دورية أكاديمية
Genomic prediction and genetic correlations estimated for milk production and fatty acid traits in Walloon Holstein cattle using random regression models.
| العنوان: | Genomic prediction and genetic correlations estimated for milk production and fatty acid traits in Walloon Holstein cattle using random regression models. |
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| المؤلفون: | Paiva, José Teodoro, Mota, Rodrigo Reis, Lopes, Paulo Sávio, Hammami, Hedi, Vanderick, Sylvie, Oliveira, Hinayah Rojas, Veroneze, Renata, Silva, Fabyano Fonseca E, Gengler, Nicolas |
| المصدر: | Journal of Dairy Research, 89 (3), 1 - 9 (2022-09-05) |
| بيانات النشر: | Cambridge University Press, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Genetic correlation, MIR, genomic prediction, single-step GBLUP, test-day model, Food Science, Animal Science and Zoology, General Medicine, Life sciences, Animal production & animal husbandry, Genetics & genetic processes, Sciences du vivant, Productions animales & zootechnie, Génétique & processus génétiques |
| الوصف: | The aims of this study were to: (1) estimate genetic correlation for milk production traits (milk, fat and protein yields and fat and protein contents) and fatty acids (FA: C16:0, C18:1 cis-9, LCFA, SFA, and UFA) over days in milk, (2) investigate the performance of genomic predictions using single-step GBLUP (ssGBLUP) based on random regression models (RRM), and (3) identify the optimal scaling and weighting factors to be used in the construction of the H matrix. A total of 302 684 test-day records of 63.875 first lactation Walloon Holstein cows were used. Positive genetic correlations were found between milk yield and fat and protein yield (rg from 0.46 to 0.85) and between fat yield and milk FA (rg from 0.17 to 0.47). On the other hand, negative correlations were estimated between fat and protein contents (rg from -0.22 to -0.59), between milk yield and milk FA (rg from -0.22 to -0.62), and between protein yield and milk FA (rg from -0.11 to -0.19). The selection for high fat content increases milk FA throughout lactation (rg from 0.61 to 0.98). The test-day ssGBLUP approach showed considerably higher prediction reliability than the parent average for all milk production and FA traits, even when no scaling and weighting factors were used in the H matrix. The highest validation reliabilities (r2 from 0.09 to 0.38) and less biased predictions (b1 from 0.76 to 0.92) were obtained using the optimal parameters (i.e., ω = 0.7 and α = 0.6) for the genomic evaluation of milk production traits. For milk FA, the optimal parameters were ω = 0.6 and α = 0.6. However, biased predictions were still observed (b1 from 0.32 to 0.81). The findings suggest that using ssGBLUP based on RRM is feasible for the genomic prediction of daily milk production and FA traits in Walloon Holstein dairy cattle. |
| نوع الوثيقة: | journal article http://purl.org/coar/resource_type/c_6501 article peer reviewed |
| اللغة: | English |
| Relation: | https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022029922000474; urn:issn:0022-0299; urn:issn:1469-7629 |
| DOI: | 10.1017/S0022029922000474 |
| URL الوصول: | https://orbi.uliege.be/handle/2268/303837 |
| حقوق: | open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
| رقم الأكسشن: | edsorb.303837 |
| قاعدة البيانات: | ORBi |
| DOI: | 10.1017/S0022029922000474 |
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