Genomic - polygenic and polygenic predictions for nine ultrasound and carcass traits in 1 Angus - Brahman multibreed cattle using three sets of genotypes

9 The objectives of this study were to estimate variance components, genetic 10 parameters, EBV, accuracies, and rankings for nine ultrasound and carcass traits in a 11 multibreed Angus-Brahman population using three genomic-polygenic models and one 12 polygenic model (PM). The genomic-polygenic models used the complete GeneSeek 13 GPF250k SNP set (GPM), top 5% SNP (GPMR1), and 5% SNP evenly spread across the 14 genome (GPMR2). Yearling ultrasound traits were weight (UW), ribeye area (UREA), 15 backfat (UFAT), and percent intramuscular fat (UPIMF). Carcass traits were slaughter age 16 (SLA), hot carcass weight (HCW), ribeye area (REA), backfat thickness (FAT), and 17 marbling score (MAR). The 9-trait GPM, GPMR1, GPMR2, and PM contained fixed 18 contemporary group, age of calf (ultrasound traits only), sex of calf, and direct heterosis 19 effects, and random animal and residual effects. Variance components and genetic 20 parameters were computed using AIREMLF90. Comparable heritabilities were obtained 21 with GPM and PM for UW (GPM: 0.54 ± 0.05; PM: 0.51 ± 0.05), UREA (GPM: 0.36 ± 22 0.03; PM: 0.34 ± 0.03), UFAT (GPM: 0.12 ± 0.02; PM: 0.11 ± 0.02), UMPIMF (GPM: 23 0.34 ± 0.03; PM: 0.30 ± 0.03), SLA (GPM: 0.59 ± 0.07, PM: 0.61 ± 0.06), HCW (GPM: 24 0.58 ± 0.06, PM: 0.52 ± 0.07), REA (GPM: 0.48 ± 0.04, PM: 0.45 ± 0.05), FAT (GPM: 25 0.41 ± 0.05, PM: 0.30 ± 0.05), and MAR (GPM: 0.56 ± 0.07, PM: 0.51 ± 0.08). Additive 26 genetic correlations between pairs of ultrasound and carcass traits were all between -0.31 27 and 0.81. The highest positive additive genetic correlations were between UW and UREA, 28 UW and HCW, UW and REA, UREA and HCW, UREA and REA, UFAT and FAT, and 29 between HCW and REA. The largest negative additive genetic correlations were between 30 UREA and UPIMF, UFAT and SLA, UFAT and HCW, UPIMF and REA, and between 31 REA and MAR. High similarity existed among predicted EBV and accuracies from GPM, 32