MULTITRAIT AND MULTIPOPULATION QTL SEARCH USING SELECTIVE GENOTYPING

Selective genotyping, i.e. increasing the size of the population pheno typed and genotyping only individuals from the high and low tails of t he population, can considerably improve the efficiency of experiments aimed at detecting and locating quantitative trait loci (QTLs) affecti ng a single trait. In this paper we study how selective genotyping can increase the efficiency of multitrait QTL experiments. By selecting o n an index combining the variables of interest and having the maximum correlation with each variable, the efficiency of QTL detection is inc reased for each trait. The efficiency of selective genotyping relative to random selection strongly depends on the correlation between the i ndex and each variable. The optimum selection rate that minimizes cost s for a given experimental power depends also on this correlation and on the genotyping costs relative to phenotyping costs. When the popula tion segregating for the quantitative traits and the markers is not as simple as a backcross or an F-2 population, but is composed of severa l connected or unconnected families, selective genotyping can be used to improve the efficiency of the QTL study. In this case, the extreme individuals should be selected within each family. A method is provide d to choose the selection rates within each family in order to optimiz e the global power of the experiment when the family sizes are unequal .