Bovine respiratory disease (BRD) causes major losses in feedlot cattle worldwide. A genetic component for BRD resistance in feedlot cattle and calves has been reported in a number of studies, with heritabilities ranging from 0.04 to 0.2. These results suggest selection could be used to reduce the incidence of BRD. Genomic selection could be an attractive approach for breeding for BRD resistance, given the phenotype is not likely to be recorded on breeding animals. In this study, we derived GEBVs for BRD resistance and assessed their accuracy in a reasonably large data set recorded for feedlot treatment of BRD (1213 Angus steers, in two feedlots). In fivefold cross validation, genomic predictions were moderately accurate (0.23 ± 0.01) when a BayesR approach was used. Expansion of this approach to include more animals and a diversity of breeds is recommended to successfully develop a GEBV for BRD resistance in feedlots for the beef industry.
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http://dx.doi.org/10.1093/jas/skae113 | DOI Listing |
Nature
December 2024
CatalYm, Munich, Germany.
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Department of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
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Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Kolkata, West Bengal 700054, India. Electronic address:
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Department of Veterinary Biomedical Sciences, College of Veterinary Medicine, Long Island University, 720 Northern Boulevard, Brookville, NY, 11548, USA.
Proc Natl Acad Sci U S A
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Laboratory of Protein Engineering and Vaccines, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.
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