A combined flow cytometric semen analysis and miRNA profiling as a tool to discriminate between high and low fertility bulls.

With our research we proposed an integrated approach between advanced semen quality analysis and miRNAs profiling of cryopreserved semen in bulls with different fertility in order to identify biomarkers and build a model that can be potentially used for the prediction of male field fertility. Our study confirms that sperm motility traits and parameters related to chromatin structure are associated with field fertility. Fiftten differentially expressed miRNAs, between high and low fertility bulls, were identified. From the multi-dimensional preference analysis, a positive correlation was revealed among specific in vitro quality parameters, specific miRNAs and bulls fertility status. The integrated approach proposed, could provide a model for prediction of fertility that might be beneficial to AI centers in the selection of high-fertility bulls, facilitating the elimination of subfertile subjects or ejaculates with low fertilizing capacity, reducing the economic impact in the breeding industry.