RESUMO
Understanding animals' genetic potential for carcass traits is the key to genetic improvements in any beef cattle. In this study, we investigated the genetic merits of carcass traits using Hanwoo males raised in a 30-month production system (PROD30). We achieved this using a dataset comprising 6092 Hanwoo males born between 2005 and 2017 and measures of four carcass traits (carcass weight, CWT; eye muscle area, EMA; backfat thickness, BFT; and marbling score, MS). Genetic parameters were estimated using a multiple-trait animal model through the AIREMLF90 program. According to the multiple-trait model, the h2 of CWT, EMA, BFT, and MS were 0.35 ± 0.04, 0.43 ± 0.05, 0.48 ± 0.05, and 0.56 ± 0.05, respectively. The strongest genetic correlation (rg) was obtained between CWT and EMA (0.49 ± 0.07), whereas it was negligible between CWT and BFT. EMA and MS were also moderately correlated, whereas there was a relatively low negative correlation between EMA and BFT (-0.26 ± 0.08). Our study revealed a consistent indirect genetic improvement in animals from 2005 onwards. Although Hanwoo improvement has mainly focused on males under a 24-month production cycle, we observed PROD30 males to have somewhat similar genetic potential. Our results provide useful insights into the genetic merits of PROD30 males for the first time, which may facilitate future studies on them and their integration into the Hanwoo National Evaluation for genomic selection.
RESUMO
The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.
