A. A. Boligon

Covariance functions for body weight from birth to maturity in Nellore cows.

The objective of this study was to estimate (co)variance functions using random regression models on Legendre polynomials for the analysis of repeated measures of BW from birth to adult age. A total of 82,064 records from 8,145 females were analyzed. Different models were compared. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered as random covariables. Eight models with polynomials of third to sixth order were used to describe additive direct and maternal effects, and animal and maternal permanent environmental effects. Residual effects were modeled using 1 (i.e., assuming homogeneity of variances across all ages) or 5 age classes. The model with 5 classes was the best to describe the trajectory of residuals along the growth curve. The model including fourth- and sixth-order polynomials for additive direct and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects were the best. Estimates of (co)variance obtained with the multi-trait and random regression models were similar. Direct heritability estimates obtained with the random regression models followed a trend similar to that obtained with the multi-trait model. The largest estimates of maternal heritability were those of BW taken close to 240 d of age. In general, estimates of correlation between BW from birth to 8 yr of age decreased with increasing distance between ages.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Genetic correlations between heifer subsequent rebreeding and age at first calving and growth traits in Nellore cattle by Bayesian inference.

We estimated heritability for subsequent rebreeding (SR) of heifers and genetic correlations between this trait and weaning weight (WW), weight gain from weaning to yearling (WG), age at first calving (AFC), and mature cow weight (MW), in order to evaluate whether SR could be included as selection criterion in Nellore cattle. The SR of heifers was defined by attributing a value of 1 (success) or 0 (failure) to heifers that calved or not, respectively, given that they had calved once before. Records from 127,430 Nellore animals were analyzed. Genetic parameters were estimated by Bayesian inference using a nonlinear (threshold) animal model for SR and a linear animal model for the other traits in three-trait analyses, including SR and WW in all analyses. The posterior means of heritability for SR, WW, WG, AFC, and MW were 0.18 ± 0.02, 0.21 ± 0.01, 0.30 ± 0.01, 0.21 ± 0.01, and 0.45 ± 0.04, respectively. The posterior mean estimates of genetic correlations between SR and WW, WG, AFC, and MW were -0.20 ± 0.06, 0.31 ± 0.07, -0.77 ± 0.05, and -0.15 ± 0.09, respectively. Based on these genetic correlations, selection for higher gains for WG and younger AFC should result in an increase in heifer SR rates, while long-term selection for increasing WW should promote unfavorable responses in heifer SR. The use of breeding values for heifer SR as a selection criterion of Nellore bulls could increase heifer SR rate without significant changes in MW.

Design of selection schemes to include tick resistance in the breeding goal for Hereford and Braford cattle1

Ticks are one of the main causes of losses in cattle, causing economic impact by reducing productivity and fertility and by transmission of diseases. The objective of this study was to analyze the genetic gains obtained through different strategies to include traditional (EBV) or genomic EBV (GEBV) for tick count (TC) in selection indexes for Hereford and Braford cattle. Besides TC, we also considered traits currently included in the Delta G Breeding Program Index (DGI): preweaning gain, weaning conformation, weaning precocity, weaning muscling, postweaning gain, yearling conformation, yearling precocity, yearling muscling, and scrotal circumference. Genetic gain per generation (ΔG) was evaluated using the current DGI and including TC in 8 alternative scenarios with TC relative weightings of 10, 50, or 100% and using phenotype or GEBV. Genomic EBV accuracy () ranged between 0.1 and 0.9. As expected, increasing increases the accuracy of the index () for all scenarios in which GEBV were considered. As the relative weight of TC was increased to 50%, greater ΔG differences in relation to the baseline DGI (

Principal component analysis of breeding values for growth and reproductive traits and genetic association with adult size in beef cattle1

53.03) scenario were observed when the GEBV information was included with equal to or greater than 0.7 only for TC (ΔG between

Reduced-rank models of growth and reproductive traits in Nelore cattle

61.06 and

Association of ADIPOQ, OLR1 and PPARGC1A gene polymorphisms with growth and carcass traits in Nelore cattle.

74.26) or equal to or greater than 0.5 for all traits (ΔG between

Pre-slaughtering factors related to bruises on cattle carcasses

56.03 and

Genetic study of visual scores and hip height at different ages in Nelore cattle

83.36). To achieve these accuracies for traits with low heritability, a large calibration data set would be required. Focusing only on TC, the availability of genomic information would be desirable to avoid the need to count ticks and the exposure of animals to parasitism risks. However, for = 0.7, the respective numbers for Hereford and Braford would be 4,703 and 6,522 animals. As expected, when comparing the relative index weights of 10, 50, and 100% for TC, the highest response to selection per generation (RS) for TC was in the scenario was with 100% relative weight and GEBV for this trait (SR = -0.09 SD with = 0.9). This would be the recommended scenario to form tick-resistant lines in Hereford and Braford cattle. However, with 50% relative weight for TC, including GEBV information for TC only or for all traits in index ( = 0.9), it should yield 93 or 84% of RS, respectively, compared to that obtained with full emphasis on TC (100% relative weight) and GEBV information. This indicates that in the presence of highly accurate GEBV, despite slightly slower gain for TC, indexes with 50% relative weight for TC are interesting alternatives to jointly improve tick resistance and other relevant traits.

Genomic prediction using different estimation methodology, blending and cross-validation techniques for growth traits and visual scores in Hereford and Braford cattle

Principal component analysis was applied to evaluate the variability and relationships among univariate breeding values predicted for 9 weaning and yearling traits, as well as suggest functions of the traits that would promote a particular breeding objective. Phenotypic and pedigree information from 600,132 Nelore animals was used. Genetic parameters and breeding values were obtained from univariate analyses of birth to weaning weight gain; weaning to yearling weight gain; conformation, finishing precocity, and muscling scores at weaning and at yearling; and yearling scrotal circumference. The principal component mainly associated with maturity (precocious vs. late animals) was used as a pseudophenotype in bivariate analyses with either adult weight or adult height of cows. Direct heritability estimates ranging from 0.19 ± 0.01 to 0.41 ± 0.01 indicate that these 9 traits are all heritable to varying degrees. Correlations between the breeding values for the various traits ranged from 0.14 to 0.88. Principal component analysis was performed on the standardized breeding values. The first 3 principal components attained the Kaiser criterion, retaining 48.06%, 18.03%, and 12.97% of the total breeding value variance, respectively. The first component was characterized by positive coefficients for all traits. The second component contrasted weaning traits with yearling traits. The third component represented a contrast between late maturity animals (better for weight gain and conformation) and early maturity animals (better for finishing precocity, muscling, and scrotal circumference). Thus, the first 3 components represent 3 different potential selection criteria. Selecting for the first principal component would identify animals with positive breeding values for all studied traits. The second principal component may be used to identify animals with higher or lower maturation rates (precocity). Animals with negative values in the third principal component are regarded as early maturing. Genetic correlations between maturity (third principal component) with adult weight and adult height were 0.19 ± 0.02 and 0.32 ± 0.02, respectively. These results showed that the weaning and yearling bovine maturity is genetically associated with the adult size of the cows used in reproduction.