Improving genomic prediction for two Yorkshire populations with a limited size using the single-step method

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Genomic Selection

Background:

• Limited population size in purebred pig breeding farms can hinder genetic gain.
• Accurate genomic prediction is crucial for efficient selection in swine.
• Yorkshire pigs in China represent a valuable population for study.

Purpose of the Study:

• To evaluate the effectiveness of genomic prediction strategies in small, purebred pig populations.
• To compare single-population and joint two-population genomic prediction methods.
• To assess the impact on growth (AGE) and reproduction (TNB) traits.

Main Methods:

• Utilized four prediction strategies: one-population BLUP, joint two-population BLUP, one-population SSBLUP, and joint two-population SSBLUP.
• Analyzed two growth traits (age at 100kg, back-fat thickness at 100kg) and one reproduction trait (total number of piglets born).
• Applied methods to two distinct Yorkshire purebred populations (Yichun and Chifeng) in China.

Main Results:

• Genomic prediction (SSBLUP methods) improved prediction accuracies for back-fat thickness (BF) and total number of piglets born (TNB) in the Yichun population.
• BF prediction accuracy also improved in the Chifeng population.
• TNB accuracy in Yichun doubled with one-population SSBLUP versus one-population BLUP; prediction biases were reduced for AGE and TNB.

Conclusions:

• Genomic prediction is a valuable tool for enhancing prediction accuracy in purebred pig breeding programs with limited population sizes.
• Joint genomic prediction across genetically linked populations offers potential for further accuracy improvements.
• These findings support the implementation of advanced genomic selection strategies in swine breeding.