Partition of the genetic trend to validate multiple selection decisions

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics

Background:

• Understanding genetic gain is crucial for effective animal breeding programs.
• Attributing genetic gain to specific selection strategies can be complex.
• Existing methods may not fully disentangle contributions from different parental groups or policies.

Purpose of the Study:

• To introduce a novel procedure for partitioning the genetic trend in selected populations.
• To enable the accurate allocation of genetic gain to different groups of animals and selection policies.
• To provide a tool for evaluating the impact of specific breeding interventions, such as artificial insemination.

Main Methods:

• The method involves a straightforward transformation of predicted breeding values.
• It partitions the overall genetic gain by accounting for Mendelian sampling terms.
• The procedure is demonstrated using simulated data for validation.

Main Results:

• The genetic trend can be successfully partitioned into components attributable to different selection sources (e.g., sires vs. dams).
• The approach allows for the quantification of genetic gain derived from specific selection policies.
• The impact of entities like artificial insemination centers on population genetic gain can be assessed.

Conclusions:

• This procedure offers a robust way to dissect genetic gain, enhancing the understanding of breeding program dynamics.
• It facilitates more precise evaluation of selection efficiency and the effectiveness of different breeding strategies.
• The method supports data-driven decision-making in animal genetics and breeding.