Selective sweep analysis reveals extensive parallel selection traits between large white and Duroc pigs.

Area of Science:

• Animal Genetics
• Genomics
• Quantitative Trait Genetics

Background:

• Commercial pig breeds like Danish Large White and Duroc are bred for meat production.
• Parallel selection, where different breeds undergo similar selection pressures for economic traits (e.g., growth, fertility), is common in pig genetic improvement.
• Understanding parallel selection is crucial for optimizing breeding strategies.

Purpose of the Study:

• To investigate the signatures of parallel selection in Danish Large White and Duroc pigs.
• To identify candidate genes and genomic regions associated with parallel selection.
• To explore breed-specific selection signatures and their genetic underpinnings.

Main Methods:

• Whole-genome sequencing of 28 Danish Large White pigs, 27 Duroc pigs, and 23 European wild boars.
• Identification of approximately 12 million high-quality single nucleotide polymorphisms (SNPs) per individual.
• Analysis of parallel selection using population genetics methods: Fst and integrated haplotype score (iHS).

Main Results:

• Identified 67 candidate genomic regions showing signatures of parallel selection between Danish Large White and Duroc pigs.
• Genes within these regions are predominantly associated with sensory perception, growth rate, and body size.
• Functional annotation suggests a polygenic basis for quantitative traits contributing to parallel selection consistency.
• Discovered breed-specific selection regions, such as limb development-related terms enriched in Duroc pigs, indicating unique trait selection.

Conclusions:

• Parallel selection in pigs is driven by shared genetic bases for quantitative traits, influencing growth and sensory perception.
• Breed-specific selection signatures highlight unique evolutionary paths and trait focuses in different pig breeds.
• The identified candidate regions and SNPs provide valuable targets for future pig genetic breeding programs and understanding selection processes.