Genomic prediction of breed composition and heterosis effects in angus, charolais, and hereford crosses using 50k genotypes

Citation

Akanno, E.C., Chen, L., Abo-Ismail, M.K., Crowley, J.J., Wang, Z., Li, C., Basarab, J.A., Macneil, M.D., Plastow, G. (2017). Genomic prediction of breed composition and heterosis effects in angus, charolais, and hereford crosses using 50k genotypes. Canadian Journal of Animal Science, [online] 97(3), 431-438. http://dx.doi.org/10.1139/cjas-2016-0124

Plain language summary

Crossbreeding is a common practice in beef production. Therefore, it is important to know the breed composition in a herd in order to maximize hybrid vigor or heterosis, an increase of performance of hybrids over purebreds. Breed composition of an animal can be estimated based on its pedigree record. However, pedigree records may not be available or may not be completed. In this study, we used DNA markers, i.e. 42,610 single nucleotide polymorphism (SNP) marker genotypes, to predict an individual animal’s breed composition and its heterosis in a population of 1,124 crossbred beef cattle, and compared the predicted breed composition and heterosis with those estimated from pedigree. The results showed that average breed composition of the crossbred cattle were 0.52 Angus, 0.23 Charolais and 0.25 Hereford based on pedigree analyses and were 0.46, 0.26, 0.28 based on the SNP marker based prediction. Therefore, the breed compositions predicted based on the SNP markers and based on pedigree were similar. The retained heterozygosity, i. e. the proportion of genes with different forms/alleles, and retained heterosis from pedigree and from the SNP marker analyses were also highly correlated or similar, and significant heterosis was observed for growth traits in the crossbred cattle population. The research showed to the industry that the genomic analyses based on SNP marker genotypes of a medium density can serve as a reliable method to predict breed composition and heterosis to improve the efficiency of commercial crossbreeding schemes.

Abstract

This study examined the feasibility and accuracy of using Illumina BovineSNP50 genotypes to estimate individual cattle breed composition and heterosis relative to estimate from pedigree. First, pedigree was used to compute breed fractions for 1124 crossbred cattle. Given the breed composition of sires and dams, retained heterosis and retained heterozygosity were computed for all individuals. Second, all animals’ genotypes were used to compute individual’s genomic breed fractions by applying a cross-validation method. Average genome-wide heterozygosity and retained heterozygosity based on genomic breed fraction were computed. Lastly, accuracies of breed composition, retained heterozygosity and retained heterosis were assessed as Pearson’s correlation between pedigree-and genome-based predictions. The average breed compositions observed were 0.52 Angus, 0.23 Charolais, and 0.25 Hereford for pedigree-based prediction and 0.46, 0.26, and 0.28 for genome-based prediction, respectively. Correlations of predicted breed composition ranged from 0.94 to 0.96. Genome-based retained heterozygosity and retained heterosis from pedigree were also highly correlated (0.96). A positive association of nonadditive genetic effects was observed for growth traits reflecting the importance of heterosis for these traits. Genomic prediction can aid analyses that depend on knowledge of breed composition and serve as a reliable method to predict heterosis to improve the efficiency of commercial crossbreeding schemes.

Publication date

2017-09-01

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