Optimization of sperm RNA processing for developmental research.

Recent studies have demonstrated the significance of sperm RNA function as a transporter of important information directing the course of life. To determine the message contained in sperm RNA, it is necessary to optimize transcriptomic research tools. The current study was performed to optimize the processing of sperm RNA from sample storage to quantitative real-time PCR and assess the corresponding method with to evaluate male fertility and its representative markers, equatorin (EQTN) and peroxiredoxin (PRDX). Following successive steps of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines, several options were compared using boar spermatozoa. To evaluate the optimized procedures, the relationship between mRNA expression of EQTN and PRDX in spermatozoa and the fertility (litter size) of 20 individual boars was assessed. Unexpectedly, DNase treatment during RNA isolation had the deleterious effect by decreasing the RNA concentration by 56% and eliminating the correlation between EQTN and PRDX4 mRNA expression and male fertility. Moreover, when sperm RNA was processed using the corresponding method, the results showed the highest exon sequence expression, male fertility prediction power, and consistency. This optimized protocol for predicting male fertility can be used to study the transport of messages directing the life course from spermatozoon to offspring.

Porcine seminal protein-I and II mRNA expression in boar spermatozoa is significantly correlated with fertility.

In recent years, genomic and proteomic biomarkers have been identified for the diagnosis of male fertility to overcome the limitations of conventional semen analysis. Owing to the limited genes available so far, the single gene approach is commonly adopted for analyzing the phenotype of interest. However, the single-gene approach is less effective than multiple-gene strategies for diagnosing a desirable phenotype. Herein, we investigate the ability of two fertility-related genomic markers (porcine seminal protein (PSP)-I and PSP-II) in spermatozoa to predict boar litter size in addition to conventional semen parameters. First, we examined different semen parameters (motility, motion kinematics, and capacitation status) and gene expression in high- and low-litter size boar spermatozoa. Then, we evaluated the correlation of these parameters with the fertility of 21 Yorkshire boars. Finally, we investigated the efficacy of single/combined markers to predict male fertility using a comprehensive statistical model. Our result showed that there were no significant differences in sperm motility, motion kinematics, or capacitation status, however, the mRNA expression of PSP-I and PSP-II in spermatozoa was significantly different in high- and low-litter size boars. In the individual screening test, the expression of both genes was negatively correlated with boar fertility (r = 0-0.578 and -0.456, respectively), whereas only hyperactivation (HYP) showed a positive correlation (r = 0.444) among the tested semen parameters. As single markers, PSP-I and PSP-II have a better diagnostic power to predict boar fertility, regardless of HYP, in quality assessment analyses. In addition, when these markers were combined, the positive predictive value, negative predictive value, and overall test effectiveness for fertility detection were improved. Surprisingly, when PSP-I and PSP-II were considered together, the deviation of the predicted average litter size between high- and low-litter size boars was 1.77. Based on the findings, we suggest that the use of genomic markers in spermatozoa rather than commonly analyzed semen parameters may be more accurate for evaluating male fertility. Moreover, using a combination of markers could increase the overall accuracy of (in)fertility predictions, and thus, could be considered for field application.

Sperm solute carrier family 9 regulator 1 is correlated with boar fertility.

Predicting male fertility is extremely important for artificial insemination and profitable farm management. Conventional semen assessment together with computer-assisted sperm analysis is widely used to predict male fertility under field conditions. However, the clinical validation and sensitivity of these methods remain unclear. Therefore, a new approach is needed to predict male fertility. Here, we investigated the use of a transcriptomic marker (solute carrier family 9, subfamily A, member 3, regulator 1; SLC9A3R1) together with sperm motility parameters and capacitation status to predict fertility/infertility in boars at the commercial level. Our data showed that among motility parameters and the capacitation status, hyperactivation (HYP) differed between high- and low-litter size boars. HYP showed a significant positive correlation (R = 0.468) with boar litter size. Simultaneously, the expression of SLC9A3R1, a gene important in sperm ion channel regulation, was significantly negatively correlated (R = -0.523) with boar litter size. Quality assessment revealed that both HYP and SLC9A3R1 showed considerable sensitivity (71.43 vs. 100%), specificity (100 vs. 71.43%), and overall accuracy (90%) for predicting male fertility. Interestingly, the potential of SLC9A3R1 expression to increase the average piglet number per breeding was higher (0.7 piglets) than that of HYP (0.5 piglets). Thus, measuring SLC9A3R1 expression in spermatozoa may be a more accurate marker for evaluating male fertility/infertility than conventionally used motility parameters and capacitation status.