Invited review: Genomic selection in dairy cattle: progress and challenges

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Breeding Technology

Background:

• Genomic selection (GS) utilizes genomic breeding values (GEBV) for dairy cattle breeding decisions.
• GEBV are calculated from dense genetic markers across the genome, potentially capturing all quantitative trait loci (QTL).

Purpose of the Study:

• To evaluate the reliability of GEBV predictions in dairy cattle.
• To compare GEBV reliability with traditional breeding value estimation methods.

Main Methods:

• Estimation of QTL effects using dense genetic markers in large reference populations with phenotypic data.
• Calculation of GEBV for young bulls using only marker information.
• Evaluation of GEBV reliability across multiple countries (US, NZ, Australia, Netherlands).

Main Results:

• GEBV reliabilities for young bulls ranged from 20-67%, influenced by trait heritability and reference population size.
• A simple BLUP method for marker effect estimation yielded reliabilities comparable to more complex methods.
• GEBV reliabilities significantly exceeded those of parental average breeding values.

Conclusions:

• Genomic selection significantly increases the reliability of breeding value prediction in dairy cattle.
• This technology enables faster genetic gain, potentially doubling the rate of genetic improvement.
• Implementation challenges include enhancing GEBV accuracy and integrating genomic data into broader genetic evaluations.