Maternal genetic effects throughout the life of the dam in Pirenaica beef cattle. a random regression model approach.

In beef cattle, dams play a crucial role in shaping the pre- and postnatal environment for the growth of their offspring. Acknowledging the substantial impact of maternal influence on the early development of calves, researchers utilize maternal animal models. These models take into account both maternal genetic and permanent environmental effects, operating under the assumption that these influences remain constant throughout the productive life of the cow. Nevertheless, it cannot be ruled out that these genetic and environmental effects may evolve throughout the lifespan of the cows. Therefore, this study aims to describe the changes in genetic and environmental maternal effects over the productive lifespan of cows. To accomplish this goal, we utilized random regression models, incorporating the age of the dam effect, maternal genetic effects, and environmental permanent effects using Legendre orthogonal polynomials. Additionally, the analytical model incorporated a covariate to adjust for the calf's age at recording, a two-level sex effect, a random herd-year-season effect, and an additive direct genetic effect associated linked to the calf. The dataset comprised information from dams aged between 2 and 16 years, resulting in a final database that comprised weight records of 58 332 calves from 21 673 dams. The average weight at 90 days was 135.0 ± 39.3 kg, and the mean age of the dam at calving was 7.03 ± 3.41 years. We evaluated models incorporating 2, 3, 4, 5, and 6 orthogonal polynomials alongside the standard maternal animal model. Afterward, we selected the model with five orthogonal polynomials based on the Akaike Information Criteria. The Restricted Maximum Likelihood estimates within this model indicated a direct heritability of around 0.50, and a maternal heritability ranging between 0.15 and 0.25, exhibiting a consistent increase between 4, 5 to 13 years. The genetic correlation estimates between direct and maternal genetic effects remained stable at approximately -0.55 across the lifespan of the cows. Furthermore, maternal genetic correlations between different ages of the dam decreased to around 0.7 for more distant age points. The maternal permanent correlations were notably lower, occasionally even reaching negative values, suggesting variability in environmental influence on maternal effects over the productive lifespan of the cow. Finally, the model enables the prediction of breeding values for the maternal genetic effects of the cow across its lifespan, providing opportunities for innovative selection strategies on the maternal side.

Invited review: Recursive models in animal breeding: Interpretation, limitations, and extensions.

Structural equation models allow causal effects between 2 or more variables to be considered and can postulate unidirectional (recursive models; RM) or bidirectional (simultaneous models) causality between variables. This review evaluated the properties of RM in animal breeding and how to interpret the genetic parameters and the corresponding estimated breeding values. In many cases, RM and mixed multitrait models (MTM) are statistically equivalent, although subject to the assumption of variance-covariance matrices and restrictions imposed for achieving model identification. Inference under RM requires imposing some restrictions on the (co)variance matrix or on the location parameters. The estimates of the variance components and the breeding values can be transformed from RM to MTM, although the biological interpretation differs. In the MTM, the breeding values predict the full influence of the additive genetic effects on the traits and should be used for breeding purposes. In contrast, the RM breeding values express the additive genetic effect while holding the causal traits constant. The differences between the additive genetic effect in RM and MTM can be used to identify the genomic regions that affect the additive genetic variation of traits directly or causally mediated for another trait or traits. Furthermore, we presented some extensions of the RM that are useful for modeling quantitative traits with alternative assumptions. The equivalence of RM and MTM can be used to infer causal effects on sequentially expressed traits by manipulating the residual (co)variance matrix under the MTM. Further, RM can be implemented to analyze causality between traits that might differ among subgroups or within the parametric space of the independent traits. In addition, RM can be expanded to create models that introduce some degree of regularization in the recursive structure that aims to estimate a large number of recursive parameters. Finally, RM can be used in some cases for operational reasons, although there is no causality between traits.

Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed.

Genomic selection has been implemented over the years in several livestock species, due to the achievable higher genetic progress. The use of genomic information in evaluations provides better prediction accuracy than do pedigree-based evaluations, and the makeup of the genotyped population is a decisive point. The aim of this work is to compare the effect of different genotyping strategies (number and type of animals) on the prediction accuracy for dairy sheep Latxa breeds. A simulation study was designed based on the real data structure of each population, and the phenotypic and genotypic data obtained were used in genetic (BLUP) and genomic (single-step genomic BLUP) evaluations of different genotyping strategies. The genotyping of males was beneficial when they were genetically connected individuals and if they had daughters with phenotypic records. Genotyping females with their own lactation records increased prediction accuracy, and the connection level has less relevance. The differences in genotyping females were independent of their estimated breeding value. The combined genotyping of males and females provided intermediate accuracy results regardless of the female selection strategy. Therefore, assuming that genotyping rams is interesting, the incorporation of genotyped females would be beneficial and worthwhile. The benefits of genotyping individuals from various generations were highlighted, although it was also possible to gain prediction accuracy when historic individuals were not considered. Greater genotyped population sizes resulted in more accuracy, even if the increase seems to reach a plateau.

Genetic correlations between fertility traits and milk composition and fatty acids in Holstein-Friesian, Brown Swiss, and Simmental cattle using recursive models.

This study aimed to investigate the genetic and putative causal relationships between fertility traits [i.e., days open (DO) and calving rate (CR)] and milk quality, composition, and fatty acid contents (milk composition traits) in Holstein-Friesian, Brown Swiss, and Simmental cattle, using recursive models within a Bayesian framework. Trivariate animal models were run, each including one fertility trait, one milk composition trait, and, in all models, milk yield. The DO and CR data were merged with the test days closest to the insemination date for milk composition traits. After editing, 16,468 to 23,424 records for Holstein-Friesian, 23,424 to 46,660 for Brown Swiss, and 26,105 to 35,574 for Simmental were available for the analyses. Recursive animal models were applied to investigate the possible causal influences of milk composition traits on fertility and the genetic relationships among these traits. The results suggested a potential cause-and-effect relationship between milk composition traits and fertility traits, with the first trait influencing the latter. We also found greater recursive effects of milk composition traits on DO than on CR, the latter with some putative differences among breeds in terms of sensitivity. For instance, the putative causal effects of somatic cell score on CR (on the observed scale, %) varied from -0.96 to -1.39%, depending on the breed. Concerning fatty acids, we found relevant putative effects of C18:0 on CR, with estimates varying from -7.8 to -9.9%. Protein and casein percentages, and short-chain fatty acid showed larger recursive effects on CR, whereas fat, protein, and casein percentages, C16:0, C18:0, and long-chain fatty acid had larger effects on DO. The results obtained suggested that these milk traits could be considered as effective indicators of the effects of animal metabolic and physiological status on fertility.

Genetic parameters for fertility traits assessed in herds divergent in milk energy output in Holstein-Friesian, Brown Swiss, and Simmental cattle.

In this study, we aimed to investigate differences in the genetics of fertility traits (heritability of traits and correlations between traits in divergent environments) in dairy cows of different production levels defined on the basis of the herd-average daily milk energy output (herd-dMEO). Data were obtained from Holstein-Friesian (n = 37,359 for fertility traits, 381,334 for dMEO), Brown Swiss (n = 79,638 for fertility traits, 665,697 for dMEO), and Simmental cows (n = 63,048 for fertility traits, 448,445 for dMEO) reared in northeastern Italy. Fertility traits under study were interval from calving to first service, interval from first service to conception, days open, calving interval, calving rate, and nonreturn rate at d 56. We classified herds into low and high productivity based on the herd-average dMEO (inferred using mixed effects models). We estimated genetic parameters using Bayesian bivariate animal models, where expressions of a phenotype in the low and high dMEO herds were taken as being different-albeit correlated-traits. Fertility traits were more favorable in Simmental than in Holstein-Friesian cows, whereas for all traits, Holstein-Friesian had the highest estimates of intraherd heritability [ranging from 0.021 (0.006-0.038) to 0.126 (0.10-0.15)] and Simmental the lowest [ranging from 0.008 (0.001-0.017) to 0.101 (0.08-0.12)]. The genetic correlations between fertility traits and dMEO were moderate and unfavorable, ranging, in absolute values, from 0.527 (0.37-0.68) to 0.619 (0.50-0.73) in Holstein-Friesian; from 0.339 (0.20-0.47) to 0.556 (0.45-0.66) in Brown Swiss; and from 0.340 (0.10-0.60) to 0.475 (0.33-0.61) in Simmental cattle. The only exception was the nonreturn rate at d 56, which had weak genetic correlations with dMEO in all 3 breeds. The herd correlations between fertility and dMEO tended to be modest and favorable and the residual correlations modest and variable. The heritability of fertility traits tended to be greater in the low dMEO than in the high dMEO herds in the case of the Holstein-Friesians, but not in the case of the Brown Swiss or Simmentals. The additive genetic correlations between fertility traits in the low and high dMEO herds were always lower than 1 [0.329 (-0.17 to 0.85) to 0.934 (0.86 to 0.99)] for all traits considered in all breeds. The correlation was particularly low for the threshold characters and the interval from first service to conception in Holstein-Friesian, suggesting that the relative performances of genotypes vary significantly between herds of different dMEO levels. Although there was large variability in the estimates, results might support making separate genetic evaluations of fertility in the different herd production groups. Our results also indicate that Simmental, a dual-purpose breed, has higher fertility and lower environmental sensitivity than Holstein-Friesian, with Brown Swiss being intermediate.

The effect of divergent selection for intramuscular fat on the domestic rabbit genome.

An experiment of divergent selection for intramuscular fat was carried out at Universitat Politècnica de València. The high response of selection in intramuscular fat content, after nine generations of selection, and a multidimensional scaling analysis showed a high degree of genomic differentiation between the two divergent populations. Therefore, local genomic differences could link genomic regions, encompassing selective sweeps, to the trait used as selection criterion. In this sense, the aim of this study was to identify genomic regions related to intramuscular fat through three methods for detection of selection signatures and to generate a list of candidate genes. The methods implemented in this study were Wright's fixation index, cross population composite likelihood ratio and cross population - extended haplotype homozygosity. Genomic data came from the 9th generation of the two populations divergently selected, 237 from Low line and 240 from High line. A high single nucleotide polymorphism (SNP) density array, Affymetrix Axiom OrcunSNP Array (around 200k SNPs), was used for genotyping samples. Several genomic regions distributed along rabbit chromosomes (OCU) were identified as signatures of selection (SNPs having a value above cut-off of 1%) within each method. In contrast, 8 genomic regions, harbouring 80 SNPs (OCU1, OCU3, OCU6, OCU7, OCU16 and OCU17), were identified by at least 2 methods and none by the 3 methods. In general, our results suggest that intramuscular fat selection influenced multiple genomic regions which can be a consequence of either only selection effect or the combined effect of selection and genetic drift. In addition, 73 genes were retrieved from the 8 selection signatures. After functional and enrichment analyses, the main genes into the selection signatures linked to energy, fatty acids, carbohydrates and lipid metabolic processes were ACER2, PLIN2, DENND4C, RPS6, RRAGA (OCU1), ST8SIA6, VIM (OCU16), RORA, GANC and PLA2G4B (OCU17). This genomic scan is the first study using rabbits from a divergent selection experiment. Our results pointed out a large polygenic component of the intramuscular fat content. Besides, promising positional candidate genes would be analysed in further studies in order to bear out their contributions to this trait and their feasible implications for rabbit breeding programmes.

Genetic parameters and direct, maternal and heterosis effects on litter size in a diallel cross among three commercial varieties of Iberian pig.

The Iberian pig is one of the pig breeds that has the highest meat quality. Traditionally, producers have bred one of the available varieties, exclusively, and have not used crosses between them, which has contrasted sharply with other populations of commercial pigs for which crossbreeding has been a standard procedure. The objective of this study was to perform an experiment under full diallel design among three contemporary commercial varieties of Iberian pig and estimate the additive genetic variation and the crossbreeding effects (direct, maternal and heterosis) for prolificacy. The data set comprised 18 193 records for total number born and number born alive from 3800 sows of three varieties of the Iberian breed (Retinto, Torbiscal and Entrepelado) and their reciprocal crosses (Retinto × Torbiscal, Torbiscal × Retinto, Retinto × Entrepelado, Entrepelado × Retinto, Torbiscal × Entrepelado and Entrepelado × Torbiscal), and a pedigree of 4609 individuals. The analysis was based on a multiple population repeatability model, and we developed a model comparison test that indicated the presence of direct line, maternal and heterosis effects. The results indicated the superiorities of the direct line effect of the Retinto and the maternal effect of the Entrepelado populations. All of the potential crosses produced significant heterosis, and additive genetic variation was higher in the Entrepelado than it was in the other two populations. The recommended cross for the highest yield in prolificacy is a Retinto father and an Entrepelado mother to generate a hybrid commercial sow.

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.

Evaluation of the potential use of a meta-population for genomic selection in autochthonous beef cattle populations.

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.

Genomic differentiation between Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta and Rubia Gallega cattle breeds.

The Spanish local beef cattle breeds have most likely common origin followed by a process of differentiation. This particular historical evolution has most probably left detectable signatures in the genome. The objective of this study was to identify genomic regions associated with differentiation processes in seven Spanish autochthonous populations (Asturiana de los Valles (AV), Avileña-Negra Ibérica (ANI), Bruna dels Pirineus (BP), Morucha (Mo), Pirenaica (Pi), Retinta (Re) and Rubia Gallega (RG)). The BovineHD 777K BeadChip was used on 342 individuals (AV, n=50; ANI, n=48; BP, n=50; Mo, n=50; Pi, n=48; Re, n=48; RG, n=48) chosen to be as unrelated as possible. We calculated the fixation index (F ST ) and performed a Bayesian analysis named SelEstim. The output of both procedures was very similar, although the Bayesian analysis provided a richer inference and allowed us to calculate significance thresholds by generating a pseudo-observed data set from the estimated posterior distributions. We identified a very large number of genomic regions, but when a very restrictive significance threshold was applied these regions were reduced to only 10. Among them, four regions can be highlighted because they comprised a large number of single nucleotide polymorphisms and showed extremely high signals (Kullback-Leiber divergence (KLD)>6). They are located in BTA 2 (5 575 950 to 10 152 228 base pairs (bp)), BTA 5 (17 596 734 to 18 850 702 bp), BTA 6 (37 853 912 to 39 441 548 bp) and BTA 18 (13 345 515 to 15 243 838 bp) and harbor, among others, the MSTN (Myostatin), KIT-LG (KIT Ligand), LAP3 (leucine aminopeptidase 3), NAPCG (non-SMC condensing I complex, subunit G), LCORL (ligand dependent nuclear receptor corepressor-like) and MC1R (Melanocortin 1 receptor) genes. Knowledge on these genomic regions allows to identify potential targets of recent selection and helps to define potential candidate genes associated with traits of interest, such as coat color, muscle development, fertility, growth, carcass and immunological response.

Performance of genomic selection under a single-step approach in autochthonous Spanish beef cattle populations.

This study evaluated different strategies for implementing a single-step genomic selection programme in two autochthonous Spanish beef cattle populations (Pirenaica-Pi and Rubia Gallega-RG). The strategies were compared in terms of accuracy attained under different scenarios by simulating genomic data over the known genealogy. Several genotyping approaches were tested, as well as, other factors like marker density, effective population size, mutation rate and heritability of the trait. The results obtained showed gains in accuracy with respect to pedigree BLUP evaluation in all cases. The greatest benefit was obtained when the candidates to selection had their genotypes included in the evaluation. Moreover, genotyping the individuals with the most accurate predictions maximized the gains but other suboptimal strategies also yielded satisfactory results. Furthermore, the gains in accuracy increased with the marker density reaching a plateau at around 50,000 markers. Likewise, the effective population size and the mutation rate have also shown an effect, both increasing the accuracy with decreasing values of these population parameters. Finally, the results obtained for the RG population showed greater gains compared to the Pi population, probably attributed to the wider implantation of artificial insemination.

Bayesian analysis of parent-specific transmission ratio distortion in seven Spanish beef cattle breeds.

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.

Linkage disequilibrium, persistence of phase, and effective population size in Spanish local beef cattle breeds assessed through a high-density single nucleotide polymorphism chip.

Linkage disequilibrium (LD) and persistence of phase are fundamental approaches for exploring the genetic basis of economically important traits in cattle, including the identification of QTL for genomic selection and the estimation of effective population size () to determine the size of the training populations. In this study, we have used the Illumina BovineHD chip in 168 trios of 7 Spanish beef cattle breeds to obtain an overview of the magnitude of LD and the persistence of LD phase through the physical distance between markers. Also, we estimated the time of divergence based on the persistence of the LD phase and calculated past from LD estimates using different alternatives to define the recombination rate. Estimates of average (as a measure of LD) for adjacent markers were close to 0.52 in the 7 breeds and decreased with the distance between markers, although in long distances, some LD still remained (0.07 and 0.05 for markers 200 kb and 1 Mb apart, respectively). A panel with a lower boundary of 38,000 SNP would be necessary to launch a successful within-breed genomic selection program. Persistence of phase, measured as the pairwise correlations between estimates of in 2 breeds at short distances (10 kb), was in the 0.89 to 0.94 range and decreased from 0.33 to 0.52 to a range of 0.01 to 0.08 when marker distance increased from 200 kb to 1 Mb, respectively. The magnitude of the persistence of phase between the Spanish beef breeds was similar to those found in dairy breeds. For across-breed genomic selection, the size of the SNP panels must be in the range of 50,000 to 83,000 SNP. Estimates of past showed values ranging from 26 to 31 for 1 generation ago in all breeds. The divergence among breeds occurred between 129 and 207 generations ago. The results of this study are relevant for the future implementation of within- and across-breed genomic selection programs in the Spanish beef cattle populations. Our results suggest that a reduced subset of the SNP panel would be enough to achieve an adequate precision of the genomic predictions.

Genetic diversity and divergence among Spanish beef cattle breeds assessed by a bovine high-density SNP chip.

The availability of SNP chips for massive genotyping has proven to be useful to genetically characterize populations of domestic cattle and to assess their degree of divergence. In this study, the Illumina BovineHD BeadChip genotyping array was used to describe the genetic variability and divergence among 7 important autochthonous Spanish beef cattle breeds. The within-breed genetic diversity, measured as the marker expected heterozygosity, was around 0.30, similar to other European cattle breeds. The analysis of molecular variance revealed that 94.22% of the total variance was explained by differences within individuals whereas only 4.46% was the result of differences among populations. The degree of genetic differentiation was small to moderate as the pairwise fixation index of genetic differentiation among breeds (F) estimates ranged from 0.026 to 0.068 and the Nei's D genetic distances ranged from 0.009 to 0.016. A neighbor joining (N-J) phylogenetic tree showed 2 main groups of breeds: Pirenaica, Bruna dels Pirineus, and Rubia Gallega on the one hand and Avileña-Negra Ibérica, Morucha, and Retinta on the other. In turn, Asturiana de los Valles occupied an independent and intermediate position. A principal component analysis (PCA) applied to a distance matrix based on marker identity by state, in which the first 2 axes explained up to 17.3% of the variance, showed a grouping of animals that was similar to the one observed in the N-J tree. Finally, a cluster analysis for ancestries allowed assigning all the individuals to the breed they belong to, although it revealed some degree of admixture among breeds. Our results indicate large within-breed diversity and a low degree of divergence among the autochthonous Spanish beef cattle breeds studied. Both N-J and PCA groupings fit quite well to the ancestral trunks from which the Spanish beef cattle breeds were supposed to derive.

Bayesian GWAS and network analysis revealed new candidate genes for number of teats in pigs.

The genetic improvement of reproductive traits such as the number of teats is essential to the success of the pig industry. As opposite to most SNP association studies that consider continuous phenotypes under Gaussian assumptions, this trait is characterized as a discrete variable, which could potentially follow other distributions, such as the Poisson. Therefore, in order to access the complexity of a counting random regression considering all SNPs simultaneously as covariate under a GWAS modeling, the Bayesian inference tools become necessary. Currently, another point that deserves to be highlighted in GWAS is the genetic dissection of complex phenotypes through candidate genes network derived from significant SNPs. We present a full Bayesian treatment of SNP association analysis for number of teats assuming alternatively Gaussian and Poisson distributions for this trait. Under this framework, significant SNP effects were identified by hypothesis tests using 95% highest posterior density intervals. These SNPs were used to construct associated candidate genes network aiming to explain the genetic mechanism behind this reproductive trait. The Bayesian model comparisons based on deviance posterior distribution indicated the superiority of Gaussian model. In general, our results suggest the presence of 19 significant SNPs, which mapped 13 genes. Besides, we predicted gene interactions through networks that are consistent with the mammals known breast biology (e.g., development of prolactin receptor signaling, and cell proliferation), captured known regulation binding sites, and provided candidate genes for that trait (e.g., TINAGL1 and ICK).

Monitoring changes in the demographic and genealogical structure of the main Spanish local beef breeds.

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.

DECR1 and ME1 genotypes are associated with lipid composition traits in Duroc pigs.

Variation at the porcine DECR1 and ME1 genes has been associated with meat quality traits and backfat thickness in Landrace pigs, respectively. However, it has not been investigated yet whether DECR1 and ME1 genotypes influence lipid composition. With this aim, we have genotyped two missense DECR1 substitutions (c.160G>C and c.437G>C) and one silent ME1 (c.576C>T) polymorphism in 361 Duroc barrows distributed in five half-sib families and phenotyped for serum lipid concentrations and intramuscular fat content and composition traits. At the whole-population level, relevant associations, that is, with a posterior probability of the allele substitution effect to be over or below zero (PPN0) > 0.90, were observed between DECR1 genotype and serum cholesterol (CHOL) (PPN0 = 0.932) and LDL concentrations (PPN0 = 0.945) at 190 days, as well as between ME1 genotype and longissimus dorsi saturated fatty acid content (PPN0 = 0.924). At the within-family level, we found relevant associations between DECR1 and ME1 genotypes and diverse lipid composition traits, but most of them were family-specific. Discrepancies in allele substitution effects estimated in half-sib families might be produced by many factors such as number of individuals, marker allele frequencies and informativeness in each family, unaccounted random genetic and environmental effects, epistasis and family-specific differences in the linkage phase or amount of linkage disequilibrium between causal and marker mutations. This lack of consistency across families, combined with the fact that the ME1 mutation is synonymous and that the two DECR1 polymorphisms are conservative, suggests that the associations found are not causative.

Crossbreeding effects on pig growth and carcass traits from two Iberian strains.

An experiment of a 2×2 full diallelic cross between two contemporary Iberian pig strains (Retinto: RR, and Torbiscal: TT) was conducted to estimate the crossbreeding effects for growth and carcass traits. Phenotypic records were obtained under intensive management and consisted of two different data sets. The first set comprised growth traits until weaning and was collected at two different farms (6236 and 1208 records, respectively). Specific data included individual piglet weight at birth and at weaning at 28 days and average daily gain from birth to weaning at 28 days (ADG28) for both RR and TT and their reciprocal crosses. The second set comprised growth data from birth to slaughter (~340 days and ~160 kg) and carcass traits from 349 individuals (randomly) sampled at weaning from the first dataset. Data were analyzed through a Bayesian analysis by using a reparameterization of Dickerson's model that allowed estimation of the posterior distributions of the following crossbreeding effects: average maternal breed effect (gM), average paternal breed effect (gP) and individual heterosis (hI). Results showed that the relative magnitude of crossbreeding effects depends on the trait analyzed. Crosses where Torbiscal strain was used as mother (RT and TT) achieved the greatest performance for all growth traits at weaning, leading to remarkable gM effects. The most outstanding example is the case of ADG28 where the probability of relevance was one. In contrast, TR cross showed the greatest differences from RR cross for all growth at slaughter and carcass traits. These differences were mainly due to hI and gP crossbreeding parameters. In particular, the posterior mean of hI was more noticeable for live weight at slaughter, average daily gain at slaughter and carcass length, while gP was more relevant for hams (kg) and loins (kg) representing from 3% to10% of average performance of traits. Hence, growth traits at weaning did not reveal any notable advantage of the crossbreeding scheme because of the superiority of the Torbiscal strain with respect to its mothering ability and the small hI. However, results from growth and carcass traits at slaughter would support the implementation of a TR crossbred system. It would allow exploitation of both the gP of the Torbiscal strain and the hI between these two Iberian pig strains. Additionally, gP estimates and phenotypic differences between reciprocal crosses might suggest signs of the presence of paternal genetic imprinting in primal cuts traits.

Non-linear recursive models for growth traits in the Pirenaica beef cattle breed.

One of the main goals of selection schemes in beef cattle populations is to increase carcass weight at slaughter. Live weights at different growth stages are frequently used as selection criteria under the hypothesis that they usually have a high and positive genetic correlation with weight at slaughter. However, the presence of compensatory growth may bias the prediction ability of early weights for selection purposes. Recursive models may represent an interesting alternative for understanding the genetic and phenotypic relationship between weight traits during growth. For the purposes of this study, the analysis was performed for three different set of data from the Pirenaica beef cattle breed: weight at 120 days (W120) and at 210 days (W210); W120 and carcass weight at slaughter at 365 days (CW365); W210 and CW365. The number of records for each analysis was 8592, 4648 and 3234, respectively. A pedigree composed of 56323 individuals was also included. The statistical model comprised sex, year-season of birth, herd and slaughterhouse, plus a non-linear recursive dependency between traits. The dependency was modeled as a polynomial up to the 4th degree and models were compared using a Logarithm of Conditional Predictive Ordinates. The results of model comparison suggest that the best models were the 3rd degree polynomial for W120-W210 and W120-CW365 and the 2nd degree polynomial for W210-CW365. The posterior mean estimates for heritabilities ranged between 0.29 and 0.44 and the posterior mean estimates of the genetic correlations were null or very low, indicating that the relationship between traits is fully captured by the recursive dependency. The results imply that the predictive ability of the performance of future growth is low if it is only based on records of early weights. The usefulness of slaughterhouse records in beef cattle breeding evaluation is confirmed.