A simulation study on the accuracy of position and effect estimates of linked QTL and their asymptotic standard deviations using multiple interval mapping in an F2 scheme

Abstract

Approaches like multiple interval mapping using a multiple-QTL model for simultaneously mapping QTL can aid the identification of multiple QTL, improve the precision of estimating QTL positions and effects, and are able to identify patterns and individual elements of QTL epistasis. Because of the statistical problems in analytically deriving the standard errors and the distributional form of the estimates and because the use of resampling techniques is not feasible for several linked QTL, there is the need to perform large-scale simulation studies in order to evaluate the accuracy of multiple interval mapping for linked QTL and to assess confidence intervals based on the standard statistical theory. From our simulation study it can be concluded that in comparison with a monogenetic background a reliable and accurate estimation of QTL positions and QTL effects of multiple QTL in a linkage group requires much more information from the data. The reduction of the marker interval size from 10 cM to 5 cM led to a higher power in QTL detection and to a remarkable improvement of the QTL position as well as the QTL effect estimates. This is different from the findings for (single) interval mapping. The empirical standard deviations of the genetic effect estimates were generally large and they were the largest for the epistatic effects. These of the dominance effects were larger than those of the additive effects. The asymptotic standard deviation of the position estimates was not a good criterion for the accuracy of the position estimates and confidence intervals based on the standard statistical theory had a clearly smaller empirical coverage probability as compared to the nominal probability. Furthermore the asymptotic standard deviation of the additive, dominance and epistatic effects did not reflect the empirical standard deviations of the estimates very well, when the relative QTL variance was smaller/equal to 0.5. The implications of the above findings are discussed. mapping / QTL / simulation / asymptotic standard error / confidence interval

A comparison of regression interval mapping and multiple interval mapping for linked QTL

“…In contrast to the findings in the literature for single QTL analyses (eg Soller and Genizi, 1978;Dupuis and Siegmund, 1999;Piepho, 2000), Mayer et al (2004) found in a simulation study using multiple interval mapping methodology for an F 2 schema with linked multiple QTL that the reduction of the marker interval size from 10 to 5 cM led to a higher power in QTL detection and to a remarkable improvement of the precision of the QTL position as well as the QTL effect estimates. They also found that the asymptotic standard deviation of the position estimates was not a good criterion for the accuracy of the position estimates.…”

“…From the wide range of scenarios studied, Kao (2000) concluded that especially when QTL are linked, regression interval mapping as compared to multiple interval mapping may have a serious problem and even more if these QTL are in repulsion. From the study of, for example, Mayer et al (2004), it is known that, in comparison with a monogenetic background, a reliable and accurate estimation of QTL positions and QTL effects of multiple QTL in a linkage group requires much more information from the data, and that even the analyses of relatively large data sets can lead to estimates with relatively large standard errors. While Kao (2000) performed just one likelihood calculation per replicate and scenario, a grid search of the maximum of the likelihood function is obviously computationally much more demanding.…”

Generalized composite interval mapping offers improved efficiency in the analysis of loci influencing non-normal continuous traits

“…The accuracy of QTL mapping must be as high as possible (Mora et al, 2008a). Mayer et al (2004) for example, found that the reduction of the marker interval size from 10 cM to 5 cM led to a higher power in QTL detection and to a remarkable improvement of the QTL position as well as the QTL effect estimates.…”

“…Statistical procedures have been extensively studied because they are essential for improving the accuracy of genetic analyses (Mora et al, 2008a). In a simulation study on the accuracy of position and effect estimates of linked QTL, Mayer et al (2004) found that the reduction of the marker interval size from 10 cM (centiMorgan) to 5 cM led to a higher power in QTL detection and to an improvement of the QTL position as well as the QTL effect estimates.…”

Statistical properties of QTL linkage mapping in biparental genetic populations

“…The bias of estimators of QTL effects and locations from IM was discussed by Bogdan and Doerge (2005). On the basis of multiple interval mapping, Mayer et al (2004) studied the accuracy of position and effect estimates of linked QTLs in F 2 populations by simulation. Some theoretical and simulation studies have also been conducted on the confidence interval of IM Dupuis and Siegmund, 1999).…”