Environmental, management and genetic factors affecting semen production in French Montbéliard bulls

Semen production and semen quality of indigenous buffalo breeds under hot semiarid climatic conditions in India

Semen data comprising of 97,023 ejaculates of 197 bulls from 6 buffalo breeds were analyzed. The traits considered were as follows: ejaculate volume, sperm concentration, mass activity, initial and post-thaw motility, total sperm, and total motile sperm before and after thawing as well as a composite trait equal to the theoretical number of doses which can be produced from each given ejaculate. The objective was to measure the semen production potential of indigenous buffalo bulls and identify factors affecting these traits. A linear mixed model was used, including a random bull effect along with other fixed factors: the order of the ejaculate on a particular day, the interval between collections, the time of collection, the breed, the age at collection, the semen collector, and the year and month of collection. The study showed breed wise variation for all traits. The first ejaculate of a bull on a particular day was superior to the second for nearly all the traits. Longer collection intervals are better than shorter intervals for all the parameters, although short collection interval of 2 to 4 days produced higher yield in terms of total semen doses without hampering semen quality. The study also showed a slight decrease of semen quality with time of collection within a day. The Murrah breed showed comparatively consistent performance during their whole life compared with the other breeds. Repeatability estimates for semen traits were found to be low (0.09 for mass activity) to relatively large (> 0.4 for volume and concentration). A negative correlation was found between bull effects for semen volume and concentration while a high positive correlation was found between mass activity, initial motility, and post-thaw motility. Results of the study will help in suggesting suitable management and breeding plans for semen production traits.

Genetic analysis of semen characteristic traits in young Norwegian Red bulls

The aim of this study was to estimate genetic parameters and genetic trends for male fertility in Norwegian Red bulls. We analyzed data on semen characteristics traits collected at the performance test station of young bulls from 1994 to 2016, in an andrology test used to ensure acceptable semen quality before being selected as an artificial insemination bull. Traits included were volume, concentration, and motility (percentage of moving sperm cells) in fresh samples and after storing for 24 and 48 h, and sperm defects. The data consisted of 14,972 ejaculates from 3,927 young (11-15 mo) Norwegian Red bulls. Genetic parameters were estimated using bivariate linear animal models that included age in months, group-year, and collection-group (main effect of the interaction between ejaculate number and interval between collections) as fixed effects, and test-day and additive genetic and permanent environment effect of the bull as random effects. Considerable genetic coefficients of variation were found for concentration and volume, with lower values for motility. Estimated heritabilities ranged from 0.02 and 0.03 (for sperm defects and motility in fresh samples) to 0.14 (volume and concentration measured on a continuous scale). All estimated genetic correlations were favorable, but the genetic correlations between volume and concentration and volume and sperm defects were not significantly different from zero. The genetic correlations between concentration and motility traits ranged from 0.53 to 0.83, and those between volume and the motility traits were between 0.24 and 0.57. All traits showed a slightly unfavorable genetic trend. Our results indicate that selection of bulls with better sperm quality is possible.

Genetic parameters, predictions, and rankings for semen production traits in a Thailand multi-breed dairy population using genomic-polygenic and polygenic models

The objectives were to compare estimates of variance components, genetic parameters, prediction accuracies, and rankings of bulls for semen volume (VOL), number of sperm (NS), and motility (MOT) using genomic-polygenic (GPRM) and polygenic repeatability models (PRM). The dataset comprised 13,535 VOL, 12,773 NS, and 12,660 MOT from 131 bulls collected from 2001 to 2017 in the Semen Production and Dairy Genetic Evaluation Center of the Dairy Farming Promotion Organization of Thailand. Genotypic data encompassed 76,519 actual and imputed SNP from 72 animals. The three-trait GPRM and PRM included the fixed effects of contemporary group, ejaculate order, age of bull, ambient temperature, and heterosis. Random effects were animal additive genetic, permanent environmental, and residual. Variance components and genetic parameters were estimated using AIREMLF90. GPRM heritabilities were slightly greater than PRM for MOT (0.27 compared with 0.24), and slightly less for VOL (0.11 compared with 0.12), and NS (0.17 compared with 0.19). Repeatabilities were slightly less for GPRM than PRM (0.44 compared with 0.45 for MOT, 0.26 compared with 0.28 for NS, and 0.20 compared with 0.21 for VOL). Additive genetic correlations were high between NS and MOT (GPRM: 0.76, PRM: 0.78), moderate between VOL and NS (GPRM: 0.43, PRM: 0.55), and near zero between VOL and MOT (GPRM: -0.13, PRM: 0.04). Rank correlations between GPRM and PRM estimated breeding values (EBV) were high for all traits. The similarity between GPRM and PRM results suggested that SNP data from the small number of genotyped animals had a minimal impact on genetic predictions in this population.

Genetic correlations between yield traits or days open measured in cows and semen production traits measured in bulls

We used a bivariate animal model to investigate the genetic correlations between yield traits or days open (DO) as characters measured in cows and semen production traits as characters measured in bulls. Lactation records of 305-day milk, fat, and protein yields, and DO, from 386 809 first-lactation Holstein cows in Hokkaido, Japan, that calved between 2008 and 2014 were used. Semen production records were collected between 2005 and 2014 and included volume per ejaculate (VOL), sperm concentration (CON), number of sperm per ejaculate (NUM), progressive motility index of sperm (MOT), and MOT after freeze-thawing (A-MOT). Number of sperm per ejaculate was log-transformed into a NUM score (NUMS). A total of 30 373 semen production records from 1196 bulls were obtained. The pedigree file used for analysing the records was involving 885 345 animals. Heritability was estimated for VOL (0.42), CON (0.12), NUMS (0.37), MOT (0.08), and A-MOT (0.11). Weak and negative genetic correlations were recorded between yield traits measured in cows and VOL, CON or NUMS measured in bulls. Moderate and negative genetic correlations were obtained between DO and MOT (-0.42) or A-MOT (-0.43). Selection focused on MOT or A-MOT measured in bulls may therefore improve DO measured in cows.

Clinical, ultrasonographic and pathological findings in a bull with segmental aplasia of the mesonephric duct

On assessment for use in an AI stud, a 12-month-old bull was found to produce low volume ejaculates with 41% of the sperm having morphological abnormalities. No left epididymal tail was palpable and the head of the epididymis on the left was twice the size compared with the right. Ultrasound examination showed the left testis to contain a large central area of decreased echogenicity, which could be followed proximally to a 15-mm echolucent lesion at the site of the epididymal head. Postmortem examination revealed a 15-mm diameter cyst in the region of the left epididymal head, and absence of the body and tail of the epididymis. The mediastinum testis of the left testis was dilated, corresponding to the area of decreased echogenicity observed on ultrasonography. No left seminal vesicle was present and the ampulla was significantly smaller than the same structure on the right. Histological examination revealed incomplete or absent spermatogenesis involving the majority of seminiferous tubules in the left testis, and a small proportion of those of the right testis. The cystic structure at the site of the left epididymal head was lined by irregular, sometimes attenuated, epithelium and contained sparse spermatozoa. This case demonstrates the adverse impact, which segmental aplasia of the mesonephric duct had on the testicular and epididymal function of a bull, and highlights the importance of careful clinical assessment in its diagnosis.

Impact of genetic selection on management of boar replacement

Boars in an artificial insemination centre have been selected for their superior genetic potential, with 'superior' being defined as having traits the customer wants transmitted to his herd. The ability to meet the customers' needs depends on the heritability of the trait, the geneticist's success in devising a selection scheme for the trait in balance with other economically important traits, and the boar's ability to produce sperm that can fertilise oocytes. Genetic evaluation research over the past 20 years has greatly increased the number of traits for which a boar can be selected: currently in the Canadian national program, these include age at 100 kg, backfat at 100 kg, feed efficiency, lean yield and litter size. In the near future, traits that are very likely to be added to this selection list include piglet survival, marbling, loin eye area and structure traits. In Canada, sires are ranked on two estimated breeding value (EBV) indices; one, focused on development of terminal sire lines, is based on the growth and yield traits and another, primarily focused on maternal line development, de-emphasises these traits and incorporates litter size. Boars that are in Canadian AI centres because of their excellent growth traits are typically in the top 5-10% of the national population for terminal sire line index, but they may be only average or substandard for litter size. Conversely, boars selected to be in the top 5-10% for conveying such reproductive traits as litter size may only be in the top 33% for growth traits. The more offspring from a superior boar in either of these indices, the faster the population average for the trait improves. The original sire gets knocked out of the elite group, is culled and replaced by a higher ranked young boar from the now improved general population. Although genetic superiority should govern an AI centre's selection and culling of boars, decision-making in real life is seldom that simple. Selection criteria may be contradictory as above, or a boar with truly superior traits may be excluded because a newly-developed molecular genetics test determines he carries an undesirable gene such as PSS, RN or others being developed. Selection for terminal sire or maternal line traits can ignore important practical factors that affect an AI centre--boars with superior genetics may not produce good semen because skeletal or penile problems prevent ejaculation, or because sperm production is poor due to a genetic flaw, disease, or some other cause. Interestingly, selection pressure for one trait may inadvertently select for a trait that is linked but whose linkage is unrecognised, and such unintentionally selected genes could benefit, harm, or have no effect on production traits. An AI centre serving a variety of customers must select boars in anticipation of their customers' needs (including new, foreign and niche markets). A centre should also review its genetic evaluation results and progeny records, both to critique its own selection success and to try to detect unexpected linkages. Finally, an AI centre needs to predict its own future, selecting not just for production traits for the swine producer, but also for factors that enhance the centre's efficiency including boar conformation and temperament, and sperm quantity, quality and hardiness. Can we select for efficiency? Our colleagues in dairy cattle AI evaluate bull performance--should the swine industry consider evaluation of male fertility traits?