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Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle

Author

Listed:
  • Xiaoqiao Wang
  • Jian Miao
  • Tianpeng Chang
  • Jiangwei Xia
  • Binxin An
  • Yan Li
  • Lingyang Xu
  • Lupei Zhang
  • Xue Gao
  • Junya Li
  • Huijiang Gao

Abstract

Chinese Simmental beef cattle are the most economically important cattle breed in China. Estimated breeding values for growth, carcass, and meat quality traits are commonly used as selection criteria in animal breeding. The objective of this study was to evaluate the accuracy of alternative statistical methods for the estimation of genomic breeding values. Analyses of the accuracy of genomic best linear unbiased prediction (GBLUP), BayesB, and elastic net (EN) were performed with an Illumina BovineHD BeadChip on 1,217 animals by applying 5-fold cross-validation. Overall, the accuracies ranged from 0.17 to 0.296 for ten traits, and the heritability estimates ranged from 0.36 to 0.63. The EN (alpha = 0.001) model provided the most accurate prediction, which was also slightly higher (0.2–2%) than that of GBLUP for most traits, such as average daily weight gain (ADG) and carcass weight (CW). BayesB was less accurate for each trait than were EN (alpha = 0.001) and GBLUP. These findings indicate the importance of using an appropriate variable selection method for the genomic selection of traits and suggest the influence of the genetic architecture of the traits we analyzed.

Suggested Citation

  • Xiaoqiao Wang & Jian Miao & Tianpeng Chang & Jiangwei Xia & Binxin An & Yan Li & Lingyang Xu & Lupei Zhang & Xue Gao & Junya Li & Huijiang Gao, 2019. "Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-14, February.
    • Handle: RePEc:plo:pone00:0210442
    DOI: 10.1371/journal.pone.0210442
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    References listed on IDEAS

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    1. Ben J Hayes & Jennie Pryce & Amanda J Chamberlain & Phil J Bowman & Mike E Goddard, 2010. "Genetic Architecture of Complex Traits and Accuracy of Genomic Prediction: Coat Colour, Milk-Fat Percentage, and Type in Holstein Cattle as Contrasting Model Traits," PLOS Genetics, Public Library of Science, vol. 6(9), pages 1-11, September.
    2. Peng Guo & Bo Zhu & Lingyang Xu & Hong Niu & Zezhao Wang & Long Guan & Yonghu Liang & Hemin Ni & Yong Guo & Yan Chen & Lupei Zhang & Xue Gao & Huijiang Gao & Junya Li, 2017. "Genomic prediction with parallel computing for slaughter traits in Chinese Simmental beef cattle using high-density genotypes," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-17, July.
    3. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    4. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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