The aim was to analyze variation in 12 Brazilian and Moroccan goat populations, and, through principal component analysis (PCA), check the importance of body measures and their indices as a means of distinguishing among individuals and populations. The biometric measurements were wither height (WH), brisket height (BH) and ear length (EL). Thorax depth (WH-BH) and the three indices, TD/WH, EL/TD and EL/WH, were also calculated. Of the seven components extracted, the first three principal components were sufficient to explain 99.5% of the total variance of the data. Graphical dispersion by genetic groups revealed that European dairy breeds clustered together. The Moroccan breeds were separated into two groups, one comprising the Drâa and the other the Zagora and Rhâali breeds. Whereas, on the one side, the Anglo-Nubian and undefined breeds were the closest to one another the goats of the Azul were observed to have the highest variation of all the breeds. The Anglo-Nubian and Boer breeds were similar to each other. The Nambi-type goats remained distinct from all the other populations. In general, the use of graphical representation of PCA values allowed to distinguish genetic groups.

-The objective of this study was to characterize the genetic variability of Anglo-Nubian goats using microsatellite markers. The study was conducted using herds from four municipalities of Central-Northern Piauí (Teresina, José de Freitas, Campo Maior, and Angical), where technical information is scarce. Seven markers suggested by FAO were used (ILSTS11, McM527, INRA23, ETH10, OarfCB304, OarfCB48, and MAF209). The samples were genotyped using a 7% polyacrylamide gel. The average number of alleles per locus was 4.0, with observed and expected heterozygosity of 0.38 and 0.55, respectively. Few deviations from the Hardy-Weinberg equilibrium were observed for each population. Only two loci deviated significantly in two localities. The coefficient of gene differentiation (G ST' ) indicated that 11.9% of the genetic variation was distributed among populations, and according to the coefficient of inbreeding (G IS = 0.23 and F IS = 0.23), there is a deficiency of heterozygotes within populations. These findings corroborate the Bayesian analyses performed with the STRUCTURE software, which revealed three distinct and moderately structured groups. The graphic analysis showed that Teresina and José de Freitas are isolated groups, while Angical and Campo Maior share most of their alleles. Despite this, the level of diversity among herds was low. Based on this genetic structure, exchange of reproducers among municipalities is recommended for the maintenance of the breed.

-The aim of this study was to compare the genetic diversity of 12 populations of goats in Brazil and Morocco (n = 796) through the use of physical measurements and different multivariate techniques. Traits measured included wither height (WH), distance from the brisket to the ground (BH) and ear length (EL). The standardized Euclidean distance (D) was adopted. The D values were submitted to clustering analysis using hierarchical methods (from nearest neighbor and UPGMAUnweighted Pair Group Method with Arithmetic Mean) and the numbers of clusters were analyzed using the Tocher optimization method. The population clustering was different depending on the method of analysis used. Among the hierarchical methods, UPGMA showed the best fit (CCC = 0.82). The Tocher method enabled the formation of four different clusters. Although the hierarchical and Tocher methods resulted in different cluster formations, both contributed to the interpretation of the genetic cluster divergence. The results obtained through UPGMA and Tocher optimization enable their use for future studies that may include a larger number of biometric variables on greater numbers of individuals and additional populations.

The application of modern methods using the animal model is essential for the efficient conduct of any breeding program. The procedures to characteristics in which continuous variation is assumed are not suitable for those with non-continuous variation. In threshold model assumes that the answering process is associated with an underlying continuous variable which has continuous normal distribution. The probabilistic representation of all knowledge uncertain is the essence of Bayesian inference, such knowledge is related to future observable quantities or unknown parameters. The priori and posteriori concepts are always relative to the observation at the time considered. Thus, we aimed at with this revision presenting and discussing some trends and applications of threshold model with a focus on Bayesian inference, applied to animal breeding.

ObjectiveThe aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats.MethodsData were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain.ResultsThreshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude.ConclusionDirect selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.