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This study investigated the potential application of genomic selection under a multi-breed scheme in the Spanish autochthonous beef cattle populations using a simulation study that replicates the structure of linkage disequilibrium obtained from a sample of 25 triplets of sire/dam/offspring per population and using the BovineHD Beadchip. Purebred and combined reference sets were used for the genomic evaluation and several scenarios of different genetic architecture of the trait were investigated. The single-breed evaluations yielded the highest within-breed accuracies. Across breed accuracies were found low but positive on average confirming the genetic connectedness between the populations. If the same genotyping effort is split in several populations, the accuracies were lower when compared with single-breed evaluation, but showed a small advantage over small-sized purebred reference sets over the accuracies of subsequent generations. Besides, the genetic architecture of the trait did not show any relevant effect on the accuracy with the exception of rare variants, which yielded slightly lower results and higher loss of predictive ability over the generations.

Transmission ratio distortion (TRD) is the departure from the expected Mendelian ratio in offspring, a poorly investigated biological phenomenon in livestock species. Given the current availability of specific parametric methods for the analysis of segregation data, this study focused on the screening of TRD in 602 402 single nucleotide polymorphisms covering all autosomal chromosomes in seven Spanish beef cattle breeds. On average, 0.13% (n = 786) and 0.01% (n = 29) of genetic markers evidenced sire- or dam-specific TRD respectively. There were no single nucleotide polymorphisms accounting for both sire- and dam-specific TRD at the same time, and only one marker (rs43147474) accounted for (sire-specific) TRD in all seven breeds. It must be noted that rs43147474 is located in the fourth intronic region of the GTP-binding protein 10 gene, and this locus has been previously linked to the maintenance of mitochondria and nucleolar architectures. Alternatively, other candidate genes surround this hot-spot for sire-specific TRD in the cattle genome, and they are related to embryonic and postnatal lethality as well as prostate cancer, among others. This research characterized the distribution of TRD in the bovine genome, highlighting heterogeneous results when comparing across breeds., (© 2016 Stichting International Foundation for Animal Genetics.)

Background: Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations., Results: Analysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic-pituitary-thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors., Conclusions: We show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits.

Demographic and pedigree analyses describe the structure and dynamics of livestock populations. We studied information recorded in the herdbooks of Asturiana de los Valles (AV; N = 458,806), Avileña-Negra Ibérica (ANI; N = 204,623), Bruna dels Pirineus (BP; N = 62,138), Morucha (Mo; N = 65,350), Pirenaica (Pi; N = 217,428), Retinta (Re; N = 135,300), and Rubia Gallega (RG; N = 235,511) beef breeds from their creation until 2009. All breeds have increased in the number of registered cows in recent years. In all breeds, herds do not behave as isolated entities and a high rate of exchange of breeding males between herds exists. A percentage of herds (12-52%) make some type of selection and sell bulls to other herds. There were large differences in average number of progeny per bull, ranging from 15.6 (AV) to 373.7 animals (RG, with a high incidence of AI). Generation interval estimates ranged from 4.7 (AV) to 7.6 (RG) yr in the sire pathway and from 5.95 (AV) to 7.8 (Mo) yr in the dam pathway. Density of pedigrees varied among breeds, with Pi, ANI, and Re having the more dense pedigrees, with average completeness indexes of more than 96% in the first generation and 80% when 6 generations were considered. A general increase in average inbreeding was observed in all breeds in the years analyzed. For animals born in 2009, average inbreeding coefficients ranged from 0.6 (BP) to 7.2% (Re) when all animals were considered and from 3.6 (Pi) to 17.6% (BP) when only inbred animals were considered. Due to the lack of completeness of pedigrees in most populations, inbreeding coefficients may be considered as a lower bound of the true parameters. The proportion of inbred animals tended to increase in the periods analyzed in all breeds. Differences between inbreeding and coancestry rates (except in RG) suggest the presence of population structure. Effective population size (Ne) based on the inbreeding rate estimated by regression ranged from 43 to 378 for Re and BP, whereas Ne estimates based on coancestry were greater, with a range of 100 for RG to 9,985 for BP. These facts suggest that an adequate mating policy can help to monitor inbreeding so as not to lose genetic variability. Effective number of ancestors in 2009 for 6 of the breeds ranged from 42 (RG) to 220 (AV), with BP having much a greater value, and was lower than was the effective number of founders in all breeds, suggesting the existence of bottlenecks.

Background: Beef carcass conformation and fat cover scores are measured by subjective grading performed by trained technicians. The discrete nature of these scores is taken into account in genetic evaluations using a threshold model, which assumes an underlying continuous distribution called liability that can be modelled by different methods., Methods: Five threshold models were compared in this study: three threshold linear models, one including slaughterhouse and sex effects, along with other systematic effects, with homogeneous thresholds and two extensions with heterogeneous thresholds that vary across slaughterhouses and across slaughterhouse and sex and a generalised linear model with reverse extreme value errors. For this last model, the underlying variable followed a Weibull distribution and was both a log-linear model and a grouped data model. The fifth model was an extension of grouped data models with score-dependent effects in order to allow for heterogeneous thresholds that vary across slaughterhouse and sex. Goodness-of-fit of these models was tested using the bootstrap methodology. Field data included 2,539 carcasses of the Bruna dels Pirineus beef cattle breed., Results: Differences in carcass conformation and fat cover scores among slaughterhouses could not be totally captured by a systematic slaughterhouse effect, as fitted in the threshold linear model with homogeneous thresholds, and different thresholds per slaughterhouse were estimated using a slaughterhouse-specific threshold model. This model fixed most of the deficiencies when stratification by slaughterhouse was done, but it still failed to correctly fit frequencies stratified by sex, especially for fat cover, as 5 of the 8 current percentages were not included within the bootstrap interval. This indicates that scoring varied with sex and a specific sex per slaughterhouse threshold linear model should be used in order to guarantee the goodness-of-fit of the genetic evaluation model. This was also observed in grouped data models that avoided fitting deficiencies when slaughterhouse and sex effects were score-dependent., Conclusions: Both threshold linear models and grouped data models can guarantee the goodness-of-fit of the genetic evaluation for carcass conformation and fat cover, but our results highlight the need for specific thresholds by sex and slaughterhouse in order to avoid fitting deficiencies.

Background: A procedure to measure connectedness among herds was applied to a beef cattle population bred by natural service. It consists of two steps: (a) computing coefficients of determination (CDs) of comparisons among herds; and (b) building sets of connected herds., Methods: The CDs of comparisons among herds were calculated using a sampling-based method that estimates empirical variances of true and predicted breeding values from a simulated n-sample. Once the CD matrix was estimated, a clustering method that can handle a large number of comparisons was applied to build compact clusters of connected herds of the Bruna dels Pirineus beef cattle. Since in this breed, natural service is predominant and there are almost no links with reference sires, to estimate CDs, an animal model was used taking into consideration all pedigree information and, especially, the connections with dams. A sensitivity analysis was performed to contrast single-trait sire and animal model evaluations with different heritabilities, multiple-trait animal model evaluations with different degrees of genetic correlations and models with maternal effects., Results: Using a sire model, the percentage of connected herds was very low even for highly heritable traits whereas with an animal model, most of the herds of the breed were well connected and high CD values were obtained among them, especially for highly heritable traits (the mean of average CD per herd was 0.535 for a simulated heritability of 0.40). For the lowly heritable traits, the average CD increased from 0.310 in the single-trait evaluation to 0.319 and 0.354 in the multi-trait evaluation with moderate and high genetic correlations, respectively. In models with maternal effects, the average CD per herd for the direct effects was similar to that from single-trait evaluations. For the maternal effects, the average CD per herd increased if the maternal effects had a high genetic correlation with the direct effects, but the percentage of connected herds for maternal effects was very low, less than 12%., Conclusions: The degree of connectedness in a bovine population bred by natural service mating, such as Bruna del Pirineus beef cattle, measured as the CD of comparisons among herds, is high. It is possible to define a pool of animals for which estimated breeding values can be compared after an across-herds genetic evaluation, especially for highly heritable traits.

The implementation of genetic groups in BLUP evaluations accounts for different expectations of breeding values in base animals. Notwithstanding, many feasible structures of genetic groups exist and there are no analytical tools described to compare them easily. In this sense, the recent development of a simple and stable procedure to calculate the Bayes factor between nested competing models allowed us to develop a new approach of that method focused on compared models with different structures of random genetic groups. The procedure is based on a reparameterization of the model in terms of intraclass correlation of genetic groups. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null intraclass correlation. It compares two nested models, a model with a given structure of genetic groups against a model without genetic groups. The calculation of the Bayes factor between different structures of genetic groups can be quickly and easily obtained from the Bayes factor between the nested models. We applied this approach to a weaning weight data set of the Bruna dels Pirineus beef cattle, comparing several structures of genetic groups, and the final results showed that the preferable structure was an only group for unknown dams and different groups for unknown sires for each year of calving.

Although inbreeding (F) is a topic of major concern in animal breeding, estimates of inbreeding depression are usually obtained by modeling the overall F coefficient of each individual, without considering that the recessive (deleterious) genetic load of a given population may be unevenly distributed among the founder genomes. The founder-specific partial F coefficient is calculated as the identity-by-descent probability at any given autosomal locus related to a particular founder and allows a more detailed analysis of inbreeding depression on productive traits. Within this context, birth BW data from 2,459 Ripollesa lambs were analyzed under a hierarchical animal model without F-related covariates (model 0), with inbreeding depression modeled by the overall F coefficient (model F1), or by the partial F coefficient of 9 founders that made a relevant contribution to the population inbreeding (model F2). A straightforward empirical Bayes factor (BF) was developed for testing statistical relevance of each F-related covariate, in which greater-than-1 values favored the model including the covariate. The deviance information criterion (DIC) clearly supported model F1 (5,767.8) rather than model 0 (5,771.2), suggesting that inbreeding depression had a relevant influence on birth BW data. The linear effect of inbreeding depression was statistically relevant in model F1 (BF = 2.52 × 1035), with lamb birth BW declining by -13.6 g with each 1% F increase. The quadratic effect of inbreeding depression was almost null in model F1 (BF = 0.02), as suggested by the reduction in DIC (5,766.9) when this effect was removed from model F1. On the other hand, model F2 provided a similar DIC (5,767.9) value, with this parameter decreasing to 5,764.7 when nonrelevant founder-specific inbreeding depression effects were removed. Substantial heterogeneity in founder-specific inbreeding depression was reported by model F2, in which estimates for 4 of the 9 founders did not differ from zero (BF between 0.05 and 0.42), whereas 5 founders originated moderate (-8.2 g for each 1% F increase; BF = 1.42) to large inbreeding depression (-96.2 g for each 1% F increase; BF = 8.80 × 1019). The substantial variability between founder estimates suggested that inbreeding depression effects may mainly be due to a few alleles with major deleterious effects. These results contribute valuable information that should help to achieve more accurate management of inbreeding in the Ripollesa breed. [ABSTRACT FROM AUTHOR]