991 resultados para Breeding value


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Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

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Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Com o objetivo de verificar a existência da interação genótipo x ambiente, sob a forma de heterogeneidade de variâncias para a produção de leite na espécie bubalina e o seu impacto na avaliação genética dos animais, utilizando a inferência Bayesiana por meio de Amostrador de Gibbs, foram utilizados 5.484 registros de produção de leite referentes à produções de 2.994 búfalas predominantemente Murrah, filhas de 150 reprodutores, acasalados com 1130 matrizes, cujos partos ocorreram entre os anos de 1974 e 2004. Os registros foram provenientes do Programa de Melhoramento Genético dos Bubalinos (PROMEBUL) com a adição de registros provenientes do rebanho da EMBRAPA Amazônia Oriental -EAO, localizada em Belém, Pará. Foram estabelecidas classes de rebanho-ano de parto e de acordo com o desvio padrão de cada classe, os registros de produção de leite foram classificados em classes de alto e baixo desvio-padrão fenotípico. Posteriormente, os dados foram analisados desconsiderando e considerando as classes de desvio-padrão. O modelo utilizado empregou os efeitos fixos referentes às classes de rebanho-ano, mês de parto e covariáveis idade da fêmea ao parto e duração da lactação, além do efeito aleatório de animal, ambiente permanente e ambiente temporário. Para os efeitos fixos, foi assumido distribuição à priori uniforme e para os componentes de (co)variâncias foram assumidas distribuições priori qui-quadrado inversa e Wishart invertida. As médias observadas e desvio-padrão para produção de leite nas classes de alto e baixo desvio-padrão e em análise geral, foram iguais a 1870,21±758,78, 1900,50±587,76 e 1885,48±677,98, respectivamente. As médias posteriores para os componentes de variâncias foram maiores na classe de alto desvio-padrão. A herdabilidade obtida na classe de alto desvio-padrão foi próxima do valor observado na análise geral e inferior ao valor encontrado na classe de baixo desvio-padrão fenotípico. A correlação genética para produção de leite entre as classes de desvio-padrão foi igual a 0,58. As correlações de Spearman entre os valores genéticos para a produção de leite obtidos em análise geral com os valores obtidos nas classes de alto e baixo desvio padrão foram iguais a 0,94 e 0,93, respectivamente, para todos os reprodutores. Para uma amostra dos 10 melhores reprodutores, as mesmas correlações foram iguais a 0,94 e 0,47, respectivamente. Tais resultados revelam presença de heterogeneidade de variâncias entre rebanhos e esta heterogeneidade de variâncias é resultante de fatores ambientais, que podem levar a uma classificação errônea dos melhores reprodutores geneticamente para a produção leite.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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The publication of the human genome sequence in 2001 was a major step forward in knowledge necessary to understand the variations between individuals. For farmed species, genomic sequence information will facilitate the selection of animals optimised to live, and be productive, in particular environments. The availability of cattle genome sequence has allowed the breeding industry to take the first steps towards predicting phenotypes from genotypes by estimating a genomic breeding value (gEBV) for bulls using genome-wide DNA markers. The sequencing of the buffalo genome and creation of a panel of DNA markers has created the opportunity to apply molecular selection approaches for this species.The genomes of several buffalo of different breeds were sequenced and aligned with the bovine genome, which facilitated the identification of millions of sequence variants in the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome compared with the bovine genome, 90,000 putative single nucleotide polymorphisms (SNP) were selected to create an Axiom (R) Buffalo Genotyping Array 90K. This SNP Chip was tested in buffalo populations from Italy and Brazil and found to have at least 75% high quality and polymorphic markers in these populations. The 90K SNP chip was then used to investigate the structure of buffalo populations, and to localise the variations having a major effect on milk production.

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Pós-graduação em Genética e Melhoramento Animal - FCAV