Aplicações da informação genômica no estudo de populações selecionadas
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Data
2019-01-14
Autores
Maiorano, Amanda Marchi [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
A disponibilidade de painéis de polimorfismos de nucleotídeos únicos (SNPs) a baixo custo tem viabilizado estudos genômicos em espécies de interesse econômico. Os objetivos do presente estudo foram conduzir análises de estruturação da população e assinaturas de seleção em duas populações de bovinos Gir selecionadas para diferentes critérios de seleção (corte ou leite); e investigar se a estimativa do efeito materno para característica medida na progênie apresenta maior acurácia com uso de “pool” de sêmen e informação genômica em diferentes cenários simulados de suínos. Análise de componentes principais (PCA) e Análise Discriminante de Componentes Principais (DAPC) foram utilizadas para verificar a estrutura da população nas populações Gir analisadas, e três métodos diferentes foram utilizados na detecção de assinaturas de seleção: índice de fixação (Fst), Escore de Integração dos Haplótipos (iHS) e Homozigose do Haplótipo Estendido Entre Populações (XP-EHH). Diferenciação genética entre as duas populações de bovinos foi observada nos resultados de PCA e DAPC. Um total de 282 genes foram identificados sob seleção, com base nos testes Fst, iHS e XP-EHH, dos quais 35 genes estão associados com QTL previamente descritos em bovinos. Os padrões de variação genética nos bovinos Gir foram consistentes com a presença de pressões seletivas em algum momento na história das populações de corte e leite. Estes resultados fornecem informações complementares sobre regiões genômicas de interesse para estudos funcionais, estudos de associação ampla do genoma e implementação de programas de melhoramento objetivando o melhoramento genético e conservação de espécies domésticas. No estudo de simulação com suínos, o programa QMSim foi utilizado para simular diferentes cenários de irmãos completos e meios-irmãos maternos. Os componentes de variâncias, herdabilidades direta e materna foram estimados com uso do programa AIREMLF90. Os preditores foram calculados por meio das metodologias Melhor Predição Linear Não-viesada (BLUP) e “single step genomic” BLUP (ssGBLUP). Correlações entre os valores genéticos verdadeiros e estimados da população de validação foram usadas para avaliar as acurácias de predição dos efeitos direto (accdireta) e materno (accmat). As estimativas de herdabilidade direta e materna variaram de 0,04 a 0,06 e 0,16 a 0,20, respectivamente. Em geral, as estimativas de accdireta e accmat foram menores para o cenário de pai único comparado com os cenários de “pool” de sêmen. Maiores acurácias foram observadas nos modelos ssGBLUP, independentemente do cenário, evidenciando a importância da inclusão da informação genômica nas avaliações genéticas.
The availability of commercial SNP panels at a low cost has made it possible the application of genomic studies in domestic species. The aim of this study was to conduct population structure and signatures of selection analyzes in two populations of Gir cattle selected for different criteria (beef or dairy); and to investigate whether maternal direct effect for litter birth weight can be improved when pooled semen and genomic information are used in different simulated scenarios in pigs. Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC) were used to verify population structure in the studied Gir cattle populations, and three different methods were used to detect signatures of selection: fixation index (Fst), Integrated Haplotype Score (iHS), and Cross-Population Extend Haplotype Homozygosity (XP-EHH). Genetic differentiation between the two cattle populations was observed in the PCA and DAPC results. A total of 282 genes were identified under selection based on the Fst, iHS and XP-EHH tests, of which 35 genes are associated with QTL previously described in cattle. The patterns of genotypic variation in Gir cattle were consistent with the presence of selective pressures at some point in the history of the beef and dairy populations. These findings can provide complementary information on genomic regions of interest for functional genomic studies, genome-wide associations, and the implementation of breeding schemes aiming genetic improvement and conservation of livestock populations. For the simulation study in pigs, QMSim program was used to simulate different scenarios of full sibling and maternal half sibling families. Variance components, direct and maternal heritabilities were estimated using AIREMLF90. Predictors were computed via Best Linear Unbiased Prediction (BLUP) and single-step genomic BLUP (ssGBLUP). Correlations of estimated and true breeding values from the validation population was used to evaluate accuracies of prediction for direct (accdirect) and maternal (accmat) effects. The estimates of h2direct and h2mat ranged from 0.04 to 0.06 and 0.16 to 0.20, respectively. The estimated direct heritability and maternal heritability ranged from 0.04 to 0.06 and from 0.16 to 0.20, respectively. In general, accdirect and accmat estimates were lower in single-boar scenario compared to pooled semen scenarios. Higher accuracies were found for ssGBLUP when compared to BLUP independently of the scenario, which is a clear evidence it is important to account for genomic information in genetic evaluations.
The availability of commercial SNP panels at a low cost has made it possible the application of genomic studies in domestic species. The aim of this study was to conduct population structure and signatures of selection analyzes in two populations of Gir cattle selected for different criteria (beef or dairy); and to investigate whether maternal direct effect for litter birth weight can be improved when pooled semen and genomic information are used in different simulated scenarios in pigs. Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC) were used to verify population structure in the studied Gir cattle populations, and three different methods were used to detect signatures of selection: fixation index (Fst), Integrated Haplotype Score (iHS), and Cross-Population Extend Haplotype Homozygosity (XP-EHH). Genetic differentiation between the two cattle populations was observed in the PCA and DAPC results. A total of 282 genes were identified under selection based on the Fst, iHS and XP-EHH tests, of which 35 genes are associated with QTL previously described in cattle. The patterns of genotypic variation in Gir cattle were consistent with the presence of selective pressures at some point in the history of the beef and dairy populations. These findings can provide complementary information on genomic regions of interest for functional genomic studies, genome-wide associations, and the implementation of breeding schemes aiming genetic improvement and conservation of livestock populations. For the simulation study in pigs, QMSim program was used to simulate different scenarios of full sibling and maternal half sibling families. Variance components, direct and maternal heritabilities were estimated using AIREMLF90. Predictors were computed via Best Linear Unbiased Prediction (BLUP) and single-step genomic BLUP (ssGBLUP). Correlations of estimated and true breeding values from the validation population was used to evaluate accuracies of prediction for direct (accdirect) and maternal (accmat) effects. The estimates of h2direct and h2mat ranged from 0.04 to 0.06 and 0.16 to 0.20, respectively. The estimated direct heritability and maternal heritability ranged from 0.04 to 0.06 and from 0.16 to 0.20, respectively. In general, accdirect and accmat estimates were lower in single-boar scenario compared to pooled semen scenarios. Higher accuracies were found for ssGBLUP when compared to BLUP independently of the scenario, which is a clear evidence it is important to account for genomic information in genetic evaluations.
Descrição
Palavras-chave
Acurácia de predição, Bovino, Estrutura da população, Gene, Suíno, Accuracy of prediction, Cattle, Population structure, Pigs