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Background: Single-step genomic best linear unbiased prediction (ssGBLUP) models allow the combination of genomic, pedigree, and phenotypic data into a single model, which is computationally challenging for large genotyped populations. In practice, genotypes of animals without their own phenotype and progeny, so-called genotyped selection candidates, can become available after genomic breeding values have been estimated by ssGBLUP. In some breeding programmes, genomic estimated breeding values (GEBV) for these animals should be known shortly after obtaining genotype information but recomputing GEBV using the full ssGBLUP takes too much time. In this study, first we compare two equivalent formulations of ssGBLUP models, i.e. one that is based on the Woodbury matrix identity applied to the inverse of the genomic relationship matrix, and one that is based on marker equations. Second, we present computationally-fast approaches to indirectly compute GEBV for genotyped selection candidates, without the need to do the full ssGBLUP evaluation. Results: The indirect approaches use information from the latest ssGBLUP evaluation and rely on the decomposition of GEBV into its components. The two equivalent ssGBLUP models and indirect approaches were tested on a six-trait calving difficulty model using Irish dairy and beef cattle data that include 2.6 million genotyped animals of which about 500,000 were considered as genotyped selection candidates. When using the same computational approaches, the solving phase of the two equivalent ssGBLUP models showed similar requirements for memory and time per iteration. The computational differences between them were due to the preprocessing phase of the genomic information. Regarding the indirect approaches, compared to GEBV obtained from single-step evaluations including all genotypes, indirect GEBV had correlations higher than 0.99 for all traits while showing little dispersion and level bias. Conclusions: In conclusion, ssGBLUP predic

Background: Compared to national evaluations, international collaboration projects further improve accuracies of estimated breeding values (EBV) by building larger reference populations or performing a joint evaluation using data (or proxy of them) from different countries. Genomic selection is increasingly adopted in beef cattle, but, to date, the benefits of including genomic information in international evaluations have not been explored. Our objective was to develop an international beef cattle single-step genomic evaluation and investigate its impact on the accuracy and bias of genomic evaluations compared to current pedigree-based evaluations. Methods: Weaning weight records were available for 331,593 animals from seven European countries. The pedigree included 519,740 animals. After imputation and quality control, 17,607 genotypes at a density of 57,899 single nucleotide polymorphisms (SNPs) from four countries were available. We implemented two international scenarios where countries were modelled as different correlated traits: an international genomic single-step SNP best linear unbiased prediction (SNPBLUP) evaluation (ssSNPBLUPINT) and an international pedigree-based BLUP evaluation (PBLUPINT). Two national scenarios were implemented for pedigree and genomic evaluations using only nationally submitted phenotypes and genotypes. Accuracies, level and dispersion bias of EBV of animals born from 2014 onwards, and increases in population accuracies were estimated using the linear regression method. Results: On average across countries, 39 and 17% of sires and maternal-grand-sires with recorded (grand-)offspring across two countries were genotyped. ssSNPBLUPINT showed the highest accuracies of EBV and, compared to PBLUPINT, led to increases in population accuracy of 13.7% for direct EBV, and 25.8% for maternal EBV, on average across countries. Increases in population accuracies when moving from national scenarios to ssSNPBLUPINT were observed for all countries

Many traits of economical relevance in beef cattle are influenced in their phenotypic expression by the dam. Genetic evaluations of maternally affected traits require to model direct, maternal and direct-maternal genetic (co)variances next to non-genetic effects. In Interbeef beef cattle international evaluations, direct-maternal genetic correlations (rdm) may be different both within countries (rdm_WC) and between countries (rdm_BC). rdm_WC for growth traits up to weaning are often reported to be negative and significantly different from zero. As rdm_BC are difficult to estimate, these are currently assumed to be equal to zero in Interbeef evaluations. The objective of this study was to evaluate the impact of using estimated values for rdm_BC instead of assuming them to be zero, on international estimated breeding values (IEBV). We implemented two scenarios that differed only in the modelling of rdm_BC: A) the current Interbeef evaluation with assumes rdm_BC to be 0 and fits estimated rdm_WC, and B) an Interbeef evaluation in which both estimated rdm_WC and rdm_BC were fitted. Weaning weight phenotypes and pedigree information were available for more than 3 million Limousin beef cattle males and females, born between 1972 and 2017, and distributed across ten European countries. We evaluated the impact of ignoring rdm_BC on different groups of animals by comparing animals’ direct and maternal IEBV between scenarios A and B. Ignoring rdm_BC resulted in no re-ranking for direct IEBV, and limited re-ranking for maternal IEBV. Less re-ranking in maternal IEBV was observed with increasing reliability. Moreover, ignoring rdm_BC resulted in no re-ranking for publishable sires, i.e. of sires with IEBV that can be exchanged across countries. Our study suggests that the current practice of ignoring rdm_BC has limited impact on Interbeef evaluations when rdm_BC are close to 0 on average (ranging from +0.14 to -0.14) as is the case for weaning weight.

peer-reviewed, This study sought to compare the in vitro characteristics of fresh and frozen non-sorted (NS) and sex-sorted (SS) bull spermatozoa. Experiment 1: Holstein–Friesian ejaculates (n = 10 bulls) were split across four treatments and processed: (1) NS fresh at 3 × 106 spermatozoa, (2) X-SS frozen at 2 × 106 spermatozoa, (3) X-SS fresh at 2 × 106 spermatozoa and (4) X-SS fresh at 1 × 106 spermatozoa. NS frozen controls of 20 × 106 spermatozoa per straw were sourced from previously frozen ejaculates (n = 3 bulls). Experiment 2: Aberdeen Angus ejaculates (n = 4 bulls) were split across four treatments and processed as: (1) NS fresh 3 × 106 spermatozoa, (2) Y-SS fresh at 1 × 106 spermatozoa, (3) Y-SS fresh at 2 × 106 spermatozoa and (4) X-SS fresh at 2 × 106 spermatozoa. Controls were sourced as per Experiment 1. In vitro assessments for progressive linear motility, acrosomal status and oxidative stress were carried out on Days 1, 2 and 3 after sorting (Day 0 = day of sorting. In both experiments SS fresh treatments had higher levels of agglutination in comparison to the NS fresh (P < 0.001), NS frozen treatments had the greatest PLM (P < 0.05) and NS spermatozoa exhibited higher levels of superoxide anion production compared with SS spermatozoa (P < 0.05). Experiment 1 found both fresh and frozen SS treatments had higher levels of viable acrosome-intact spermatozoa compared with the NS frozen treatments (P < 0.01)., ACCEPTED, peer-reviewed

peer-reviewed, Bovine fertility remains a critical issue underpinning the sustainability of the agricultural sector. Phenotypic records collected on >7,000 bulls used in artificial insemination (AI) were used to identify 160 reliable and divergently fertile bulls for a dual strategy of targeted sequencing (TS) of fertilityrelated β-defensin genes and whole exome sequencing (WES). A haplotype spanning multiple β-defensin genes and containing 94 SNPs was significantly associated with fertility and functional analysis confirmed that sperm from bulls possessing the haplotype showed significantly enhanced binding to oviductal epithelium. WES of all exons in the genome in 24 bulls of high and low fertility identified 484 additional SNPs significantly associated with fertility. After validation, the most significantly associated SNP was located in the FOXJ3 gene, a transcription factor which regulates sperm function in mice. This study represents the first comprehensive characterisation of genetic variation in bovine β-defensin genes and functional analysis supports a role for β-defensins in regulating bull sperm function. This first application of WES in AI bulls with divergent fertility phenotypes has identified a novel role for the transcription factor FOXJ3 in the regulation of bull fertility. Validated genetic variants associated with bull fertility could prove useful for improving reproductive outcomes in cattle.