Fertility is one of the most economically important traits in both beef and dairy cattle production; however, only female fertility is typically subjected to selection. Male and female fertility have only a small positive genetic correlation which is likely due to the existence of a relatively small number of genetic variants within each breed that cause embryonic and developmental losses. Genomic tools have been developed that allow the identification of lethal recessive loci based upon marker haplotypes. Selection against haplotypes harbouring lethal alleles in conjunction with selection to improve female fertility will result in an improvement in male fertility. Genomic selection has resulted in a two to fourfold increase in the rate of genetic improvement of most dairy traits in US Holstein cattle, including female fertility. Considering the rapidly increasing rate of adoption of high-throughput single nucleotide polymorphism genotyping in both the US dairy and beef industries, genomic selection should be the most effective of all currently available approaches to improve male fertility. However, male fertility phenotypes are not routinely recorded in natural service mating systems and when artificial insemination is used, semen doses may be titrated to lower post-thaw progressively motile sperm numbers for high-merit and high-demand bulls. Standardization of sperm dosages across bull studs for semen distributed from young bulls would allow the capture of sire conception rate phenotypes for young bulls that could be used to generate predictions of genetic merit for male fertility in both males and females. These data would allow genomic selection to be implemented for male fertility in addition to female fertility within the US dairy industry. While the rate of use of artificial insemination is much lower within the US beef industry, the adoption of sexed semen in the dairy industry has allowed dairy herds to select cows from which heifer replacements are produced and cows that are used to produce terminal crossbred bull calves sired by beef breed bulls. Capture of sire conception rate phenotypes in dairy herds utilizing sexed semen will contribute data enabling genomic selection for male fertility in beef cattle breeds. As the commercial sector of the beef industry increasingly adopts fixed-time artificial insemination, sire conception rate phenotypes can be captured to facilitate the development of estimates of genetic merit for male fertility within US beef breeds.

The technology available to assess sperm population characteristics has advanced greatly in recent years. Large artificial insemination (AI) organizations that sell bovine semen utilize many of these technologies not only for novel research purposes, but also to make decisions regarding whether to sell or discard the product. Within an AI organization, the acquisition, interpretation and utilization of semen quality data is often performed by a quality control department. In general, quality control decisions regarding semen sales are often founded on the linkages established between semen quality and field fertility. Although no one individual sperm bioassay has been successful in predicting sire fertility, many correlations to various in vivo fertility measures have been reported. The most powerful techniques currently available to evaluate semen are high-throughput and include computer-assisted sperm analysis and various flow cytometric analyses that quantify attributes of fluorescently stained cells. However, all techniques measuring biological parameters are subject to the principles of precision, accuracy and repeatability. Understanding the limitations of repeatability in laboratory analyses is important in a quality control and quality assurance program. Hence, AI organizations that acquire sizeable data sets pertaining to sperm quality and sire fertility are well-positioned to examine and comment on data collection and interpretation. This is especially true for sire fertility, where the population of AI sires has been highly selected for fertility. In the December 2017 sire conception rate report by the Council on Dairy Cattle Breeding, 93% of all Holstein sires (n=2062) possessed fertility deviations within 3% of the breed average. Regardless of the reporting system, estimates of sire fertility should be based on an appropriate number of services per sire. Many users impose unrealistic expectations of the predictive value of these assessments due to a lack of understanding for the inherent lack of precision in binomial data gathered from field sources. Basic statistical principles warn us of the importance of experimental design, balanced treatments, sampling bias, appropriate models and appropriate interpretation of results with consideration for sample size and statistical power. Overall, this review seeks to describe and connect the use of sperm in vitro bioassays, the reporting of AI sire fertility, and the management decisions surrounding the implementation of a semen quality control program.

This work evaluated if an in vitro test, with the combined power of the statistical evaluation of spermatozoa and zona pellucida (ZP) competitive binding ability and a rapid method for accessory sperm counts, could predict the bull fertility. Ten Holstein Friesian bulls of known field fertility (five of high and five of low fertility) were selected. An in vitro heterospermic insemination approach, based on differential staining, was tested on 45 possible pairs of bulls (two batches per bull). Motility and quality (abnormalities and membrane status) seminal characteristics and estimated relative conception rates (ERCR) highlighted only one association between membrane integrity and ERCR (p = 0.007). Differences in ZP binding allowed us to rank bulls into two categories based on low and high binding ability. For eight bulls, this classification reflected the ERCR. Differences between batches were reported for two bulls, in which the effect of heterospermic insemination (the number of sperm binding to ZP from different bulls not in a 1:1 ratio) showed a significant bull-related effect (p < 0.001) in the first batch and no effect (p > 0.05) in the second batch for both bulls. Reduction of the number of oocytes per assay from 25 to 5 had no effect (p > 0.5) on the bulls’ ranking. Our results suggest that in vitro competitive binding is a promising approach for estimating bull fertility and support concepts for further implementation, e.g. drastic reduction of oocyte number in a single pair assay and larger scale testing for batches.