Antonio Reverter, Yutao Li, Pâmela A. Alexandre, Sonja Dominik, Carel Teseling, Aaron van den Heuvel, Karen Schutt, Matt McDonagh, Laercio Porto-Neto
{"title":"和牛饲养检查:一种基于基因组的工具，用于识别澳大利亚和牛和杂交牛的性能差异","authors":"Antonio Reverter, Yutao Li, Pâmela A. Alexandre, Sonja Dominik, Carel Teseling, Aaron van den Heuvel, Karen Schutt, Matt McDonagh, Laercio Porto-Neto","doi":"10.1071/an23246","DOIUrl":null,"url":null,"abstract":"<strong> Context</strong><p>Wagyu Feeder Check is a genomic-based tool designed to provide genomic estimated breeding values (GEBV) for five feedlot growth and carcase traits. At present, Wagyu Feeder Check is based on a reference population of 8316 genotyped and phenotyped Australian fullblood (FB; <i>N</i> = 2120) Wagyu and Wagyu-crossed (XB; <i>N</i> = 6196) cattle, principally Wagyu × Angus F1 animals.</p><strong> Aims</strong><p>We provide technical details behind the development of the Wagyu Feeder Check and validate the ability of its GEBV to predict differences in performance of Wagyu cattle in daily weight gain at feedlot, carcase weight, carcase eye muscle area, carcase marbling score and carcase rump fat at the P8 site.</p><strong> Methods</strong><p>Data supplied from eight commercial supply chains across Australia was used to generate GEBV using mixed-model equations that incorporated a genomic relationship matrix build with 82 504 autosomal markers. The bias, dispersion, and accuracy of the GEBV were evaluated using a four-way cross-validation scheme where, in each turn, the phenotypes from a random 1549 (or 25%) XB cattle were set as missing.</p><strong> Key results</strong><p>The genomic estimate of the Wagyu content in the FB and XB population averaged 99.12% and 59.55%, respectively, and with most of the non-Wagyu content associated with Angus. The estimates of heritability (± s.e.) were 0.497 ± 0.016, 0.474 ± 0.004, 0.347 ± 0.014, 0.429 ± 0.003 and 0.422 ± 0.003 for daily weight gain at feedlot, carcase weight, eye muscle area, marbling and rump fat, respectively. Averaged across the four XB validation populations, the accuracy of GEBV was 0.624, 0.634, 0.385, 0.620, and 0.526 for the same set of traits.</p><strong> Conclusions</strong><p>Genomic predictions generated by Wagyu Feeder Check can predict differences in feedlot and carcase performance of Australian Wagyu cattle. Given the large content of Angus in the XB population, further research is required to determine the predictive ability of GEBV in Wagyu × <i>Bos indicus</i> and Wagyu × dairy animals.</p><strong> Implications</strong><p>Commercial feedlot operators finishing animals with a strong Wagyu breed component will benefit from using Wagyu Feeder Check for decision making.</p>","PeriodicalId":7895,"journal":{"name":"Animal Production Science","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wagyu Feeder Check: A genomic-based tool to identify performance differences of Australian Wagyu and Wagyu crossed cattle\",\"authors\":\"Antonio Reverter, Yutao Li, Pâmela A. 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At present, Wagyu Feeder Check is based on a reference population of 8316 genotyped and phenotyped Australian fullblood (FB; <i>N</i> = 2120) Wagyu and Wagyu-crossed (XB; <i>N</i> = 6196) cattle, principally Wagyu × Angus F1 animals.</p><strong> Aims</strong><p>We provide technical details behind the development of the Wagyu Feeder Check and validate the ability of its GEBV to predict differences in performance of Wagyu cattle in daily weight gain at feedlot, carcase weight, carcase eye muscle area, carcase marbling score and carcase rump fat at the P8 site.</p><strong> Methods</strong><p>Data supplied from eight commercial supply chains across Australia was used to generate GEBV using mixed-model equations that incorporated a genomic relationship matrix build with 82 504 autosomal markers. The bias, dispersion, and accuracy of the GEBV were evaluated using a four-way cross-validation scheme where, in each turn, the phenotypes from a random 1549 (or 25%) XB cattle were set as missing.</p><strong> Key results</strong><p>The genomic estimate of the Wagyu content in the FB and XB population averaged 99.12% and 59.55%, respectively, and with most of the non-Wagyu content associated with Angus. The estimates of heritability (± s.e.) were 0.497 ± 0.016, 0.474 ± 0.004, 0.347 ± 0.014, 0.429 ± 0.003 and 0.422 ± 0.003 for daily weight gain at feedlot, carcase weight, eye muscle area, marbling and rump fat, respectively. Averaged across the four XB validation populations, the accuracy of GEBV was 0.624, 0.634, 0.385, 0.620, and 0.526 for the same set of traits.</p><strong> Conclusions</strong><p>Genomic predictions generated by Wagyu Feeder Check can predict differences in feedlot and carcase performance of Australian Wagyu cattle. 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Wagyu Feeder Check: A genomic-based tool to identify performance differences of Australian Wagyu and Wagyu crossed cattle
Context
Wagyu Feeder Check is a genomic-based tool designed to provide genomic estimated breeding values (GEBV) for five feedlot growth and carcase traits. At present, Wagyu Feeder Check is based on a reference population of 8316 genotyped and phenotyped Australian fullblood (FB; N = 2120) Wagyu and Wagyu-crossed (XB; N = 6196) cattle, principally Wagyu × Angus F1 animals.
Aims
We provide technical details behind the development of the Wagyu Feeder Check and validate the ability of its GEBV to predict differences in performance of Wagyu cattle in daily weight gain at feedlot, carcase weight, carcase eye muscle area, carcase marbling score and carcase rump fat at the P8 site.
Methods
Data supplied from eight commercial supply chains across Australia was used to generate GEBV using mixed-model equations that incorporated a genomic relationship matrix build with 82 504 autosomal markers. The bias, dispersion, and accuracy of the GEBV were evaluated using a four-way cross-validation scheme where, in each turn, the phenotypes from a random 1549 (or 25%) XB cattle were set as missing.
Key results
The genomic estimate of the Wagyu content in the FB and XB population averaged 99.12% and 59.55%, respectively, and with most of the non-Wagyu content associated with Angus. The estimates of heritability (± s.e.) were 0.497 ± 0.016, 0.474 ± 0.004, 0.347 ± 0.014, 0.429 ± 0.003 and 0.422 ± 0.003 for daily weight gain at feedlot, carcase weight, eye muscle area, marbling and rump fat, respectively. Averaged across the four XB validation populations, the accuracy of GEBV was 0.624, 0.634, 0.385, 0.620, and 0.526 for the same set of traits.
Conclusions
Genomic predictions generated by Wagyu Feeder Check can predict differences in feedlot and carcase performance of Australian Wagyu cattle. Given the large content of Angus in the XB population, further research is required to determine the predictive ability of GEBV in Wagyu × Bos indicus and Wagyu × dairy animals.
Implications
Commercial feedlot operators finishing animals with a strong Wagyu breed component will benefit from using Wagyu Feeder Check for decision making.
期刊介绍：
Research papers in Animal Production Science focus on improving livestock and food production, and on the social and economic issues that influence primary producers. The journal (formerly known as Australian Journal of Experimental Agriculture) is predominantly concerned with domesticated animals (beef cattle, dairy cows, sheep, pigs, goats and poultry); however, contributions on horses and wild animals may be published where relevant.
Animal Production Science is published with the endorsement of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the Australian Academy of Science.
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