Comparison of molecular breeding values based on within- and across-breed training in beef cattle

Abstract

Background: Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported.

Methods: Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype.

Results: With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero.

Conclusions: Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.

Figure 1

Box plots of estimated genetic correlations between phenotypic traits and within-breed trained MBV. MBV were evaluated either in the same breed used for training or in a different breed. Training excluded animals in the pedigrees of the field data evaluation population bulls.

Figure 2

Estimated genetic correlations and their standard errors between phenotypic traits and within-breed trained MBV. Traits were weaning weight (WWT) and yearling weight (YWT) and were evaluated in Angus (AN), Hereford (HH), or Limousin (LM).Within-breed trained MBV were evaluated in the same breed as used in training.

Figure 3

Scatter plots of within-breed trained MBV against across-breed trained MBV for weaning weight. Within-breed MBV trained in Angus (AN), Hereford (HH), and Limousin (LM) and evaluated in animals in the field data set of either the same or different breed.

Figure 4

Scatter plots of within-breed trained MBV against across-breed trained MBV for yearling weight. Within-breed MBV trained in Angus (AN), Hereford (HH), and Limousin (LM) and evaluated in animals in the field data set of either the same or different breed.