Optimization of dairy cattle breeding programs for different environments with genotype by environment interaction.

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Agricultural Science

Background:

• Dairy cattle breeding organizations distribute semen globally, necessitating consideration of genotype x environment (GxE) interactions.
• GxE interactions can significantly impact genetic gain and breeding program effectiveness across diverse environments.

Purpose of the Study:

• To investigate and optimize dairy cattle breeding programs considering GxE interactions across two distinct environments.
• To evaluate different breeding strategies based on genetic gain in multiple environments.

Main Methods:

• Simulated breeding strategies involving single or dual breeding programs and progeny testing in one or two environments.
• Utilized a pseudo-BLUP selection index model to predict average genetic gain across environments.
• Assessed the impact of genetic correlation, heritability, progeny number, environmental importance, and selection intensity.

Main Results:

• A single breeding program with progeny testing in both environments maximized genetic gain when environments were equally important and genetic correlation exceeded 0.61.
• Two environment-specific breeding programs were optimal when genetic correlation was below 0.61.
• Differences in average genetic gain between strategies ranged from 2% to 12% for genetic correlations between 0.50 and 1.00.

Conclusions:

• The optimal breeding strategy is sensitive to the genetic correlation between environments and selection intensity.
• Environment-specific breeding programs are advantageous under lower genetic correlations or higher selection intensity.
• Findings provide guidelines for optimizing global dairy cattle breeding programs by accounting for GxE interactions.