Abstract
Several methods are available for genome-wide association analysis, including the classical GWAA (cGWAA) based on fixed, single-SNP regression; efficient mixed-model association expedited (EMMAX) that fits single-SNP regressions together with a relationship matrix to account for population structure; and single-step GWAA (ssGWAA) where all data, including non-genotyped animals, are used. The objectives of this study were to: 1) investigate the ability of ssGWAA to account for population structure and correctly identify quantitative trait nucleotides (QTN); and 2) compare ssGWAA with cGWAA and EMMAX. Three simulated datasets were used, which mimic fish, beef cattle, and dairy cattle populations. The fish population was composed of 2,040 fish, out of which 1,040 were genotyped and had phenotypes for a trait with heritability of 0.25. The beef cattle population had 6,010 animals in the pedigree, but only 1,500 with phenotypes (h2 = 0.35) and genotypes. Lastly, the dairy cattle population had 40,800 pedigreed animals, of which 20,000 females had phenotypes (h2 = 0.32) and 2,400 males were genotyped. All phenotypes, pedigree, and genotypes were used in ssGWAA, whereas only genotypes and phenotypes were used in cGWAA and EMMAX for the fish and beef cattle analyses. For the dairy cattle analysis using the last two methods, deregressed proofs had to be used instead of phenotypes. The ability to correctly identify QTN and the number of statistically significant SNP (P < 0.05/number of SNP) was assessed among methods. In all populations, cGWAA was able to identify some of the strongest QTN but showed a large number of false positives. EMMAX and ssGWAA did not show false associations and correctly identified the top QTN, with more signals observed in ssGWAA. The ssGWAA accounts for population structure and is a proper association method, especially for livestock populations where sparse genotyping is a reality and phenotypes may not be recorded in genotyped animals.
Population structure and genome-wide association analysis for salinity tolerance in wheat using SNP, SSR and SCoT marker assays.
