Detalhes bibliográficos
Ano de defesa: |
2017 |
Autor(a) principal: |
Marques, Daniele Botelho Diniz |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Tese
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
eng |
Instituição de defesa: |
Universidade Federal de Viçosa
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
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Link de acesso: |
http://www.locus.ufv.br/handle/123456789/18797
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Resumo: |
The widespread use of artificial insemination (AI) has greatly contributed to the success of the pig industry by assisting and disseminating the genetic progress. Currently, young boars are selected for AI based on their breeding values for production traits and selecting boars for semen traits, such as volume, concentration, motility and morphology, and for low variation in semen quality and production is still not a common practice. This selection is important for better performance of boars at AI stations, whose objective is to maximize the number of insemination doses produced by each ejaculate. The estimation of genetic parameters and the quantification of genetic variation for semen traits and within-boar variation allow an analysis of whether these traits should be included in the breeding goal. Besides the estimation of genetic parameters for selection purposes, the interest in studying the molecular processes and genetic mechanisms affecting semen traits is increasing in recent years. Genome-wide association studies (GWAS) are commonly used to identify single nucleotide polymorphisms (SNPs) associated with quantitative trait loci (QTL) with major effect. The weighted single-step GWAS (WssGWAS) is a method that allows estimation of SNP effects using information from all genotyped, phenotyped and pedigree animals. Expanding the frontiers of reproduction studies in pigs, another important field to be explored in breeding programs is the boar fertility. Reproductive traits, such as gestation length (GL), total number of piglets born (TNB) and stillborn (SB) are some of the bottleneck traits for efficient pig production. Because of the low to moderate heritabilities for these traits, it is important to identify all factors influencing them and to include these factors in the genetic evaluation models. The service sire (boar which ejaculate dose was used to inseminate the sow) and ejaculate effects are two of those important factors that have the potential to improve the traditional models used in the genetic evaluations of reproductive traits. Among the elements controlling the litter size, the fertilization rate and prenatal survival rate might be influenced by the service sire due to genetic differences in the capacity of fertilization, which is related to sperm quality and/or the boar genetic contribution to viability of the embryo. In this context, my overall aims were 1) to estimate genetic parameters for semen quality and quantity traits, as well as for within-boar variation of these traits; 2) to identify QTL regions and candidate genes associated with semen traits through a WssGWAS and, subsequently, to perform gene network analyses to investigate the biological processes shared by genes identified in different pig lines and 3) to estimate genetic parameters for service sire on reproductive traits GL, TNB and SB and to evaluate the inclusion of service sire and ejaculate effects in the genetic evaluation models of these traits. The results of this thesis showed moderate estimates of heritability and favorable genetic correlations between semen traits, indicating that boar selection for these traits could make reasonable genetic progress. In addition, relevant genetic variation was found for within-boar variability of these traits, revealing the possibility of selection of boars for reduced variation in semen quality and production. Results from WssGWAS pinpointed relevant QTL regions explaining high proportions of genetic variance (up to 10.8%) for semen traits in several pig chromosomes, confirming the assumption of genetic complexity of these traits. This identification was possible with low number of animals having both phenotypes and genotypes due to the appropriate choice of the method. Candidate genes SCN8A, PTGS2, PLA2G4A, DNAI2, IQCG, LOC102167830, NME5, AZIN2, SPATA7, METTL3 and HPGDS were identified associated with semen traits in the QTL regions identified for the pig lines evaluated. The gene network analysis showed candidate genes found for different pig lines sharing biological pathways that occur in mammalian testes. Regarding boar fertility, the results showed that there is genetic variation due to service sire effect on GL, TNB and SB; and the model with inclusion of permanent environmental and genetic effects due to service sire, in addition to ejaculate effect, showed the best fit to the data. This thesis resulted in important and innovative scientific information on male reproduction field in pigs, which will contribute to increase the still scarce knowledge about genetic selection and genomic architecture of boar semen quality and fertility traits. |