Caracterização da estrutura genética da raça Guzerá (Bos indicus) através de genotipagem em escala genômica - Pablo Augusto de Souza Fonseca (2014)
The Brazilian dairy industry had a significant increase in its production in the last decade, reaching an annual production of 32.30 billion liters in 2012. This increase is explained, in part, by the genetic improvement of the dairy herds subjected to genetic selection programs. About 80% of all Brazilian cattle heads are Zebu animals or their crossbreeds. The Guzerá breed stands out among the other zebuine breeds due to some important characteristics like resistance to parasites such as ticks, ability to consume gross forage and heat tolerance. However, the genetic estimative for Guzerá breed is close to the threshold in which the loss of genetic variability by genetic drift and inbreeding depression is observed. Until the present moment, the studies developed in the Guzerá breeds, which aim to estimate the genetic variability, are based on pedigree, microsatellites and on few SNPs data, which do not make possible a Genome-Wide estimative. The development of high-density genotyping chips for cattle permitted a more precise approach to estimate the genetic variability. These methods, in general, assume that the population studied is a homogeneous sample. However, natural populations are connected in networks due to gene flow. This can lead to spurious representations of population structure and/or associations, if they are not adjusted correctly before the analyses. Thus, strategies to reduce the relatedness level in samples are important tools to avoid spurious associations and erroneous conclusions. The present work is composed of two studies. In the first, the performance of the platform Illumina Bovine SNP50 for the Guzerá breed and the applicability of a methodology based on centrality statistics analysis to resampling individuals based on the Kinship coefficient was evaluated. The second study is the analysis in Genomic scale of the population genetic structure of Guzerá breed. For this, individuals from herds belonging to the National breeding programs of Guzerá were evaluated. The sample used in the present study represents the most selected and one of the largest genetic repositories of the Guzerá breed in Brazil. The results of these studies indicate a great applicability of the node selection algorithm based on a networks degree of centrality statistic, showing up more efficient for the detection of some estimative parameters of the genetic diversity such as ROH and resulting in a higher number of individuals in the final sample when compared to the other strategy of resampling. Furthermore, the population genetic diversity study of Guzerá breed indicates a strong influence of the bottlenecks and increase of the endogamy, suffered by the breed during the process of settlement in Brazil, in the current genetic diversity of the breed. These findings reinforce the results already presented in other studies, which indicate the need for monitoring the genetic diversity of the breed through parameters of population diversity, to ensure the success of the breeding programs