Mating programs including genomic relationships and dominance effects.

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Genomic Selection

Background:

• Breed associations and AI organizations require advanced mating programs leveraging genomic data.
• Existing software faces challenges with the computational demands of large genomic relationship matrices.
• Efficient data management and transfer are crucial for disseminating genomic predictions to customers.

Purpose of the Study:

• To investigate sire selection, mate assignment methods, and the impact of genomic versus pedigree relationships in mating programs.
• To evaluate the effect of including genetic dominance on mating program outcomes.
• To compare different mating strategies for optimizing expected progeny value and managing inbreeding.

Main Methods:

• Utilized genomic and pedigree relationship data for three cattle breeds (Holsteins, Jerseys, Brown Swiss).
• Tested sire selection and mating programs using top-marketed and randomly selected bulls.
• Employed linear programming for mate assignment and estimated dominance variance using marker data.

Main Results:

• Sire selection was the most critical factor for improving progeny value, followed by inbreeding management and dominance effects.
• Genomic relationships led to greater reductions in expected progeny inbreeding and higher progeny value compared to pedigree relationships.
• Linear programming outperformed sequential selection in reducing inbreeding by up to 1.41%.

Conclusions:

• Optimizing sire selection, managing inbreeding, and incorporating dominance are key to maximizing genetic gains in cattle.
• Genomic relationships offer substantial economic advantages over pedigree data in mating programs.
• Enhanced mating services incorporating genomic data, precise allocation, and dominance effects provide greater economic benefits.