Journal of dairy science

Sperm viability, reactive oxygen species, and DNA fragmentation index combined can discriminate between above- and below-average fertility bulls.

PMID 28478003


The accurate prediction of bull fertility is of major economic importance in the dairy breeding industry. Sperm fertilizing potential is determined by their ability to reach the oocyte, complete fertilization, and sustain embryogenesis, which is partly determined by the quality of sperm DNA. In the present study, we analyzed several sperm functions required for fertility, including DNA damage, in frozen-thawed spermatozoa of breeding bulls with different adjusted nonreturn rates (NRR56), and identified a suitable combination of parameters that could be used to predict bull fertility. Based on the NRR56, bulls were classified into below- and above-average fertility, a total of 37 characteristics of spermatozoa were evaluated for each bull, and their relationship with bull fertility was studied. Of the different sperm functional attributes, differences were observed in sperm viability, acrosomal integrity, reactive oxygen species, and DNA fragmentation index (%DFI) among below-average, average, and above-average fertility bulls. Principal component analysis also revealed that sperm viability, acrosome status, reactive oxygen species, and %DFI were the important variables, having highest correlation with NRR56. Our results indicated that the proportion of live [correlation coefficient (r) = 0.53] and live acrosome-reacted spermatozoa (r = 0.50) were significantly positively related to NRR56, whereas the proportion of dead spermatozoa (r = -0.53) and %DFI (r = 0.61) were significantly negatively related to NRR56 in bulls. Linear regression analysis indicated that a combination of live [coefficient of determination (R(2)) = 0.72], dead (R(2) = 0.72), live hydrogen peroxide-negative spermatozoa (R(2) = 0.64), and %DFI (R(2) = 0.56) could differentiate below-average and above-average fertility bulls, and thus were considered for development of a fertility prediction model. The accuracy of the developed model for fertility prediction in bulls was high (R(2) = 0.83). We concluded that flow cytometric detection of sperm viability, hydrogen peroxide status, and %DFI could discriminate below- from above-average fertility bulls.