Análise de associação global do genoma para características produtiva e reprodutiva em suínos

• Autor(a) principal: Leite, Carla Daniela Suguimoto
• Data de Publicação: 2013
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: http://locus.ufv.br/handle/123456789/1834
• topic: Seleção genômica; Simulação de dados; Avaliação genética; SNP; Genomic selection; Simulation data; Genetic evaluation; SNP; CNPQ::CIENCIAS AGRARIAS::ZOOTECNIA::GENETICA E MELHORAMENTO DOS ANIMAIS DOMESTICOS

The aim of the genome wide association studies (GWAS) is to identify chromosome regions associated with phenotypic traits, based in differences between allele frequencies of single nucleotide polymorphisms (SNPs). The aim of this study was to identify SNPs in the swine genomes that influence productive and reproductive traits, using information from animals from a breeding swine program. It was used genotypic and phenotypic data from Landrace (LA) and Large White (LW) animals. First, it was performed quality control of samples and SNPs. After this step, the GWAS analysis for age adjusted to 100 kg and age at first farrowing traits, were performed only with LA data. The quality control for samples removed in the cases of disagreement on sex or paternity, duplicate animals, call rate < 90%, deviations of heterozygosity of more than ± 3 standard deviations, and check if there is stratification and substructure in the population. For the quality control of the SNPs, were removed those that have call rate < 0.98, the minor allele frequency (MAF) < 0.03, Hardy-Weinberg equilibrium (HWE) with &#967;2 < 10-6, and the SNPs that were coincident. The softwares R and Plink were used for this analysis. After removing samples and SNPs that were problematic, for the analysis remained 604 samples and 42,360 SNPs for LA and for LW there were 345 samples and 40,166 SNPs. For GWAS analysis, by single marker, phenotypic data were previously corrected for contemporary group effects for both traits. The model included as fixed effects the mean and the SNPs and as random infinitesimal effect and residue. The relationship matrix contains information of the last 3 generations of genotyped animals. It was considered 3 thresholds: a conservative (p-value = 5x10-7), a moderate (p- value = 5x10-5) and one based on Bonferroni test (p-value = 1.18x10-6). The GWAS analysis for age at 100 kg found 22 significant SNPs on chromosome 1 and one SNP on chromosome 4, considering the moderate threshold. For age at first farrowing, two SNPs were significant, with no defined position in the genome. For both traits, the additive effect estimated was of large magnitude, 2.22 days for age at 100 kg and 4.69 days for age at first farrowing, indicating a great potential of the inclusion of this information in selection to reduce these traits. The quality control analysis was effective to remove samples and SNPs with problems in genotyping. Further analysis including more genotyped animals and evaluation of additional methodologies may detect SNPs with minor effect for traits of interest.