Use of field data in pig genomic selection schemes: a simulation study

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Swine Production Systems

Background:

• Genomic selection (GS) is a powerful tool in animal breeding.
• Accurate genetic gain relies on comprehensive phenotypic and genotypic data.
• Optimizing data collection strategies is crucial for breeding schemes.

Purpose of the Study:

• To evaluate methods for increasing genetic gain in pig breeding schemes for traits not directly measured on nucleus animals.
• To assess the impact of using offspring phenotypes and genotyping production animals within a genomic selection framework.
• To compare different data recording and genotyping strategies for their effectiveness in enhancing genetic gain.

Main Methods:

• Stochastic simulation of a multi-tier pig breeding program (nucleus, multiplier, production).
• Testing three strategies: offspring phenotypic records, genotyping production animals, and a combined approach.
• Evaluating genetic gain under varying economic weights for the trait of interest.

Main Results:

• No significant effect on genetic gain for traits with low economic value (10% of breeding goal).
• A combined strategy (offspring records + genotyping production animals) was most effective for traits with higher economic value (30% of breeding goal).
• Phenotypic records from offspring of nucleus animals had a greater impact than genotyping distant relatives.

Conclusions:

• For traits with high economic importance, combining offspring data and genotyping production animals maximizes genetic gain in genomic selection programs.
• If offspring records from nucleus animals are unavailable, genotyping production animals is a viable strategy for high-value traits.
• The effectiveness of different genomic selection strategies is dependent on the economic significance of the trait.