Abstract
Two previously described QTL mapping methods, which combine linkage analysis (LA) and linkage disequilibrium analysis (LD), were compared for their ability to detect and map multiple QTL. The methods were tested on five different simulated data sets in which the exact QTL positions were known. Every simulated data set contained two QTL, but the distances between these QTL were varied from 15 to 150 cM. The results show that the single QTL mapping method (LDLA) gave good results as long as the distance between the QTL was large (> 90 cM). When the distance between the QTL was reduced, the single QTL method had problems positioning the two QTL and tended to position only one QTL, i.e. a "ghost" QTL, in between the two real QTL positions. The multi QTL mapping method (MP-LDLA) gave good results for all evaluated distances between the QTL. For the large distances between the QTL (> 90 cM) the single QTL method more often positioned the QTL in the correct marker bracket, but considering the broader likelihood peaks of the single point method it could be argued that the multi QTL method was more precise. Since the distances were reduced the multi QTL method was clearly more accurate than the single QTL method. The two methods combine well, and together provide a good tool to position single or multiple QTL in practical situations, where the number of QTL and their positions are unknown.
Highlights
Several studies have suggested combining linkage and linkage disequilibrium mapping for finding QTL, e.g. [1, 4, 12, 14]
MP-LDLA tests whether there is a QTL at the putative position given all other QTL fitted in the model
For 30 cM between QTL, the LDLA analysis was performed for a region containing both the QTL, while the MP-LDLA analysis was done for two separate regions
Summary
Several studies have suggested combining linkage and linkage disequilibrium mapping for finding QTL, e.g. [1, 4, 12, 14]. Several studies have suggested combining linkage and linkage disequilibrium mapping for finding QTL, e.g. Linkage analysis only takes into consideration the recombinations that can be observed using pedigree data in the genotyped generations to position the QTL. This implies that, even if dense marker maps are used, the confidence intervals of the position estimates are quite large, because dense marker maps generally give too few recombinations in the genotyped generations to delineate small regions of interest. Linkage disequilibrium (LD) is based on identity by descent probabilities (IBD), allowing to use historical recombinations, and can distinguish between very dense marker maps and give very short confidence intervals. LD alone is, likely to result in false positives, because of spurious associations between the markers and the QTL
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