PT - JOURNAL ARTICLE AU - Kao, Chen-Hung TI - Mapping Quantitative Trait Loci Using the Experimental Designs of Recombinant Inbred Populations AID - 10.1534/genetics.106.056416 DP - 2006 Nov 01 TA - Genetics PG - 1373--1386 VI - 174 IP - 3 4099 - 4100 - SO - Genetics2006 Nov 01; 174 AB - 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 Fu be the genotyped population and Fv (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 (Fu/Fv, u = v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (Fu/Fv, v &gt; u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F2(F2/F2) designs, the other (Fu/Fv, v ≥ u) designs are also very popular. The great benefits of using the other (Fu/Fv, v ≥ 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. Current QTL mapping methods including those for the (Fu/Fv, u = v) designs, mostly for the backcross or F2/F2 design, and for the F2/F3 design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (Fu/Fv, 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 (Fu/Fv, v ≥ u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were performed 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.