Efficiency of QTL mapping based on least squares, maximum likelihood, and Bayesian approaches under high marker density - Jan, Hikmat Ullah (2016)
Previous studies on quantitative trait loci (QTL) mapping efficiency assumed few QTLs of higher effect, no minor genes, and low marker density. This study assessed the efficiency of the least squares, maximum likelihood, and Bayesian approaches for QTL mapping assuming high single nucleotide polymorphism (SNP) density, zero to three QTLs and eight or nine minor genes per chromosome, and low proportion of the phenotypic variance explained by each QTL. We simulated 50 samples of 400 F2 individuals, which were genotyped for 1,000 SNPs (average density of one SNP/centiMorgan) and phenotyped for three traits controlled by 12 QTLs and 88 minor genes. The genes were randomly distributed in the regions covered by the SNPs along 10 chromosomes. The heritabilities were 0.3 and 0.7, and the sample sizes were 200 and 400. The least squares and maximum likelihood approaches were equivalent. The QTL mapping efficiency was not influenced by the degree of dominance but it was affected by heritability, sample size, marker density, and QTL effect. The Bayesian analysis showed greater power of QTL detection, mapping precision, and number of false- positives compared to the least squares and maximum likelihood approaches. The most important factor affecting the QTL mapping efficiency is the QTL effect.