Genome-Wide Association Analysis of Boar Semen Traits Based on Computer-Assisted Semen Analysis and Flow Cytometry

Area of Science:

• Animal Genetics
• Reproductive Biology
• Quantitative Genetics

Background:

• Semen quality is crucial for artificial insemination (AI) in pig breeding.
• Evaluating individual boar fertility impacts breeding program efficiency and economic outcomes.

Purpose of the Study:

• To conduct Genome-Wide Association Studies (GWAS) on key semen traits in Duroc boars.
• To identify genetic variants and candidate genes influencing sperm quality and persistence.

Main Methods:

• Assessed semen traits (motility, density, abnormality, mitochondrial membrane potential, acrosome integrity, reactive oxygen species) using Flow Cytometry (FCM) and Computer-Assisted Sperm Analysis (CASA).
• Genotyped 1183 Duroc boars using the GeneSeek GGP Porcine 50 K SNP BeadChip.
• Performed GWAS using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU methods.
• Estimated heritability using single- and multiple-trait PBLUP models.

Main Results:

• Identified low heritability for most semen traits (MOT, DEN, MMP, AIR, ROS), with medium heritability for abnormality (ABN).
• Detected nine candidate genes (e.g., GPX5, AWN, PSP-II) potentially associated with semen traits.
• These genes are implicated in antioxidant and mitochondrial functions within porcine sperm.

Conclusions:

• The study elucidates the genetic architecture of semen traits in Duroc boars.
• Identified SNPs and candidate genes offer potential for enhancing pig breeding economic outcomes.
• Findings support targeted breeding strategies to improve porcine sperm quality.