Genomic predictions under different genetic architectures are impacted by mating designs

Area of Science:

• Animal genetics and breeding
• Genomic selection
• Quantitative genetics

Background:

• Managing animal mating is crucial for progeny performance and controlling inbreeding.
• Genome-wide marker profiles, including millions of single nucleotide polymorphisms (SNPs), enable advanced animal selection.
• Understanding the impact of different mating designs on genomic prediction accuracy is essential for optimizing breeding programs.

Purpose of the Study:

• To evaluate the effect of five distinct mating designs (random, positive assortative, negative assortative, minimized inbreeding, maximized inbreeding) on genomic prediction accuracy.
• To analyze how genetic diversity, relatedness, and inbreeding influence genomic prediction accuracy under various conditions.
• To determine the optimal mating strategy for unbiased and accurate genomic predictions in animal breeding.

Main Methods:

• A stochastic simulation technique was employed to model various scenarios.
• Simulations considered different marker and quantitative trait loci (QTL) densities, and heritabilities (0.05, 0.30, 0.60).
• Genomic prediction accuracy was assessed by correlating estimated and true breeding values, and prediction bias was examined using regression coefficients.

Main Results:

• Positive assortative mating yielded the highest genomic prediction accuracy (0.733 ± 0.003 to 0.966 ± 0.001).
• Negative assortative mating resulted in the lowest genomic evaluation accuracy (0.680 ± 0.011 to 0.899 ± 0.003).
• Positive assortative mating produced unbiased regression coefficients, indicating accurate genomic breeding value estimation.

Conclusions:

• Implementing positive assortative mating in genomic evaluation programs is recommended for achieving accurate and unbiased genomic predictions.
• Careful management of mating strategies based on genetic diversity and inbreeding levels can enhance offspring performance without compromising genetic health.
• Considering diverse mating designs is vital for maximizing breeding outcomes and ensuring long-term genetic improvement in animal populations.