Estimation of genetic parameters for weight and length gains in tambaqui (Colossoma macropomum).

The goal of this study was to determine the genetic parameters for growth traits in tambaqui (Colossoma macropomum) fish of similar age and weight. The data set included monthly measurements of body weight and length from120 fish for a year (1,440 measurements). The study found that weight gain had a heritability estimate of 0.01, while length gain had a heritability estimate of 0.27. There was a high positive correlation (0.84) between weight and length gains. The genetic variance and heritability of body weight decreased with age. This study suggests that breeding programs should select for body weight and weight gain to promote genetic gain in tambaqui. Selecting younger animals can also help reduce costs while still achieving genetic gains.

Method for the estimation of genetic merit of animals with uncertain paternity under Bayesian inference.

The use of controlled mating or artificial insemination is impracticable in the case of large herds, mainly because of labour costs and the need to delimit areas during the breeding period. However, the exclusion of information from animals with uncertain paternity reduces genetic progress. The objectives of this study were as follows: (i) propose an iterative empirical Bayesian procedure to implement the hierarchical animal model (ITER); (ii) calculate the posterior probabilities of paternity by the maximum likelihood method following the concepts; (iii) compare an average numerator relationship matrix (ANRM), Bayesian hierarchical (HIER) models and ITER. Records of Nellore animals born between 1984 and 2006 from the zootechnical archive of Agropecuária Jacarezinho Ltda were used. For data consistency, records of contemporary groups (CGs) with fewer than three animals and animals whose records were 3.5 standard deviations above or below the mean of their CG were eliminated. After editing the data, 62,212 animals in the file and 12,876 animals in pedigree file were maintained, respectively. Spearman and Pearson correlations between the posterior mean of the genetic effects of animals were calculated to compare the ranking of animals for selection. Simulated data were used to confirm the veracity of the model. The correlations between ITER and HIER and between ITER and ANRM were similar evaluating different files, which decreased at the same proportion when only high-ranked animals were evaluated. In conclusion, the model proposed herein is a suitable computational alternative to improve the prediction of breeding values of animals in genetic evaluations using large databases, including animals with uncertain paternity.

Comparison of a genetic group and unknown paternity models for growth traits in Nellore cattle.

The aim of the present study was to compare a model assuming unknown paternity and a model using genetic grouping to indicate the most adequate statistical procedure for the estimation of breeding values for animals with uncertain paternity. After data consistency, 62,212 Nellore animals, offspring of 581 bulls and 27,743 cows, were used in the analyses. The pedigree file contained 75,088 animals, including 22,810 (30.18%) offspring of multiple sires and 12,876 animals belonging to the base population with unknown parents. Three different approaches were adopted to deal with uncertain paternity of multiple-sire (MS) offspring. In the model of unknown paternity, the MS groups were ignored, and the sires of MS offspring were considered to be unknown and to belong to a single base population. In the genetic group approach, 2 definitions were used. In the first definition (GGa), "phantom parents" for animals with uncertain paternity were attributed, defining the genetic group as the MS group. In the other approach, GGb, phantom parents for animals with uncertain paternity were also attributed; however, MS offspring were clustered in genetic groups according to their year of birth, every 3 yr, on the basis of the average of male generation interval. Univariate analyses were performed under the Bayesian approach via Markov chain Monte Carlo methods. Models were compared by deviance information criteria and the conditional predictive ordinate. According to the choice criteria results, the genetic group model defined by the generation interval of males was more appropriate for predicting the genetic merit of animals with uncertain paternity. Therefore, the use of this model is recommended for the prediction of genetic merit and classification of offspring of multiple sires.

Genetic associations of sexual precocity with growth traits and visual scores of conformation, finishing, and muscling in Nelore cattle.

The objective of this study was to determine the possible use of heifer pregnancy at 16 mo as a selection criterion and its possible genetic associations with hip height, yearling weight, and visual scores of conformation, finishing, and muscling. The data set contained records of 56,458 Nelore yearlings for the traits described above. Covariance components were estimated by bivariate animal models assuming a linear model for hip height, yearling weight and conformation, and finishing and muscling scores, and a nonlinear (threshold) model for heifer pregnancy. Variance components were estimated using Bayesian inference. Flat distributions were used for all (co)variance components and genetic correlations. The first 5,000 rounds were considered as the burn-in period and discarded. The heritability estimate of heifer pregnancy indicates that the trait can be used as a selection criterion. Long-term selection for heifer pregnancy will result in a reduction of animal height. However, selection for increasing yearling weight should be possible in this population of Nelore cattle without having major effects on fertility. Selection for increasing visual scores of conformation, finishing, and muscling will result in small or no response in heifer pregnancy at 16 mo.