Duffy David L
Genetic Epidemiology Laboratory, QIMR Berghofer Medical Research Institute, 300 Herston Rd., Brisbane, QLD, 4006, Australia.
Methods Mol Biol. 2017;1526:191-203. doi: 10.1007/978-1-4939-6613-4_11.
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.
尽管数量性状基因座（QTL）这一术语严格来说仅指导致身高之类的数量性状发生变化的基因变异，但QTL分析通常更多地描述用于研究寡基因或多基因性状的技术，其中每个已识别的基因座对性状的遗传决定作用相对较小，而该性状本质上可能是分类性状。最初，很明显它涵盖了分离分析和遗传连锁分析，但现在全基因组SNP或测序实验中的遗传关联分析是最常见的应用。在此设置中使用的相同生物统计学遗传统计工具——方差分析、线性或广义线性混合模型——实际上可应用于分类性状，也可同时应用于多个性状，处理并利用基因多效性。最近，它们正被用于对群体和进化遗传学进行推断，应用范围从人类疾病到致病生物的控制。有几个计算机软件包能让将这些统计上复杂的模型与如今常规收集的大量基因型和表型数据进行拟合变得相对简单。
