establishment of a male fertility prediction model with sperm RNA markers in pigs as a translational animal model.

BACKGROUND: Male infertility is an important issue that causes low production in the animal industry. To solve the male fertility crisis in the animal industry, the prediction of sperm quality is the most important step. Sperm RNA is the potential marker for male fertility prediction. We hypothesized that the expression of functional genes related to fertilization will be the best target for male fertility prediction markers. To investigate optimum male fertility prediction marker, we compared target genes expression level and a wide range of field data acquired from artificial insemination of boar semen. RESULTS: Among the genes related to acrosomal vesicle exocytosis and sperm-oocyte fusion, equatorin (EQTN), zona pellucida sperm-binding protein 4 (ZP4), and sperm acrosome membrane-associated protein 3 exhibited high accuracy (70%, 90%, and 70%, respectively) as markers to evaluate male fertility. Combinations of EQTN-ZP4, ZP4-protein unc-13 homolog B, and ZP4-regulating synaptic membrane exocytosis protein 1 (RIMS1) showed the highest prediction value, and all these markers are involved in the acrosome reaction. CONCLUSION: The EQTN-ZP4 model was efficient in clustering the high-fertility group and may be useful for selection of animal that has superior fertility in the livestock industry. Compared to the EQTN-ZP4 model, the ZP4-RIMS1 model was more efficient in clustering the low-fertility group and may be useful in the diagnosis of male infertility in humans and other animals. The appointed translational animal model and established biomarker combination can be widely used in various scientific fields such as biomedical science.