Detection of closely linked multiple quantitative trait loci using a genetic algorithm

The existence of a quantitative trait locus (QTL) is usually tested using t he likelihood of the quantitative trait on the basis of phenotypic characte r data plus the rt combination fraction between QTL and flanking markers. W hen doing this, the likelihood is calculated for all possible locations on the linkage map. When multiple QTL are suspected close by, it is impractica l to calculate the likelihood for all possible combinations of numbers and locations of QTL. Here, we propose a genetic algorithm (GA) for the heurist ic solution of this problem. GA can globally search tile optimum by improvi ng the "genotype" with alterations called "recombination" and "mutation." T he "genotype" of our GA is the number and location of QTL. The "fitness" is a function based on the likelihood plus Akaike's information criterion (AT C), which helps avoid false-positive QTL. A simulation study comparing the new method with existing QTL mapping packages shows the advantage of tile n ew GA. The GA reliably distinguishes multiple QTL located in a single marke r interval.