In the current era of genomic selection, there is an increased demand to collect semen from genomically selected sires at a young age. The objective of this study was to assess the effect of bull age, ejaculate number, and season of collection on semen production (ejaculate volume, sperm concentration, and total sperm number; TSN) and sperm motility (prefreeze and post-thaw total and gross motility) parameters in Holstein Friesian bulls in a commercial artificial insemination (AI) center. The study involved the interrogation of a large dataset collected over a 4-yr period, (n = 8,983 ejaculates; n = 176 Holstein Friesian bulls aged between 9 mo and 8 yr). Bulls aged less than 1 yr had the poorest semen production and sperm motility values for all parameters assessed compared with bulls older than 1 yr (P < 0.01). First ejaculates had greater semen production and greater prefreeze motility values than second consecutive ejaculates (P < 0.01), but despite this, there was no difference in post-thaw motility. When subsequent ejaculates were collected from bulls aged less than 1 yr, semen production and sperm motility did not differ compared with mature bulls. Semen collected in winter was poorest in terms of sperm concentration and TSN, but best in terms of post-thaw motility (P < 0.01). In conclusion, second ejaculates can be collected, particularly from bulls aged less than 1 yr, without a significant decrease in post-thaw sperm motility, thus may be a useful strategy to increase semen availability from young genomically selected AI bulls in high demand.

The ability to predict the fertility of bulls before semen is released into the field has been a long-term objective of the animal breeding industry. However, the recent shift in the dairy industry towards the intensive use of young genomically selected bulls has increased its urgency. Such bulls, which are often in the highest demand, are frequently only used intensively for one season and consequently there is limited time to track their field fertility. A more pressing issue is that they produce fewer sperm per ejaculate than mature bulls and therefore there is a need to reduce the sperm number per straw to the minimum required without a concomitant reduction in fertility. However, as individual bulls vary in the minimum number of sperm required to achieve their maximum fertility, this cannot be currently achieved without extensive field-testing. Although an in vitro semen quality test, or combination of tests, which can accurately and consistently determine a bull’s fertility and the optimum sperm number required represent the ‘holy grail’ in terms of semen assessment, this has not been achieved to date. Understanding the underlying causes of variation in bull fertility is a key prerequisite to achieving this goal. In this review, we consider the reliability of sire conception rate estimates and then consider where along the pregnancy establishment axis the variation in reproductive loss between bulls occurs. We discuss the aetiology of these deficiencies in sperm function and propose avenues for future investigation.

In vitro methods of assessing bull semen quality in artificial insemination (AI) centers are unable to consistently detect individuals of lower fertility, and attempts to reliably predict bull fertility are still ongoing. This highlights the need to identify robust biomarkers that can be readily measured in a practical setting and used to improve current predictions of bull fertility. In this study, we comprehensively analyzed a range of functional, morphological, and intracellular attributes in cryopreserved spermatozoa from a selected cohort of Holstein Friesian AI bulls classified as having either high or low fertility (n = 10 of each fertility phenotype; difference of 11.4% in adjusted pregnancy rate between groups). Here, spermatozoa were assessed for motility and kinematic parameters, morphology, acrosome integrity, plasma membrane lipid packing, viability (or membrane integrity), superoxide production, and DNA integrity. In addition, spermatozoa were used for in vitro fertilization to evaluate their capacity for fertilization and successful embryo development. The information collected from these assessments was then used to phenotypically profile the 2 groups of bulls of divergent fertility status as well as to develop a model to predict bull fertility. According to the results, acrosome integrity and viability were the only sperm attributes that were significantly different between high- and low-fertility bulls. Interestingly, although spermatozoa from low-fertility bulls, on average, had reduced viability and acrosome integrity, this response varied considerably from bull to bull. Principal component analysis revealed a sperm phenotypic profile that represented a high proportion of ejaculates from low-fertility bulls. This was constructed based on the collective influence of several sperm attributes, including the presence of cytoplasmic droplets and superoxide production. Finally, using the combined results as a basis for modeling, we developed a linear model that was able to explain 47% of the variation in bull field fertility in addition to a logistic predictive model that had a 90% chance of distinguishing between fertility groups. Taken together, we conclude that viability and acrosome integrity could serve as fertility biomarkers in the field and, when used alongside other sperm attributes, may be useful in detecting low-fertility bulls. However, the variable nature of low-fertility bulls suggests that additional, in-depth characterization of spermatozoa at a molecular level is required to further understand the etiology of low fertility in dairy bulls.