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Article

Evaluation of Genome-Enabled Prediction for Carcass Primal Cut Yields Using Single-Step Genomic Best Linear Unbiased Prediction in Hanwoo Cattle

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Animal Breeding and Genetics Division, National Institute of Animal Science, Cheonan-si 31000, Chungcheongnam-do, Korea
2
Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran
3
Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si 17579, Gyeonggi-do, Korea
*
Authors to whom correspondence should be addressed.
Academic Editor: Martien A. M. Groenen
Genes 2021, 12(12), 1886; https://doi.org/10.3390/genes12121886 (registering DOI)
Received: 12 October 2021 / Revised: 16 November 2021 / Accepted: 24 November 2021 / Published: 25 November 2021
(This article belongs to the Section Animal Genetics and Genomics)
There is a growing interest worldwide in genetically selecting high-value cut carcass weights, which allows for increased profitability in the beef cattle industry. Primal cut yields have been proposed as a potential indicator of cutability and overall carcass merit, and it is worthwhile to assess the prediction accuracies of genomic selection for these traits. This study was performed to compare the prediction accuracy obtained from a conventional pedigree-based BLUP (PBLUP) and a single-step genomic BLUP (ssGBLUP) method for 10 primal cut traits—bottom round, brisket, chuck, flank, rib, shank, sirloin, striploin, tenderloin, and top round—in Hanwoo cattle with the estimators of the linear regression method. The dataset comprised 3467 phenotypic observations for the studied traits and 3745 genotyped individuals with 43,987 single-nucleotide polymorphisms. In the partial dataset, the accuracies ranged from 0.22 to 0.30 and from 0.37 to 0.54 as evaluated using the PBLUP and ssGBLUP models, respectively. The accuracies of PBLUP and ssGBLUP with the whole dataset varied from 0.45 to 0.75 (average 0.62) and from 0.52 to 0.83 (average 0.71), respectively. The results demonstrate that ssGBLUP performed better than PBLUP averaged over the 10 traits, in terms of prediction accuracy, regardless of considering a partial or whole dataset. Moreover, ssGBLUP generally showed less biased prediction and a value of dispersion closer to 1 than PBLUP across the studied traits. Thus, the ssGBLUP seems to be more suitable for improving the accuracy of predictions for primal cut yields, which can be considered a starting point in future genomic evaluation for these traits in Hanwoo breeding practice. View Full-Text
Keywords: genomic prediction; accuracy; primal cut yields; single-step method; Hanwoo genomic prediction; accuracy; primal cut yields; single-step method; Hanwoo
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MDPI and ACS Style

Naserkheil, M.; Mehrban, H.; Lee, D.; Park, M.N. Evaluation of Genome-Enabled Prediction for Carcass Primal Cut Yields Using Single-Step Genomic Best Linear Unbiased Prediction in Hanwoo Cattle. Genes 2021, 12, 1886. https://doi.org/10.3390/genes12121886

AMA Style

Naserkheil M, Mehrban H, Lee D, Park MN. Evaluation of Genome-Enabled Prediction for Carcass Primal Cut Yields Using Single-Step Genomic Best Linear Unbiased Prediction in Hanwoo Cattle. Genes. 2021; 12(12):1886. https://doi.org/10.3390/genes12121886

Chicago/Turabian Style

Naserkheil, Masoumeh, Hossein Mehrban, Deukmin Lee, and Mi N. Park 2021. "Evaluation of Genome-Enabled Prediction for Carcass Primal Cut Yields Using Single-Step Genomic Best Linear Unbiased Prediction in Hanwoo Cattle" Genes 12, no. 12: 1886. https://doi.org/10.3390/genes12121886

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