Abstract
Although the term quantitative trait locus (QTL) strictly refers merely to a genetic variant that causes changes in a quantitative phenotype such as height, QTL analysis more usually describes techniques used to study oligogenic or polygenic traits where each identified locus contributes a relatively small amount to the genetic determination of the trait, which may be categorical in nature. Originally, too, it would be clear that it covered segregation and genetic linkage analysis, but now genetic association analysis in a genome-wide SNP or sequencing experiment would be the commonest application. The same biometrical genetic statistical apparatus used in this setting-analysis of variance, linear or generalized linear mixed models-can actually be applied to categorical phenotypes, as well as to multiple traits simultaneously, dealing with and taking advantage of genetic pleiotropy. Most recently, they are being used to make inferences about population and evolutionary genetics, with applications ranging from human disease to control of disease-causing organisms. Several computer software packages make it relatively straightforward to fit these statistically complex models to the large amounts of genotype and phenotype data routinely collected today.
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