A total of 17 356 test-day milk yield (TDMY) records from 642 first lactations of Alpine goats were used to model variations in lactation curve using random regression models (RRM). Orthogonal Legendre polynomials and B-splines were evaluated in order to obtain adequate and parsimonious models for the estimation of genetic parameters. The analysis were performed using a single-trait RRM, including the additive genetic, permanent environmental and residual effects. We estimated the mean trend of milk yield, and the additive genetic and permanent environmental covariance functions through random regression using different orders of Orthogonal Legendre polynomial (three to six) and B-spline functions (linear, quadratic and cubic, with three to six knots). This study further evaluated different number of classes of residual variances. The covariance components and the genetic parameters were estimated using the Restricted Maximum Likelihood method. Heritability estimates presented similar trends for both functions. RRMs with a higher number of parameters better described the genetic variation of TDMY throughout the lactation. The most suitable RRM for genetic evaluation of TDMY of Alpine goats is a quadratic B-spline function with six knots, for the mean trend, curves of additive genetic and permanent environmental effects and five classes of residual variance.

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Meta-analysis based on a random-effects model is used to summarise and overcome the variability between divergent parameter estimates. We proposed a meta-analysis of published heritability and genetic-correlation estimates for reproduction, growth and carcass traits in purebred Nellore cattle. In total, 197 heritability and 107 genetic-correlation estimates from 62 scientific publications were used here. Most of traits (gestation length; weights at birth, 120, 210, 365 and 550 days of age; mature weight and all carcass traits) presented direct heritability estimates ranging from 0.20 to 0.40. Age at first calving presented the lowest value among direct heritabilities (0.1498); whereas the higher values (>0.40) were found for scrotal circumference at different ages and for weight at 450 days of age. Low maternal heritability estimates (ranging from 0.06 to 0.11) were observed for all growth traits. With the exception of correlation estimates involving the age at first calving, all other correlations were positive. High correlations (>0.85) were found mainly for the same trait at different ages. The results reported here will give support to genetic evaluations when reliable estimates for different traits in purebred Nellore cattle are not available.

a b s t r a c tReproductive traits as number of piglets born (NPB) and weaned (NWP) are directly related to the economic efficiency of swine production systems. Pig breeding programs seek to increase the number of weaned piglets per sow per year, and the NPB is among the factors that directly and indirectly influence the NWP. Thus, multi-trait evaluations are essential to estimate heritabilities and mainly genetic correlations between these traits over different farrowing orders. In general, Gaussian linear mixed models have been used to genetic evaluation of litter traits; however since these traits are characterized as count variables, Poisson models are also indicated. Some studies were carried out using Poisson mixed models in the area of Animal Breeding and Genetics, but they do not point out for a multi-trait scenario, as it should be for litter size at birth and weaning. Toward this orientation, we aimed to apply a multi-trait Poisson mixed model (MPM) for the genetic evaluation of the number of born and weaned piglets under a Bayesian framework. It was aimed also to compare the proposed model with the traditional multi-trait Gaussian model (MGM) by using posterior based goodness-of-fit measures. Two-trait analyses for NPB and NWP were performed separately by each considered farrowing order (first, second and third) using MPM and MGM fitted to data from a commercial Landrace population. Based on DIC (Deviance Information Criterion) and PMP (Posterior Model Probability) values, the MGM outperformed the MPM, but the genetic parameter and breeding values provided by both models were consistent and similar over the three first farrowing orders. Bayesian generalized a multi-trait mixed model approach is feasible for genetic evaluations in the animal breeding context and can be an alternative method for genetic evaluations assuming non-Normal phenotypes.

ABSTRACT. Knowledge of dominance effects should improve genetic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of heterosis in crossbreeds. In this study, we combined genomic and pedigree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broadsense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respectively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only E.V. Costa et al. 6304©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (2): 6303-6311 (2015) for birth weight and weight at 21 days of age.