PSVIII-38 Genomic prediction for tick resistance in Angus cattle

Abstract

Abstract The main objective of this study was to evaluate the feasibility of single-step genomic BLUP (ssGBLUP) for genetic evaluation of tick resistance in Angus cattle in Brazil. Additionally, we investigated population parameters, namely effect population size (Ne) and inbreeding (F) based on pedigree (PED) and genomic (GEN) information. Half-body tick counts were recorded up to three times in the same animal, totaling 2291 records. To normalize the distribution, records were log-transformed prior to the analysis. From 7073 animals in the pedigree, 1299 were genotyped with 3 different SNP chips of density 50k, 77k, and 150k. After imputation and quality control, 61,066 SNP remained. A repeatability animal model was used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out for young genotyped animals, with no phenotypes in the reduced data but at least one record in the complete data, using two different approaches: 1) predictive ability as the correlation between phenotypes adjusted for fixed effects and (G)EBV; 2) a method based on linear regressions that is called LR, which uses correlations between (G)EBV in the complete and reduced data as a measure of consistency between subsequent evaluations. Heritability for tick counts was 0.18 ± 0.03. Based on PED and GEN, Ne was 254 and 199, whereas F was 0.016 and 0.003, respectively. Predictive ability for tick counts was 0.11 for EBV and 0.14 for GEBV, which is considered low. Conversely, when LR validation was used, the relative increase in accuracy by adding extra phenotypic information was 0.49 for EBV and 0.61 for GEBV. Even though tick counts has low heritability, our study indicates that genomic selection can help to improve prediction accuracy and, therefore, to increase tick resistance in this Angus population.