03755naa a2200397 a 450000100080000000500110000800800410001902400450006010000180010524501420012326000090026550000130027452025600028765000180284765000110286565000140287665000240289065000240291465300170293865300200295565300330297565300230300865300340303170000190306570000240308470000180310870000260312670000260315270000230317870000200320170000230322170000150324470000160325970000170327577300650329221459262022-08-31       2022    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1093/jas/skac0092DOI1 aCAMPOS, G. S.  aDevelopment of genomic predictions for Angus cattle in Brazil incorporating genotypes from related american sires.h[electronic resource]  c2022  askac009.  aGenomic prediction has become the new standard for genetic improvement programs, and currently, there is a desire to implement this technology for the evaluation of Angus cattle in Brazil. Thus, the main objective of this study was to assess the feasibility of evaluating young Brazilian Angus (BA) bulls and heifers for 12 routinely recorded traits using single-step genomic BLUP (ssGBLUP) with and without genotypes from American Angus (AA) sires. The second objective was to obtain estimates of effective population size (Ne) and linkage disequilibrium (LD) in the Brazilian Angus population. The dataset contained phenotypic information for up to 277,661 animals belonging to the Promebo breeding program, pedigree for 362,900, of which 1,386 were genotyped for 50k, 77k, and 150k single nucleotide polymorphism (SNP) panels. After imputation and quality control, 61,666 SNPs were available for the analyses. In addition, genotypes from 332 American Angus (AA) sires widely used in Brazil were retrieved from the AA Association database to be used for genomic predictions. Bivariate animal models were used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out with the linear regression method (LR) using young-genotyped animals born between 2013 and 2015 without phenotypes in the reduced dataset and with records in the complete dataset. Validation animals were further split into progeny of BA and AA sires to evaluate if their progenies would benefit by including genotypes from AA sires. The Ne was 254 based on pedigree and 197 based on LD, and the average LD (±SD) and distance between adjacent single nucleotide polymorphisms (SNPs) across all chromosomes were 0.27 (±0.27) and 40743.68 bp, respectively. Prediction accuracies with ssGBLUP outperformed BLUP for all traits, improving accuracies by, on average, 16% for BA young bulls and heifers. The GEBV prediction accuracies ranged from 0.37 (total maternal for weaning weight and tick count) to 0.54 (yearling precocity) across all traits, and dispersion (LR coefficients) fluctuated between 0.92 and 1.06. Inclusion of genotyped sires from the AA improved GEBV accuracies by 2%, on average, compared to using only the BA reference population. Our study indicated that genomic information could help us to improve GEBV accuracies and hence genetic progress in the Brazilian Angus population. The inclusion of genotypes from American Angus sires heavily used in Brazil just marginally increased the GEBV accuracies for selection candidates.  aGado de Corte  aGenoma  aGenótipo  aSeleção Genética  aSeleção Genótipa  aAngus cattle  aGEBV accuracies  aGenetic improvement programs  aGenomic prediction  aGenotypes from American Angus1 aCARDOSO, F. F.1 aGULIAS GOMES, C. C.1 aDOMINGUES, R.1 aREGITANO, L. C. de A.1 aOLIVEIRA, M. C. de S.1 aOLIVEIRA, H. N. DE1 aCARVALHEIRO, R.1 aALBUQUERQUE, L. G.1 aMILLER, S.1 aMISTZAL, I.1 aLOURENCO, D.  tJournal of Animal Sciencegv. 100, n. 2, p. 1-13, Feb. 2022.