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.
Highlights
Chinese Simmental beef cattle play an important role in the Chinese beef industry because of their high adaptability and the rapid growth of their young with sufficient feeding
We suggest that average daily weight gain (ADG), carcass weight (CW), eye muscle area (EMA) and marbling score (MS) traits are suitable for the infinitesimal model, as these traits have small effects distributed on many loci
The results showed that genomic best linear unbiased prediction (GBLUP) and elastic net (EN) were clearly superior to BayesB for each trait, LW and carcass length (CL)
Summary
Chinese Simmental beef cattle play an important role in the Chinese beef industry because of their high adaptability and the rapid growth of their young with sufficient feeding. The beef is well marbled and tender, contributing to its marketability. Estimated breeding values of economical traits, such as carcass weight (CW), eye muscle area (EMA), and marbling score (MS), are generally considered to be the major selection criteria in beef cattle breeding. The average daily weight gain (ADG) is important as an indicator of growth. In China, small holders manage a large proportion of young bulls, in some cases keeping fewer than 100 cattle. Considering this situation, these bulls cannot be managed well.
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