Mapping quantitative trait loci using the experimental designs of recombinant inbred populations

In the data collection of the QTL experiments using recombinant inbred (RI) populations, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be obtained from the genotyped individuals (from the same population) or from some progeny of the genotyped individuals (from the different populations). Let F-u be the genotyped population and F-v (v >= u) be the phenotyped population. The experimental designs that both marker genotypes and phenotypes are recorded on the same populations can be denoted as (F-u/F-v, u = v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (F-u/F-v, v > u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F-2 (F-2/F-2) designs, the other (F-u/F-v, v >= u) designs are also very popular. The great benefits of using the other (F./F,, v E! u) designs in QTL mapping include reducing cost and environmental variance by phenotyping several progeny for the genotyped individuals and taking advantages of the changes in population structures of other RI populations. Gurrent QTL mapping methods including those for the (F-u/F-v, u = v) designs, mostly for the backcross or F-2/F-2 design, and for the F-2/F-3 design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (F-u/F-v, u <= v) designs, and they can be problematic due to ignoring their differences in population Structures. In this article, a statistical method considering the differences in population structures between different RI populations is proposed on the basis of a multiple-QTL model to map for QTL in different (F-u/F-v, v >= u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were pet-formed to evaluate the performance of the proposed and approximate methods. The proposed method is proven to be able to correct the problems of the approximate and current methods for improving the resolution of genetic architecture of quantitative traits and can serve as an effective tool to explore the QTL mapping study in the system of RI populations.