Beef cattle production is a major component of the Brazilian economy and places the country amongst the top worldwide beef producers and exporters. The development and use of composite populations represent a promising alternative to increase production efficiency and quality in beef cattle. The strategic combination of different breeds poses a great opportunity to maximize genetic variability and exploit heterosis and breed complementarity. In order to successfully implement genomic evaluations for composite populations, various genomic approaches and methodologies need to be investigated. For instance, the use of haplotype information and incorporation of both additive and non-additive effects in the genomic evaluation models. In addition, the majority of genomic models and methods currently used for genomic evaluations were developed based on purebred animals and the knowledge on the use of genomic information in synthetic or composite cattle breeds is still very limited. Therefore, studies investigating more sophisticated methodologies and genomic approaches will enable a more efficient use of the genomic information available for composite breeds and consequently, more accurate breeding values. This project is part of a thematic project supported by FAPESP (Process 2014/07566-2), also an important part of the developing project in Brazil (Process 2017/11919-6). The overall objectives are to investigate genomic selection methodologies and imputation strategies to improve the accuracy of genomic prediction of breeding values in the genetically diverse population of Montana Tropical®. The traits included in this study will be: birth weight, weaning weight, weight at 12 months, scrotal circumference (as indicator of fertility performance) and musculature at 14 months. A total of 2,000 high-density genotypes from animals of numerous breeds (Montana, Nellore, Aberdeen Angus, Belmont Red, Bonsmara, Charolais, Devon, Hereford, Braunvieh, Limousin, Red Angus, Senepol and Simmental) are currently available for this research. The imputation analyses will be performed using the FImpute 2.2 and Beagle 4.1 software. Genomic predictions will be performed using different methodologies (GBLUP, Bayes LASSO, CÀ, R and Bayesian single-step) and strategies to define the training populations, based on results of genetic diversity and population structure analyses. In summary, this project will contribute to the development of genomic methods and approaches to fastener genetic progress for a variety of economically important traits in composite beef cattle and increase the profitability of beef producers.
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