Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data.

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Statistical Genomics

Background:

• Genome-wide association studies (GWAS) face challenges with significance testing due to strong linkage disequilibrium (LD) and population stratification, especially with increasing SNP density up to whole-genome sequence (WGS) data.
• Accurate significance testing is crucial for identifying genetic variants associated with traits in livestock breeding programs.

Purpose of the Study:

• To investigate genomic control and evaluate different significance testing procedures for GWAS in a commercial pig breeding scheme.
• To assess the impact of SNP density and population stratification correction methods on genomic inflation factors.
• To recommend appropriate significance thresholds for different genetic discovery goals in pigs.

Main Methods:

• Genome-wide association study (GWAS) performed using GCTA software on 4,964 Large White pigs with medium, high-density, or imputed whole-genome sequence data.
• A leave-one-chromosome-out genomic relationship matrix was fitted to account for population structure.
• Genomic inflation factors were assessed, and significance thresholds were evaluated using permutation testing, Bonferroni corrections, and False Discovery Rate (FDR) methods (Benjamini-Hochberg and Benjamini-Yekutieli).

Main Results:

• Genomic inflation factors varied between chromosomes but not between different genotype densities.
• Neither the leave-one-chromosome-out approach nor pedigree relationships adequately corrected for population stratification, resulting in significant genomic inflation.
• The Benjamini-Yekutieli FDR procedure was recommended for identifying quantitative trait loci (QTL) regions, while Bonferroni correction based on total SNPs was suggested for pinpointing specific mutations.

Conclusions:

• Standard methods for population stratification correction in GWAS may be insufficient, leading to inflated genomic control.
• The Benjamini-Yekutieli FDR approach provides a robust significance threshold for QTL discovery in pig GWAS.
• Bonferroni correction remains a conservative choice for identifying specific causal mutations until more refined methods are available.