Genomic predictions for crossbred dairy cattle

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Dairy Science

Background:

• Genomic evaluations are crucial for both purebred and crossbred populations in commercial dairy farming.
• Dairy farmers invested heavily in genotyping crossbred animals before official genomic evaluations were available, necessitating new prediction tools.
• Accurate imputation of genotypes for crossbred animals requires a reference population that includes purebreds.

Purpose of the Study:

• To develop and validate accurate genomic prediction methods for crossbred dairy cattle.
• To assess the accuracy of genomic predictions using breed base representation (BBR) weighting.
• To compare the performance of crossbred genomic predictions against traditional methods.

Main Methods:

• Imputed genotypes for 6,296 crossbred animals using reference populations of either 3,119 ancestors or 834,367 genotyped animals.
• Estimated genomic breed composition from 60,671 markers, adjusting percentages to derive breed base representation (BBR).
• Calculated crossbred genomic predictions as averages of pure breed marker effects weighted by BBR, with effects estimated on an all-breed scale.

Main Results:

• Genomic predictions weighted by BBR were more accurate for crossbreds than the average of parents' breeding values.
• BBR-weighted predictions were also slightly more accurate than predictions using only the predominant breed's information.
• For purebreds, single-trait predictions were as accurate as multi-trait predictions when allele effects were treated as correlated across breeds.

Conclusions:

• The developed method provides accurate genomic predictions for crossbred dairy cattle.
• Breed base representation (BBR) weighting enhances the accuracy of genomic selection in crossbred populations.
• The implementation of crossbred genomic predicted transmitting abilities aids producers in breeding program management and heifer selection.