Modeling heterotic effects in beef cattle using genome-wide SNP-marker genotypes


Akanno, E.C., Abo-Ismail, M.K., Chen, L., Crowley, J.J., Wang, Z., Li, C., Basarab, J.A., MacNeil, M.D., Plastow, G.S. (2018). Modeling heterotic effects in beef cattle using genome-wide SNP-marker genotypes. Journal of Animal Science, [online] 96(3), 830-845.

Plain language summary

Heterosis or hybrid vigor refers to enhanced performance of offspring as a result of mixing the genetic contributions of its parents. In beef cattle, heterosis is achieved through crossing beef cattle of different breeds, and it is expected that animals with positive heterosis have better performance than the average of their parents, i.e. better than the mid-parent value. In this study, we used dense DNA makers or 50,000 single nucleotide polymorphisms (SNP) markers to assess breed composition of each animal, and to predict retained heterozygosity as well as heterosis effects for growth and carcass traits for a total of 6,794 multi-breed and crossbred Canadian beef cattle. The results showed that positive heterotic effects existed for growth traits but not for carcass traits which reflect the importance of heterosis for growth traits in beef cattle. In addition, the results showed that inclusion of predicted heterosis in genetic or genomic evaluation would improve the accuracy of genetic evaluation up to 20% for some traits, which allows more reliable selection of breeding stocks with superior genetics. The results will help optimize crossbreeding programs to improve growth of beef cattle as well as will benefit genetic evaluation and selection in beef cattle.


An objective of commercial beef cattle crossbreeding programs is to simultaneously optimize use of additive (breed differences) and non-additive (heterosis) effects. A total of 6,794 multibreed and crossbred beef cattle with phenotype and Illumina BovineSNP50 genotype data were used to predict genomic heterosis for growth and carcass traits by applying two methods assumed to be linearly proportional to heterosis. The methods were as follows: 1) retained heterozygosity predicted from genomic breed fractions (HET1) and 2) deviation of adjusted crossbred phenotype from midparent value (HET2). Comparison of methods was based on prediction accuracy from cross-validation. Here, a mutually exclusive random sampling of all crossbred animals (n = 5,327) was performed to form five groups replicated five times with approximately 1,065 animals per group. In each run within a replicate, one group was assigned as a validation set, while the remaining four groups were combined to form the reference set. The phenotype of the animals in the validation set was assumed to be unknown; thus, it resulted in every animal having heterosis values that were predicted without using its own phenotype, allowing their adjusted phenotype to be used for validation. The same approach was used to test the impact of predicted heterosis on accuracy of genomic breeding values (GBV). The results showed positive heterotic effects for growth traits but not for carcass traits that reflect the importance of heterosis for growth traits in beef cattle. Heterosis predicted by HET1 method resulted in less variable estimates that were mostly within the range of estimates generated by HET2. Prediction accuracy was greater for HET2 (0.37– 0.98) than HET1 (0.34–0.43). Proper consideration of heterosis in genomic evaluation models has debatable effects on accuracy of EBV predictions. However, opportunity exists for predicting heterosis, improving accuracy of genomic selection, and consequently optimizing crossbreeding programs in beef cattle.

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