the objective of this study was to compare the accuracy of estimating and predicting breeding values using two diverse approaches, gblup and bayesc, using simulated data under different quantitative trait locus(qtl) effect distributions. data were simulated with three different distributions for the qtl effect which were uniform, normal and gamma (1.66, 0.4). the number of qtl was assumed to be...

The objective of this study was to compare the accuracy of estimating and predicting breeding values using two diverse approaches, GBLUP and BayesC, using simulated data under different quantitative trait locus(QTL) effect distributions. Data were simulated with three different distributions for the QTL effect which were uniform, normal and gamma (1.66, 0.4). The number of QTL was assumed to be...

introduction genetic evaluation and estimation of breeding value are one of the most fundamental elements of breeding programmes for genetic improvement. recently, genomic selection has become an efficient method to approach this aim. the accuracy of estimated genomic breeding value is the most important factor in genomic selection. different studies have been performed addressing the factors a...

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype infor...

The shrinkage estimate of a quantitative trait locus (QTL) effect is the posterior mean of the QTL effect when a normal prior distribution is assigned to the QTL. This note gives the derivation of the shrinkage estimate under the multivariate linear model. An important lemma regarding the posterior mean of a normal likelihood combined with a normal prior is introduced. The lemma is then used to...

The distribution of effect sizes of genes underlying adaptation is unknown (Orr 2005). Are suites of traits that diverged under natural selection controlled by a few pleiotropic genes of large effect (major genes model), by many independently acting genes of small effect (infinitesimal model), or by a combination, with frequency inversely related to effect size (geometric model)? To address thi...

The L-shaped distribution of estimated QTL effects (R(2)) has long been reported. We recently showed that a metabolic mechanism could account for this phenomenon. But other nonexclusive genetic or nongenetic causes may contribute to generate such a distribution. Using analysis and simulations of an additive genetic model, we show that linkage disequilibrium between QTL, low heritability, and sm...

Quantitative trait loci (QTLs) may affect not only the mean of a trait but also its variability. A special aspect is the variability between multiple measured traits of genotyped animals, such as the within-litter variance of piglet birth weights. The sample variance of repeated measurements is assigned as an observation for every genotyped individual. It is shown that the conditional distribut...

We considered a strategy to map quantitative trait loci (QTLs) using linkage disequilibrium (LD) when the QTL and marker locus were multiallelic. The strategy involved phenotyping a large number of unrelated individuals and genotyping only selected individuals from the two tails of the trait distribution. Power to detect trait-marker association was assessed as a function of the number of QTL a...