Genetic analysis of female reproductive efficiency, scrotal circumference and growth traits in Nelore cattle.

This study estimated the genetic variability and correlations between growth and reproductive traits in Nelore cattle. Annual genetic changes in female reproductive traits were also evaluated using repeated measures. Direct heritability was moderate for the growth traits and scrotal circumference (0.235 ±â€¯0.015 to 0.443 ±â€¯0.006), indicating genetic variability in these traits in the population studied. Maternal heritability was low for weaning height (0.042 ±â€¯0.012) and weaning weight (0.112 ±â€¯0.013). Regarding female reproductive traits, gestation length (GL) exhibited a slightly higher heritability (0.179 ±â€¯0.006) than days to calving (DC) and calving interval (CI) (0.123 ±â€¯0.006 and 0.105 ±â€¯0.008, respectively). Repeatability was lower for GL (0.222 ±â€¯0.006) compared to DC (0.318 ±â€¯0.004) and CI (0.406 ±â€¯0.006). Moderate and positive genetic correlations were obtained between the growth traits and scrotal circumference, ranging from 0.193 ±â€¯0.019 to 0.519 ±â€¯0.007. Weaning height showed low and positive genetic associations with GL (0.138 ±â€¯0.007) and CI (0.189 ±â€¯0.016), but was not correlated with DC (-0.016 ±â€¯0.011). Similarly, weaning weight, yearling height or yearling weight was not associated with any of the female reproductive traits. The genetic correlations between scrotal circumference and female reproductive traits were negative and favorable, but low: -0.116 ±â€¯0.020 (GL), -0.084 ±â€¯0.028 (DC), and -0.054 ±â€¯0.038 (CI). Favorable genetic associations were estimated between all female reproductive traits, ranging from 0.170 ±â€¯0.040 to 0.442 ±â€¯0.050. Genetic changes were favorable for GL and CI (-0.02 days/year and -0.11 days/year, respectively) and unfavorable for DC (0.16 days/year). In conclusion, selection for higher growth using the estimated breeding values for height and weight will not affect the reproductive performance of Nelore females. Nonetheless, simultaneous selection for growth and reproductive traits is possible.

Effect of mature size and body condition of Nelore females on the reproductive performance.

The size and body condition of cows can affect their reproductive efficiency. However, few studies reported genetic correlations between these traits in beef cattle. Thus, we estimated the genetic parameters and correlations between weight (MW), height (MH) and body condition score (BCS) of cows and reproductive traits (SC: scrotal circumference, AFC: age at first calving, GL: gestation length, DC: days to calving, and CI: calving interval) in Nelore animals. In addition, it has also obtained direct and correlated responses aiming at determining whether changes in cow size and body condition may affect the herd reproductive performance. A series of two-trait Bayesian analyzes were performed including MW, MH or BCS with each of the reproductive traits. The heritability estimated for MW, MH and BCS were 0.46 ±â€¯0.02, 0.35 ±â€¯0.01 and 0.17 ±â€¯0.02, indicating an involvement of additive gene action mainly in cows' size determination. For the reproductive traits of females, heritability ranged from 0.05 ±â€¯0.00 for CI to 0.18 ±â€¯0.01 for GL, and was 0.37 ±â€¯0.01 for SC. Low repeatability were estimates for GL (0.19 ±â€¯0.00), DC (0.19 ±â€¯0.00) and CI (0.05 ±â€¯0.00). The MW was positive correlated with AFC (0.23 ±â€¯0.08), CI (0.25 ±â€¯0.15) and, with lower magnitude, of GL (0.14 ±â€¯0.03). Null genetic correlations were obtained between MW with SC (0.03 ±â€¯0.03) and DC (-0.01 ±â€¯0.04). The MH showed positive and low genetic association with all female reproductive traits, but negative with SC (-0.08 ±â€¯0.03). Negative and favorable genetic correlations were estimated between BCS and females reproductive traits, but unfavorable with SC (-0.13 ±â€¯0.06). In summary, the negative impact of increase the size of Nelore females on their reproductive performance is expected to be small in tropical regions. The use of sires with high genetic breeding values for SC should result in slight reduction of BCS of cows, but no effective genetic response in female size is expected. Selection based on BCS should promote little improvement in reproductive efficiency of cows.

Correlation between phenotype, genotype and antral follicle population in beef heifers.

The present study was performed in indicus-taurus heifers 1) to determine if the antral follicle count (AFC) exhibits repeatability from puberty to yearling age and 2) to evaluate whether the phenotypic and genotypic parameters used in genetic improvement programs are correlated with AFC. In study I, Braford heifers (3/8 Nelore x 5/8 Hereford, n = 137) were serially examined by ultrasonography (with 60-day intervals) from weaning (9 ± 1 mo of age) to yearling ages (20 ± 1 mo of age) to monitor the numbers of antral follicles. In study II, the AFC of animals from experiment I and contemporary (same farm, considered at same age and kept under same conditions heifers n = 270 18-24 months) was correlated with the records of a genetic selection program using four statistical models with different covariates: i) model 1 considered effects of contemporary group and covariates age, weight gain from birth to weaning and visual scores for carcass traits at weaning, ii) model 2 covered contemporary group, age, weight gain from weaning to yearling and visual scores for carcass traits at yearling. The effects, variables and covariates of models 1 and 2 were combined to form model 3. Model 4 included the model 3 with addition of paternal effect. In study I, AFC varied from 3 to 64 follicles among females but was highly repeatable (0.89-0.92) within individuals in the same group. In study II, the four models tested showed low correlations with AFC: 0.072, 0.056, 0.082 and 0.172 for models 1, 2, 3 and 4, respectively. However, the model with paternal effect provided 17% of correlation of AFC and genotypic and phenotypic characteristics. Models 1, 3 and 4 also showed that AFC in indicus-taurus heifers can be influenced by finishing precocity at weaning (P < 0.05) with a variation of three follicles. Based on these studies, AFC in heifers from weaning to yearling age is highly variable between individuals and repeatable within the same female. Additionally, there is no correlation between phenotypic or genotypic characteristics and the antral follicle population. However, AFC can be slightly affected by finishing precocity at weaning.

Genetic models for breed quality and navel development scores and its associations with growth traits in beef cattle.

Estimation and prediction ability of linear and threshold models for yearling breed quality score (BQ) and navel development score at weaning (WN) and yearling (YN), considering variances, heritabilities, and rank correlations based on the breeding values predicted for bulls, were compared. Furthermore, it was determined whether BQ, WN, and YN are genetically associated with growth traits (BWG: birth to weaning weight gain, WH: weaning height, WYG: weaning to yearling weight gain, YH: yearling height) to field data of Nelore cattle. For BQ, similar heritabilities were estimated using linear (0.14 ± 0.01) and threshold (0.15 ± 0.02) models. For navel development scores, higher heritability was estimated with threshold (WN 0.22 ± 0.03; YN 0.42 ± 0.03) rather than linear (WN 0.16 ± 0.01; YN 0.29 ± 0.01) models. Rank correlations between sires breeding values predicted for visual scores with linear and threshold models ranging from 0.53 to 0.98, indicating that different sires would be selected using these models, mainly for higher selection intensities. The BQ showed little genetic variability and was not associated with WH and YH. However, low and positive genetic correlations were obtained between BQ with BWG (0.27 ± 0.02) and WYG (0.25 ± 0.02). In general, they are expected low genetic gains for BQ as correlated response to selection based on any of the growth traits studied. The WN showed higher genetic correlation with BWG (0.63 ± 0.02) and WH (0.53 ± 0.02) rather than WYG (-0.06 ± 0.02) and YH (0.26 ± 0.02), indicating that selection for increased growth at weaning (height and weight gain) should lead to longer and most pendulous navels at this age. Weak genetic correlations were obtained between yearling navel and growth traits.

Comparing methodologies to estimate fixed genetic effects and to predict genetic values for an Angus × Nellore cattle population.

The study assesses the need for and effectiveness of using ridge regression when estimating regression coefficients of covariates representing genetic effects due to breed proportion in a crossbreed genetic evaluation. It also compares 2 ways of selecting the ridge parameters. A large crossbred Angus × Nellore population with 294,045 records for weaning gain and 148,443 records for postweaning gain was used. Phenotypic visual scores varying from 1 to 5 for weaning and postweaning conformation, weaning and postweaning precocity, weaning and postweaning muscling, and scrotal circumference were analyzed. Three models were used to assess the need for ridge regression, having 4, 6, and 8 genetic covariates. All 3 models included the fixed contemporary group effect and random animal, maternal, and permanent environment effects. Model AH included fixed direct and maternal breed additive and the direct and maternal heterosis covariates, model AHE also included direct and maternal epistatic loss covariates, and model AHEC further included direct and maternal complementarity effects. The normal approach is to include these covariates as fixed effects in the model. However, being all derived from breed proportions, they are highly collinear and, consequently, may be poorly estimated. Ridge regression has been proposed as a method of reducing the collinearity. We found that collinearity was not a problem for models AH and AHE. We found a high variance inflation factor, >20, associated with some maternal covariates in the AHEC model reflecting instability of the regression coefficients and that this instability was well addressed by using ridge regression using a ridge parameter calculated from the variance inflation factor.

Genomic prediction for tick resistance in Braford and Hereford cattle.

One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for -means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breed-specific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance.

Genetic parameters and investigation of genotype × environment interactions in Nellore × Hereford crossbred for resistance to cattle ticks in different regions of Brazil.

Data from 6,156 Nellore × Hereford crossbred cattle, distributed in 18 herds located in the Brazilian states of Mato Grosso do Sul (MS), São Paulo (SP), Paraná (PR) and Rio Grande do Sul (RS), were analysed in order to investigate genetic variation for resistance to the cattle tick through the estimation of variance components and genetic parameters for counting ticks (Rhipicephalus (Boophilus) microplus) in natural infestation, and also a possible genotype × environment interaction. The tick count data (CC) were transformed to log10(CC + 1) and grouped into two regions, defined by cluster analysis and analysed using the method of restricted maximum likelihood. The statistical model included the additive genetic effect as random and fixed effects of the contemporary group (CG) and genetic group (GG) as classificatory and the age of the animal at the time of counting (linear effect) and individual heterozygosity (linear effect, ranging from 0 to 1) as covariates. In the studied regions, the effect of heterosis found was inversely proportional; in other words, the count of ticks decreased with the increase of heterozygosity. The observed heritability estimation for resistance to tick infestation were 0.12 ± 0.04 and 0.11 ± 0.04 for groups A (RS and south PR) and B (MS, SP and north PR), respectively. The results of this study suggest that selection for animals resistant to ticks would be possible using the tick count to estimate the genetic value of animals, but with a slow genetic progress. The genetic correlation for tick count between the two groups (A and B) was 0.84 ± 0.27 and genotype × environment interaction for this trait was not observed in the studied population.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals.

Additive, dominance, and epistatic loss effects on preweaning weight gain of crossbred beef cattle from different Bos taurus breeds.

(Co)variance components, direct and maternal breed additive, dominance, and epistatic loss effects on preweaning weight gain of beef cattle were estimated. Data were from 478,466 animals in Ontario, Canada, from 1986 to 1999, including records of both purebred and crossbred animals from Angus, Blonde d'Aquitaine, Charolais, Gelbvieh, Hereford, Limousin, Maine-Anjou, Salers, Shorthorn, and Simmental breeds. The genetic model included fixed direct and maternal breed additive, dominance, and epistatic loss effects, fixed environmental effects of age of the calf, contemporary group, and age of the dam x sex of the calf, random additive direct and maternal genetic effects, and random maternal permanent environment effects. Estimates of direct and maternal additive genetic, maternal permanent environmental and residual variances, expressed as proportions of the phenotypic variance, were 0.32, 0.20, 0.12, and 0.52, respectively. Correlation between direct and maternal additive genetic effects was -0.63. Breed ranking was similar to previous studies, but estimates showed large SE. The favorable effects of direct and maternal dominance (P < 0.05) on preweaning gain were equivalent to 1.3 and 2.3% of the phenotypic mean of purebred calves, respectively. The same features for direct and maternal epistatic loss effects were -2.2% (P < 0.05) and -0.1% (P > 0.05). The large SE of breed effects were likely due to multicollinearity among predictor variables and deficiencies in the dataset to separate direct and maternal effects and may result in a less reliable ranking of the animals for across breed comparisons. Further research to identify the causes of the instability of estimates of breed additive, dominance, and epistatic loss genetic effects, and application of alternative statistical methods is recommended.

Estimation of genetic effects in the presence of multicollinearity in multibreed beef cattle evaluation.

Breed additive, dominance, and epistatic loss effects are of concern in the genetic evaluation of a multibreed population. Multiple regression equations used for fitting these effects may show a high degree of multicollinearity among predictor variables. Typically, when strong linear relationships exist, the regression coefficients have large SE and are sensitive to changes in the data file and to the addition or deletion of variables in the model. Generalized ridge regression methods were applied to obtain stable estimates of direct and maternal breed additive, dominance, and epistatic loss effects in the presence of multicollinearity among predictor variables. Preweaning weight gains of beef calves in Ontario, Canada, from 1986 to 1999 were analyzed. The genetic model included fixed direct and maternal breed additive, dominance, and epistatic loss effects, fixed environmental effects of age of the calf, contemporary group, and age of the dam x sex of the calf, random additive direct and maternal genetic effects, and random maternal permanent environment effect. The degree and the nature of the multicollinearity were identified and ridge regression methods were used as an alternative to ordinary least squares (LS). Ridge parameters were obtained using two different objective methods: 1) generalized ridge estimator of Hoerl and Kennard (R1); and 2) bootstrap in combination with cross-validation (R2). Both ridge regression methods outperformed the LS estimator with respect to mean squared error of predictions (MSEP) and variance inflation factors (VIF) computed over 100 bootstrap samples. The MSEP of R1 and R2 were similar, and they were 3% less than the MSEP of LS. The average VIF of LS, R1, and R2 were equal to 26.81, 6.10, and 4.18, respectively. Ridge regression methods were particularly effective in decreasing the multicollinearity involving predictor variables of breed additive effects. Because of a high degree of confounding between estimates of maternal dominance and direct epistatic loss effects, it was not possible to compare the relative importance of these effects with a high level of confidence. The inclusion of epistatic loss effects in the additive-dominance model did not cause noticeable reranking of sires, dams, and calves based on across-breed EBV. More precise estimates of breed effects as a result of this study may result in more stable across-breed estimated breeding values over the years.