PSXI-4 - Genome-wide association study for muscle visual score in Nellore cattle raised in pasture-based systems

Visual scoring traits have been proposed as an alternative to evaluate body composition of Zebu cattle near the slaughter season when phenotyping technologies are not available. Considering the increased demand for high-quality animal protein in developing countries, there is a need to genetically improve body muscle (MUSC) in Zebu cattle (Bos taurus indicus), especially in animals raised in pasture-based systems. Therefore, our main objectives were to estimate genetic parameters, perform a genome-wide association study based on the single-step GBLUP approach (ssGWAS), and identify candidate genes and metabolic pathways related to MUSC in Nellore cattle. A total of 20,808 Nellore animals born between 2009 and 2018 were visually score at 18 months of age and 2,775 of these animals were also genotyped using the GGP-Indicus 35K SNP panel (33,247 SNPs after quality control). Heritability was estimated based on the REML approach and the model included the effects of age at measurement as covariable and the contemporary group (farm, birth season, management group and sex). The ssGWAS was performed using the BLUPF90 family programs. The identification of candidate genes was performed through the Ensembl database incorporated in the BioMart tool. MUSC is heritable (0.38) and can be improved through selection. Nineteen genomic regions (explaining 38.12% of the total additive genetic variance) located on BTA1, BTA7, BTA9, BTA16, and BTA21 and harboring 19 candidate genes were identified. The main genes identified were SEMA6A, TIAM2, UNC5A, and UIMC1, which are related to the metabolism of energy, growth, homeostasis and axonogenesis, and therefore, muscle development. These findings contribute to a better understanding of the molecular mechanisms over the gene expression of muscle visual score in Nellore cattle, and the polymorphisms located in these genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for body and carcass traits.