FINE-SCALE MAPPING OF QUANTITATIVE TRAIT LOCI USING HISTORICAL RECOMBINATIONS

With increasing popularity of QTL mapping in economically important an imals and experimental species, the need for statistical methodology f or fine-scale QTL mapping becomes increasingly urgent. The ability to disentangle several linked QTL depends on the number of recombination events. An obvious approach to increase the recombination events is to increase sample size, but this approach is often constrained by resou rces. Moreover, increasing the sample size beyond a certain point will not further reduce the length of confidence interval for QTL map loca tions. The alternative approach is to use historical recombinations. W e use analytical methods to examine the properties of fine QTL mapping using historical recombinations that are accumulated through repeated intercrossing from an F-2 population. We demonstrate that, using the historical recombinations, both simple and multiple regression models can reduce significantly the lengths of support intervals for estimate d QTL map locations and the variances of estimated QTL map locations. We also demonstrate that, while the simple regression model using hist orical recombinations does not reduce the variances of the estimated a dditive and dominant effects, the multiple regression model does. We f urther determine the power and threshold values for both the simple an d multiple regression models. In addition, we calculate the Kullback-L eibler distance and Fisher information for the simple regression model , in the hope to further understand the advantages and disadvantages o f using historical recombinations relative to F-2 data.