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The effect of prior distributions of different statistical models on the accuracy of genomic prediction: simulation study

Document Type : Research Paper

Authors

1 Assistant professor, Department of Animal Science, Faculty of Agriculture, Ilam University, Ilam, Iran

2 Animal Science Research Department, Kermanshah Agriculture and Natural Resources Research and Education Center, Kermanshah, Iran.

3 Animal Science Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

Abstract

In the genomic selection, SNP markers across whole genome are used to estimate the marker effects. Genomic breeding value of animals can be predicted by different statistical methods. Genomic breeding value of animals can be predicted by different statistical methods. In the present study, accuracies of the predicted direct genomic breeding values were compared under several statistical models including Bayes A, B-LASSO gamma, B-LASSO beta and BGLR by considering two heritabilities of 0.3 and 0.05. Three values of π (0.1, 0.3, and 0.5) and four values of s2 (0.01, 0.1, 10, and 100) were simulated and correspondingly evaluated in terms of accuracy. The obtained results showed the highest accuracy of direct genomic breeding value was obtained under Bayes-A method, which were 0.88 and 0.69 for heritabilities of 0.3 and 0.05, respectively. Regression coefficients of methods for estimating the marker effects were more unbiased under heritability of 0.3 than 0.05. By considering the heritability of 0.3, the lowest and highest error were obtained under Bayes-A (121.2) and B-LASSO beta (165.2) methods, respectively. Under BGLR method, the highest and lowest accuracy of Bayes-A were obtained for π, 0.5 (0.81) and π, 0.1 (0.45). By increasing s2 parameter a decrease in the accuracy of genomic predictions was obtained. The obtained results suggested that to maximize the accuracy of the genetic prediction for traits with moderate to high heritability (0.3) optimal point of parameter π may ranged from 0.41 to 0.56 and while for traits with low heritability from 0.56 to 0.73.

Keywords

References
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Zhang, H., Yin, L., Wang, M., Yuan, X.,  and Liu X. (2019). Factors Affecting the Accuracy of Genomic Selection for Agricultural Economic Traits in Maize, Cattle, and Pig Populations. Frontiers in Genetics. 10: 180-189.

Research Journal of Livestock Science
Volume 34, Issue 130
June 2021
Pages 191-202
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