Enhanced fertility prediction of cryopreserved boar spermatozoa using novel sperm function assessment

Due to reduced fertility, cryopreserved semen is seldom used for commercial porcine artificial insemination (AI). Predicting the fertility of individual frozen ejaculates for selection of higher quality semen prior to AI would increase overall success. Our objective was to test novel and traditional laboratory analyses to identify characteristics of cryopreserved spermatozoa that are related to boar fertility. Traditional post-thaw analyses of motility, viability, and acrosome integrity were performed on each ejaculate. In vitro fertilization, cleavage, and blastocyst development were also determined. Finally, spermatozoa-oviduct binding and competitive zona-binding assays were applied to assess sperm adhesion to these two matrices. Fertility of the same ejaculates subjected to laboratory assays was determined for each boar by multi-sire AI and defined as (i) the mean percentage of the litter sired and (ii) the mean number of piglets sired in each litter. Means of each laboratory evaluation were calculated for each boar and those values were applied to multiple linear regression analyses to determine which sperm traits could collectively estimate fertility in the simplest model. The regression model to predict the percent of litter sired by each boar was highly effective (p < 0.001, r(2) = 0.87) and included five traits; acrosome-compromised spermatozoa, percent live spermatozoa (0 and 60 min post-thaw), percent total motility, and the number of zona-bound spermatozoa. A second model to predict the number of piglets sired by boar was also effective (p < 0.05, r(2) = 0.57). These models indicate that the fertility of cryopreserved boar spermatozoa can be predicted effectively by including traditional and novel laboratory assays that consider functions of spermatozoa.