RESUMO
Considering the economic and commercial efficiency of the beef production chain, the yield and quality of the meat produced must also be included in breeding programs. For the Nellore breed, including the polled herd, these aspects have not been much studied. The aim of this study was to estimate genetic parameters for scrotal circumference adjusted to 365 (SC365) and 450 (SC450) days of age, age at first calving (AFC), accumulated productivity (AP), stayability (STAY), longissimus muscle area (LMA), thickness of subcutaneous fat over the 12th-13th ribs (BF), thickness of subcutaneous fat over the rump (RF), and shear force measured by Warner-Bratzler shear force (WBSF) of polled Nellore cattle. Bayesian analyses were performed by adopting a linear animal model, whereas STAY analyses used the linear threshold model. Heritability estimates were 0.31 (SC365), 0.37 (SC450), 0.16 (AFC), 0.25 (AP), 0.16 (STAY), 0.30 (LMA), 0.13 (BF), 0.24 (RF), and 0.15 (WBSF), indicating moderate response to selection. Genetic and residual correlations between SC365 and SC450 were high (0.91 and 0.74, respectively), as well as the genetic correlations of AP with SC365, SC450, AFC, and STAY (0.61, 0.62, - 0.69, and 0.83, respectively). Genetic and residual correlations of WBSF with reproductive and carcass characteristics exhibited high standard deviations, however favorable. Based on the results, it is expected that in the medium term, animals with greater sexual precocity will also have greater accumulated productivity and longer permanence of females in the herd, along with superior carcass traits. However, due to the low heritabilities and small genetic associations with reproductive traits, fat thickness characteristics (BF and RF) will still require direct selection.
Assuntos
Carne , Reprodução , Animais , Bovinos/genética , Feminino , Teorema de Bayes , Fenótipo , Reprodução/genéticaRESUMO
Several methods have been used for genome-enabled prediction (or genomic selection) of complex traits, for example, multiple regression models describing a target trait with a linear function of a set of genetic markers. Genomic selection studies have been focused mostly on single-trait analyses. However, most profitability traits are genetically correlated, and an increase in prediction accuracy of genomic breeding values for genetically correlated traits is expected when using multiple-trait models. Thus, this study was carried out to assess the accuracy of genomic prediction for carcass and meat quality traits in Nelore cattle, using single- and multiple-trait approaches. The study considered 15 780, 15 784, 15 742 and 526 records of rib eye area (REA, cm2), back fat thickness (BF, mm), rump fat (RF, mm) and Warner-Bratzler shear force (WBSF, kg), respectively, in Nelore cattle, from the Nelore Brazil Breeding Program. Animals were genotyped with a low-density single nucleotide polymorphism (SNP) panel and subsequently imputed to arrays with 54 and 777â¯k SNPs. Four Bayesian specifications of genomic regression models, namely, Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression; blending methods, BLUP; and single-step genomic best linear unbiased prediction (ssGBLUP) methods were compared in terms of prediction accuracy using a fivefold cross-validation. Estimates of heritability ranged from 0.20 to 0.35 and from 0.21 to 0.46 for RF and WBSF on single- and multiple-trait analyses, respectively. Prediction accuracies for REA, BF, RF and WBSF were all similar using the different specifications of regression models. In addition, this study has shown the impact of genomic information upon genetic evaluations in beef cattle using the multiple-trait model, which was also advantageous compared to the single-trait model because it accounted for the selection process using multiple traits at the same time. The advantage of multi-trait analyses is attributed to the consideration of correlations and genetic influences between the traits, in addition to the non-random association of alleles.
Assuntos
Genoma , Genômica , Animais , Teorema de Bayes , Brasil , Bovinos/genética , Genótipo , Carne/análise , Modelos Genéticos , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
This study was carried out to investigate (co)variance components and genetic parameters for growth traits in beef cattle using a multi-trait model by Bayesian methods. Genetic and residual (co)variances and parameters were estimated for weights at standard ages of 120 (W120), 210 (W210), 365 (W365), and 450 days (W450), and for pre- and post-weaning daily weight gain (preWWG and postWWG) in Nellore cattle. Data were collected over 16 years (1993-2009), and all animals were raised on pasture in eight farms in the North of Brazil that participate in the National Association of Breeders and Researchers. Analyses were run by the Bayesian approach using Gibbs sampler. Additive direct heritabilities for W120, W210, W365, and W450 and for preWWG and postWWG were 0.28 ± 0.013, 0.32 ± 0.002, 0.31 ± 0.002, 0.50 ± 0.026, 0.61 ± 0.047, and 0.79 ± 0.055, respectively. The estimates of maternal heritability were 0.32 ± 0.012, 0.29 ± 0.004, 0.30 ± 0.005, 0.25 ± 0.015, 0.23 ± 0.017, and 0.22 ± 0.016, respectively, for W120, W210, W365, and W450 and for preWWG and postWWG. The estimates of genetic direct additive correlation among all traits were positive and ranged from 0.25 ± 0.03 (preWWG and postWWG) to 0.99 ± 0.00 (W210 and preWWG). The moderate to high estimates of heritability and genetic correlation for weights and daily weight gains at different ages is suggestive of genetic improvement in these traits by selection at an appropriate age. Maternal genetic effects seemed to be significant across the traits. When the focus is on direct and maternal effects, W210 seems to be a good criterium for the selection of Nellore cattle considering the importance of this breed as a major breed of beef cattle not only in Northern Brazil but all regions covered by tropical pastures. As in this study the genetic correlations among all traits were high, the selection based on weaning weight might be a good choice because at this age there are two important effects (maternal and direct genetic effects). In contrast, W120 should be preferred when the objective is improving the maternal ability of the dams. Furthermore, selection for postWWG can be used if the animals show both heavier weaning weights and high growth rate after weaning because it is possible to shorten the time between weaning and slaughter based on weaning weight, postWWG, and desired weight at the time of slaughter.
Assuntos
Peso Corporal/genética , Bovinos/genética , Característica Quantitativa Herdável , Seleção Artificial , Animais , Teorema de Bayes , Bovinos/crescimento & desenvolvimento , Feminino , Masculino , Herança MaternaRESUMO
Brazil is one of the world's largest beef exporters, although the product has a low price due to quality issues. The meat exported by Brazil is considered medium and low quality by international buyers, mainly due to lack of tenderness. The predominant Zebu breeds (80% Nellore) are known for producing tougher beef than taurine breeds. Nonetheless, some studies have shown that there is substantial genetic variability for tenderness within the Nellore breed, although it is a difficult trait to improve by conventional selection methods. Therefore, the aim of this study was to perform a genomewide association study (GWAS) and a gene set enrichment analysis to identify genomic regions and biologically relevant pathways associated with meat tenderness in Polled Nellore cattle. Data consisted of Warner-Bratzler shear force values of LM from 427 Polled Nellore animals divided into 3 experimental slaughters (years 2005, 2008, and 2010). The animals were genotyped with either the Illumina BovineHD BeadChip (777k, on 61 samples) or the GGP Indicus HD chip (77k, on 366 samples). Single nucleotide polymorphisms were excluded when the call rate was <90%, the Hardy-Weinberg proportions -value was <1% (Fisher exact test, Bonferroni adjusted), and the minor allele frequency was <1%. Imputation from the GGP Indicus HD chip to the Illumina BovineHD BeadChip was performed using the FImput program. Genomewide association analysis was performed using the Efficient Mixed Model Association eXpedited (EMMAx) and the population parameters previously determined (P3D) methods. The GWAS was complemented with a gene set enrichment analysis performed using the FatiGO procedure. Significant markers ( < 0.0001) explaining a larger proportion of variation than other significant SNPs were located on chromosomes 3, 13, 17, 20, 21, and 25, indicating QTL associated with meat tenderness throughout the genome. Additionally, gene set analysis identified 22 Gene Ontology functional terms and 2 InterPro entries that showed significant enrichment of genes associated with tenderness. The functional categories included protein tyrosine and serine/threonine kinase activity, calcium ion binding, lipid metabolic process, and growth factors, among others. These results help to elucidate the genetic architecture and metabolic pathways underlying this trait, which is of extreme economic and social importance to Brazil, because Nellore is the dominant beef cattle breed in the country.
Assuntos
Bovinos/genética , Estudo de Associação Genômica Ampla , Genoma/genética , Polimorfismo de Nucleotídeo Único , Carne Vermelha/normas , Animais , Brasil , Cruzamento , Bovinos/fisiologia , Mapeamento Cromossômico/veterinária , Feminino , Frequência do Gene , Ontologia Genética , Genômica , Genótipo , Masculino , Análise de Sequência com Séries de Oligonucleotídeos/veterinária , FenótipoRESUMO
The aim of the present study was to evaluate the prediction ability of models that cope with longevity phenotypic expression as uncensored and censored in Nellore cattle. Longevity was defined as the difference between the dates of last weaned calf and cow birth. There were information of 77 353 females, being 61 097 cows with uncensored phenotypic information and 16 256 cows with censored records. These data were analyzed considering three different models: (1) Gaussian linear model (LM), in which only uncensored records were considered; and two models that consider both uncensored and censored records: (2) Censored Gaussian linear model (CLM); and (3) Weibull frailty hazard model (WM). For the model prediction ability comparisons, the data set was randomly divided into training and validation sets, containing 80% and 20% of the records, respectively. There were considered 10 repetitions applying the following restrictions: (a) at least three animals per contemporary group in the training set; and (b) sires with more than 10 progenies with uncensored records (352 sires) should have daughters in the training and validation sets. The variance components estimated using the whole data set in each model were used as true values in the prediction of breeding values of the animals in the training set. The WM model showed the best prediction ability, providing the lowest χ 2 average and the highest number of sets in which a model had the smallest value of χ 2 statistics. The CLM and LM models showed prediction abilities 2.6% and 3.7% less efficient than WM, respectively. In addition, the accuracies of sire breeding values for LM and CLM were lower than those obtained for WM. The percentages of bulls in common, considering only 10% of sires with the highest breeding values, were around 75% and 54%, respectively, between LM-CLM and LM-WM models, considering all sires, and 75% between LM-CLM and LM-WM, when only sires with more than 10 progenies with uncensored records were taken into account. These results are indicative of reranking of animals in terms of genetic merit between LM, CLM and WM. The model in which censored records of longevity were excluded from the analysis showed the lowest prediction ability. The WM provides the best predictive performance, therefore this model would be recommended to perform genetic evaluation of longevity in this population.
Assuntos
Bovinos/fisiologia , Longevidade/genética , Longevidade/fisiologia , Animais , Cruzamento , Feminino , Modelos Lineares , Modelos Biológicos , Parto , Gravidez , Modelos de Riscos Proporcionais , Reprodução , DesmameRESUMO
Zebu () cattle, mostly of the Nellore breed, comprise more than 80% of the beef cattle in Brazil, given their tolerance of the tropical climate and high resistance to ectoparasites. Despite their advantages for production in tropical environments, zebu cattle tend to produce tougher meat than Bos taurus breeds. Traditional genetic selection to improve meat tenderness is constrained by the difficulty and cost of phenotypic evaluation for meat quality. Therefore, genomic selection may be the best strategy to improve meat quality traits. This study was performed to compare the accuracies of different Bayesian regression models in predicting molecular breeding values for meat tenderness in Polled Nellore cattle. The data set was composed of Warner-Bratzler shear force (WBSF) of longissimus muscle from 205, 141, and 81 animals slaughtered in 2005, 2010, and 2012, respectively, which were selected and mated so as to create extreme segregation for WBSF. The animals were genotyped with either the Illumina BovineHD (HD; 777,000 from 90 samples) chip or the GeneSeek Genomic Profiler (GGP Indicus HD; 77,000 from 337 samples). The quality controls of SNP were Hard-Weinberg Proportion -value ≥ 0.1%, minor allele frequency > 1%, and call rate > 90%. The FImpute program was used for imputation from the GGP Indicus HD chip to the HD chip. The effect of each SNP was estimated using ridge regression, least absolute shrinkage and selection operator (LASSO), Bayes A, Bayes B, and Bayes Cπ methods. Different numbers of SNP were used, with 1, 2, 3, 4, 5, 7, 10, 20, 40, 60, 80, or 100% of the markers preselected based on their significance test (-value from genomewide association studies [GWAS]) or randomly sampled. The prediction accuracy was assessed by the correlation between genomic breeding value and the observed WBSF phenotype, using a leave-one-out cross-validation methodology. The prediction accuracies using all markers were all very similar for all models, ranging from 0.22 (Bayes Cπ) to 0.25 (Bayes B). When preselecting SNP based on GWAS results, the highest correlation (0.27) between WBSF and the genomic breeding value was achieved using the Bayesian LASSO model with 15,030 (3%) markers. Although this study used relatively few animals, the design of the segregating population ensured wide genetic variability for meat tenderness, which was important to achieve acceptable accuracy of genomic prediction. Although all models showed similar levels of prediction accuracy, some small advantages were observed with the Bayes B approach when higher numbers of markers were preselected based on their -values resulting from a GWAS analysis.
Assuntos
Cruzamento , Genoma , Genômica/métodos , Carne/normas , Animais , Teorema de Bayes , Brasil , Bovinos/genética , Frequência do Gene , Estudo de Associação Genômica Ampla , Genótipo , Carne/análise , Análise de Sequência com Séries de Oligonucleotídeos/veterinária , Polimorfismo de Nucleotídeo ÚnicoRESUMO
The continuous trait age at subsequent rebreeding (ASR) was evaluated using survival analysis in Nellore breed cows that conceived for the first time at approximately 14 months of age. This methodology was chosen because the restricted breeding season produces censored data. The dataset contained 2885 records of ASR (in days). Records of females that did not produce calves in the following year after being exposed to a sire were considered censored (48.3% of the total). The statistical model used was a Weibull mixed survival model, which included fixed effects of contemporary groups (CG) and period and a random effect of individual animal. The effect of contemporary groups on ASR was significant (P < 0.01). Heritabilities obtained for ASR were 0.03 and 0.04 in logarithmic and original scales, respectively. These results indicate that the genetic selection response for subsequent reproduction of 2-year-old Nellore breed females is not expected to be effective based on survival analysis. Furthermore, these results suggest that environmental improvement is fundamental to this important trait. It should be highlighted that an increase in the average date of birth can produce an adverse effect in the future, since this cannot be compensated by genetic improvement.
Assuntos
Cruzamento , Reprodução/genética , Seleção Genética , Análise de Sobrevida , Fatores Etários , Animais , Bovinos , Meio Ambiente , Feminino , FenótipoRESUMO
The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated.
Assuntos
Cruzamento/métodos , Bovinos/genética , Bovinos/fisiologia , Lactação/genética , Leite/metabolismo , Fatores Etários , Animais , Brasil , Feminino , Modelos GenéticosRESUMO
In most studies on beef cattle longevity, only the cows reaching a given number of calvings by a specific age are considered in the analyses. With the aim of evaluating all cows with productive life in herds, taking into consideration the different forms of management on each farm, it was proposed to measure cow longevity from age at last calving (ALC), that is, the most recent calving registered in the files. The objective was to characterize this trait in order to study the longevity of Nellore cattle, using the Kaplan-Meier estimators and the Cox model. The covariables and class effects considered in the models were age at first calving (AFC), year and season of birth of the cow and farm. The variable studied (ALC) was classified as presenting complete information (uncensored = 1) or incomplete information (censored = 0), using the criterion of the difference between the date of each cow's last calving and the date of the latest calving at each farm. If this difference was >36 months, the cow was considered to have failed. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The records of 11 791 animals from 22 farms within the Nellore Breed Genetic Improvement Program ('Nellore Brazil') were used. In the estimation process using the Kaplan-Meier model, the variable of AFC was classified into three age groups. In individual analyses, the log-rank test and the Wilcoxon test in the Kaplan-Meier model showed that all covariables and class effects had significant effects (P < 0.05) on ALC. In the analysis considering all covariables and class effects, using the Wald test in the Cox model, only the season of birth of the cow was not significant for ALC (P > 0.05). This analysis indicated that each month added to AFC diminished the risk of the cow's failure in the herd by 2%. Nonetheless, this does not imply that animals with younger AFC had less profitability. Cows with greater numbers of calvings were more precocious than those with fewer calvings.
Assuntos
Bovinos/fisiologia , Longevidade , Parto , Envelhecimento , Animais , Brasil , Feminino , Estimativa de Kaplan-Meier , Modelos Biológicos , Gravidez , Modelos de Riscos ProporcionaisRESUMO
A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.