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.

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.

A single nucleotide polymorphism in the coding region of bovine transferrin is associated with milk fat yield.

The bovine transferrin gene (TF) is located at 125 cM on bovine chromosome 1 (BTA1); it codes for transferrin, a glycoprotein that is highly conserved in many species and that is responsible for iron transport. The TF gene has been located in several QTL regions, and some transferrin classes have been associated with fat and milk yields. We analyzed by means of allele-specific oligonucleotide real-time PCR the c.1455A>G SNP in exon 12 of the TF cDNA sequence (accession number U02564), which induces an Asp/Gly substitution at position 469 of the peptide. The c.1455A>G SNP was assayed in eight Spanish cattle breeds, as well as in two groups of Holstein-Friesian animals that had the highest and lowest estimated breeding values for milk fat yield. Analysis of the cSNP showed balanced frequencies in all breeds, with a mean of 0.44. Evaluation of a potential association between the cSNP and the groups of Holstein-Friesian animals selected for milk fat yield showed a significant association (P < 0.0006); the G allele was associated with high fat production. Significant differences in genotypic frequencies between the groups were also detected (P < 0.0028). These results lead us to suggest that the TF gene has an effect on milk fat yield.

Parameter estimation in selected populations with missing data.

This study proposes a procedure to estimate genetic parameters in populations where a selection process results in the loss of an unknown number of observations. The method was developed under the Bayesian inference scope following the missing data theory approach. Its implementation requires slight modifications to the Gibbs sampler algorithm. In order to show the efficiency of this option, a simulation study was conducted.

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.

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 inference of variance components for litter size in Rasa Aragonesa sheep.

Variance components were estimated for litter size in Rasa Aragonesa sheep, a meat breed from northern Spain, to determine whether selective breeding for litter size is a reasonable strategy to improve reproductive performance. We assumed an animal mixed effect threshold model with a binary response variable. Marginal estimates of the genetic parameters were obtained in the underlying scale using Bayesian inference, implemented via the Gibbs sampling procedure and a data augmentation approach. Posterior marginal means of heritability and repeatability were .077 and .141, respectively. Moreover, the 95% highest marginal posterior density region of heritability ranged from .051 to .101. Therefore, we conclude that litter size is a trait that could be selected for in breeding programs. The effect of the loss of pedigree information, a common feature of sheep production, on the estimation of the genetic parameters was also studied using simulation. The results indicate that the lack of pedigree information has little effect on our estimates of heritability.

Computer methodology for simulation and prediction of alloimmune responses: expected antibody specificities.

The methodology presented here was developed for simulating planned alloimmunization results, with regard to the type and number of expected antibody specificities. The computer program designed for this purpose was adapted to an immunogenetic model using Boolean algebra. It was written to help immunogeneticists avoid handling routine data preceding selection of donor-recipient pairs, specially concerning blood type alloimmunizations in animals: all of the donor-recipient combinations and the expected antibody specificities (their limit number being specified in each particular immunization program) are provided in the print-out.

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.

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.

Genetic correlation of longevity with growth, post-mortem, docility and some morphological traits in the Pirenaica beef cattle breed.

Survival or longevity is an economically relevant trait in cattle. However, it is not currently included in cattle selection criteria because of the delayed recording of phenotypic data and the high computational demand of survival techniques under proportional hazard models. The identification of longevity-correlated traits that can be early registered in lifetime would therefore be very useful for beef cattle selection processes. The aim of this study was to estimate the genetic correlation of survival (SURV) with: growth - birth weight (BW), weight at 120 days (W120), weight at 210 days (W210); carcass - cold carcass weight (CCW), conformation (CON), fatness (FAT) and meat colour (COL); teat morphology - teat thickness (TT), teat length (TL) and udder depth (UD); leg morphology - forward (FL) and backward legs (BL); milk production (MILK) and docility (DOC). In the statistical analysis, SURV was measured in discrete-time intervals and modelled via a sequential threshold model. A series of independent bivariate Bayesian analyses between cow survival and each recorded trait were carried out. The posterior mean estimates (and posterior standard deviation) for the heritability of SURV was 0.05 (0.01); and for the relevant genetic correlations with SURV were 0.07 (0.04), 0.12 (0.05), 0.10 (0.05), 0.15 (0.05), -0.18 (0.06), 0.33 (0.06) and 0.27 (0.15) for BW, W120, W210, CCW, CON, FAT and COL, respectively.

The bovine annexin 9 gene (ANXA9) is significantly associated with milk-fat yield in a Spanish Holstein-Friesian population.

On the basis of QTL studies for milk-fat yield trait on BTA3, annexin 9 protein (ANXA9), fatty acid transport protein type 3 (SLC27A3) and diacylglycerol O-acyltransferase 1 (DGAT1) were selected as candidate genes. Three different single nucleotide polymorphisms (SNPs) of bovine ANXA9, SLC27A3 and DGAT1 genes have been tested in a selective genotyping design for milk-fat yield. Significant allele frequency differences were found for ANXA9 (p=0.02), in Holstein-Friesian animals with high and low breeding values for milk-fat yield. Regression analysis also showed a significant effect (p=0.0207) between estimated breeding values (EBVs) for fat milk content and ANXA9 polymorphism. So ANXA9 gene falls into a significant quantitative trait loci interval for milk-fat yield that was previously reported on bovine chromosome 3 in other dairy populations. Our results suggest that the ANXA9 gene polymorphism or a linked segregating QTL contributes to variation in milk-fat yield.

A model with heterogeneous thresholds for subjective traits: fat cover and conformation score in the Pirenaica beef cattle.

Current selection schemes for livestock improvement use a wide variety of phenotypic traits. Some of them, such as sensory, type, or carcass traits, obtain their records from subjective grading performed by trained technicians. Data from this subjective evaluation usually involve classification under a categorical and arbitrary predefined scale, whose output may lead to strong departures from the Gaussian distribution. In addition, the scale of grading may be different according to different technicians. To study this phenomenon, we have analyzed subjective conformation (CON) and fat cover (FAT) scores in the Pirenaica beef cattle breed from data provided by 12 different slaughterhouses. Three statistical models were used: 1) a Gaussian linear model; 2) an ordered category threshold model; and 3) a specific slaughterhouse ordered category threshold model. These models were analyzed through a Bayesian analysis via a Gibbs sampler with a data augmentation step. Posterior mean estimates of heritability ranged from 0.23 to 0.26 for CON, and from 0.13 to 0.16 for FAT. Statistical models were compared by the deviance information criteria, and the slaughterhouse-specific ordered category threshold model was selected as the most plausible. This result was confirmed by the fact that the threshold estimates differed noticeably between slaughterhouses. Finally, the proposed model for genetic evaluation increased the expected selection response by up to 7.6% for CON and 11.2% for FAT.

Bayesian estimates of genetic parameters for pre-conception traits, gestation length and calving interval in beef cattle.

A total of 5253 records obtained from 2081 Rubia Gallega beef cows managed using artificial insemination as the only reproduction system were analysed to estimate genetic parameters for days to first insemination (DFI), days from first insemination to conception (FIC), number of inseminations per conception (IN), days open (DO), gestation length (GL) and calving interval (CI) via multitrait Bayesian procedures. Estimates of the mean of posterior distribution of the heritability of DFI, FIC, IN, DO, GL and CI were, respectively, 0.050, 0.078, 0.071, 0.053, 0.037 and 0.085 and the corresponding estimates for repeatability of these traits were 0.116, 0.129, 0.147, 0.138, 0.082 and 0.132, respectively. No significant genetic correlations associated to DFI or GL were found. However, genetic correlations between the other four analysed traits were high and significant. Genetic correlations between FIC and IN, DO and CI were similar and higher than 0.85. Genetic correlations of IN-DO and IN-CI were over 0.65. The highest genetic correlation was estimated for the pair DO-CI (0.992) that can be considered the same trait in genetic terms. Results indicated that DFI can be highly affected by non-genetic factors thus limiting its usefulness to be used as an earlier indicator of reproductive performance in beef cattle. Moreover, GL could not be associated to the reproductive performance of the cow before conception. The other four analysed traits, FIC, IN, DO and CI, have close genetic relationships. The inclusion of IN as an earlier indicator of fertility in beef cattle improvement programs using artificial insemination as the main reproductive system can be advisable due to the low additional recording effort needed.

Association of polymorphisms in the bovine FASN gene with milk-fat content.

Fatty acid synthase (FASN) is a multifunctional protein that carries out the synthesis of fatty acids so it plays a central role in de novo lipogenesis in mammals. Previously, we defined the genetic structure and expression of the bovine FASN gene. Our mapping studies placed FASN on BTA19 (19q22) where several quantitative trait loci (QTL) affecting milk-fat content and related traits have been described. This study was conducted to identify polymorphisms in the bovine FASN gene and to study their association with milk-fat content. The bovine FASN gene was screened for polymorphisms in two cattle breeds. Sequence analysis revealed several single nucleotide polymorphisms (SNPs), and two of them were analysed: a G>C substitution in the untranslated exon 1 (g.763G>C), altering a potential Sp1 transcription factor-binding site, and an A>G substitution in exon 34 (g.16009A>G), which determines a non-conservative substitution of threonine by alanine. Allele-specific amplification of the SNPs in FASN revealed significant frequency differences for both polymorphisms in Holsteins with high and low breeding values for milk-fat content. The intragenic haplotypes comprising exon 1 (alleles G and C) and exon 34 (alleles A and G) polymorphisms were studied, and the existence of linkage disequilibrium between these SNPs was found (D(CG) = 0.048, P < 0.001). Our results suggest that the FASN gene polymorphisms contribute to variation in milk-fat content. We propose that the bovine FASN gene is a candidate gene for a milk-fat content QTL.

Repetition blindness and bilingual memory: token individuation for translation equivalents.

The repetition blindness effect (RB) occurs when individuals are unable to recall a repeated word relative to a nonrepeated word in a sentence or string of words presented in a rapid serial visual presentation task. This effect was explored across languages (English and Spanish) in an attempt to provide evidence for RB at a conceptual level using noncognate translation equivalents (e.g., nephew-sobrino). In the first experiment, RB was found when a word was repeated in an English sentence but not when the two repetitions were in different languages. In the second experiment, RB was found for identical repetitions in Spanish and in English using word lists. However, the cross-language condition produced significant facilitation in recall, suggesting that although conceptual processing had taken place, semantic overlap was not sufficient to produce RB. The results confirm Kanwisher's (1987) token individuation hypothesis in the case of translation equivalents.

Semantic codes are not used in integrating information across eye fixations in reading: evidence from fluent Spanish-English bilinguals.

The question of whether meaning can be extracted from unidentified parafoveal words was examined using fluent Spanish-English bilinguals. In Experiment 1, subjects fixated on a central cross, and a preview word was presented to the right of fixation in parafoveal vision. During the saccade to the parafoveal preview word, the preview was replaced by the target word, which the subject was required to name. In Experiment 2, subjects read sentences containing the target word, and, as in the naming task, a preview word was replaced by the target word when the subject's saccade crossed a boundary location. In both experiments, preview words were identical to the target word, translations, orthographic controls for the translations, or unrelated words in the opposite language. In both experiments, the preview benefit from the translation conditions was no greater than would be predicted by the orthographic similarity of the preview to the target. Hence, the data indicated that subjects obtained no useful semantic information from words seen parafoveally that enabled them to identify them more quickly on the subsequent fixation.