Accuracies of Genomic Prediction for Growth Traits at Weaning and Yearling Ages in Yak
| Autor: | Wu Xiaoyun, Bao Pengjia, Ping Yan, Fei Ge, Congjun Jia, Chunnian Liang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Withers Bayesian probability Population Best linear unbiased prediction Biology Article 03 medical and health sciences Bayes' theorem Statistics lcsh:Zoology Weaning lcsh:QL1-991 education Genotyping genomic prediction Bayesian approaches yak education.field_of_study lcsh:Veterinary medicine General Veterinary fungi 0402 animal and dairy science 04 agricultural and veterinary sciences YAK 040201 dairy & animal science 030104 developmental biology GBLUP lcsh:SF600-1100 Animal Science and Zoology growth traits genomic estimation of breeding value (GEBV) |
| Zdroj: | Animals, Vol 10, Iss 1793, p 1793 (2020) Animals Volume 10 Issue 10 Animals : an Open Access Journal from MDPI |
| ISSN: | 2076-2615 |
| Popis: | Genomic selection is a promising breeding strategy that has been used in considerable numbers of breeding projects due to its highly accurate results. Yak are rare mammals that are remarkable because of their ability to survive in the extreme and harsh conditions predominantly at the so-called &ldquo roof of the world&rdquo &mdash the Qinghai&ndash Tibetan Plateau. In the current study, we conducted an exploration of the feasibility of genomic evaluation and compared the predictive accuracy of early growth traits with five different approaches. In total, four growth traits were measured in 354 yaks, including body weight, withers height, body length, and chest girth in two early stages of development (weaning and yearling). Genotyping was implemented using the Illumina BovineHD BeadChip. The predictive accuracy was calculated through five-fold cross-validation in five classical statistical methods including genomic best linear unbiased prediction (GBLUP) and four Bayesian methods. Body weights at 30 months in the same yak population were also measured to evaluate the prediction at 6 months. The results indicated that the predictive accuracy for the early growth traits of yak ranged from 0.147 to 0.391. Similar performance was found for the GBLUP and Bayesian methods for most growth traits. Among the Bayesian methods, Bayes B outperformed Bayes A in the majority of traits. The average correlation coefficient between the prediction at 6 months using different methods and observations at 30 months was 0.4. These results indicate that genomic prediction is feasible for early growth traits in yak. Considering that genomic selection is necessary in yak breeding projects, the present study provides promising reference for future applications. |
| Databáze: | OpenAIRE |
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