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

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Animal Breeding

Background:

• Optimizing beef cattle crossbreeding requires balancing additive (breed differences) and non-additive (heterosis) genetic effects.
• Genomic selection offers potential for predicting heterosis and improving breeding program efficiency.

Purpose of the Study:

• To predict genomic heterosis for growth and carcass traits in beef cattle using two distinct methods.
• To compare the prediction accuracy of two methods for estimating genomic heterosis.
• To evaluate the impact of predicted heterosis on the accuracy of genomic breeding values (GBV).

Main Methods:

• Utilized phenotype and genotype data from 6,794 multibreed and crossbred beef cattle.
• Applied two methods to predict genomic heterosis: retained heterozygosity from genomic breed fractions (HET1) and phenotype deviation from midparent value (HET2).
• Employed a cross-validation strategy with a reference set and a validation set to assess prediction accuracy.

Main Results:

• Positive heterotic effects were observed for growth traits, but not for carcass traits.
• The HET2 method yielded higher prediction accuracy (0.37-0.98) compared to the HET1 method (0.34-0.43).
• HET1 estimates showed less variability and were generally within the range of HET2 estimates.

Conclusions:

• Heterosis is important for growth traits in beef cattle, with potential for genomic prediction.
• The HET2 method is more accurate for predicting genomic heterosis than HET1.
• Incorporating predicted heterosis into genomic evaluation models may enhance accuracy and optimize crossbreeding strategies.