Simulation Study on the Methods for Mapping Quantitative Trait Loci in Inbred Line Crosses

As the fast advance in molecular genetics, it is much easy to get well-distributed genetic markers in almost every organism nowadays. Therefore, as the major direction of quantitative genetics, vary statistical methods have been developed to detect or map quantitative trait loci (QTL) by using the genetic marker information. In this dissertation, the principles and models have been summarized for various QTL mapping methods. These methods include single marker analysis, interval mapping (IM), composite interval mapping (CIM), mixed-model-based composite interval mapping (MCIM), and multiple interval mapping (MIM). A large scale of simulation studies has been used for exploring and comparing various QTL mapping methods. The simulation study has indicated that although the single marker analysis has the ability to detect the QTLs but it cannot locate the positions of the QTL and obtain the estimation of the QTL effects. Simulations have also been conducted for studying and comparing different methods (IM, CIM, and MCIM) of QTL mapping under the simple additive situation. By analysing the LR profile, the power of QTL detection and the probability of false QTL detected can be calculated for the three methods under various situations. The estimation of QTL effects and positions as well as their 95% experimental confidence interval (ECI) for the detected QTLs is also obtained. The simulation results are useful to those who are using these three methods for QTL mapping practices. The results could be used as one of the bases for chosen the QTL mapping method among the available methods for a particular experiment design. The research can also provide the information for helping the analysis of the QTL mapping result. However, under the real QTL mapping experiments, more complicated situations such as QTL by environment interactions and QTL epistasis are existed generally. For IM and CIM methods, the simulation studies implied that the estimation of QTL main effects can be obtained unbiased by using data for all environments together. However, it is difficult to obtain the estimation of QE interaction effects, even by doing QTL mapping on the data for different environment separately. MCIM method has the ability to put all QTL main effects and QE interaction effects into the mixed linear model and obtained the unbiased estimation of main and QE effects as indicated by the simulation study work. MCIM method can also use mixed linear model for mapping QTLs with marginal and epistatic effects. The simulation study has indicated that MCIM method can obtain the unbiased estimation of QTL marginal and epistatic effects at the same time. Although IM and CIM have the ability to get the unbiased estimation of marginal QTL effects when the QTL epistatic effects are existed, the variance for the estimation of marginal effects will increase largely too. On the other hand, the detection power of QTLs will go down and the probability of false QTL detection will go up apparently, especially for the CIM method as the simulation study indicated. MIM is a multiple QTL oriented method and it also has the ability to analysis the QTL epistatic effects. However, one of the crucial parts for MIM method is the criteria or stopping rule for model selection. We proposed a set of parameters for measuring the fitness between the selected model and the real model and an experimental criterion has been presented for model selection in the framework of QTL mapping by using simulation method. The criterion is a modification of BIC by adding relevant facts such as heritability, marker density, sample size, and chromosome numbers. The experimental criterion works fine in the simulation cases. A modified software version of QTL Cartographer has been developed and it is called Windows QTL Cartographer. Unlike original QTL Cartographer, Windows QTL Cartographer is the QTL mapping software with user-friend interface and powerful ability of graphic presentation for the mapping results. It has many users and been posted on the Internet: (http://statgen.ncsu.edu/qtlcart/WQTLCart.htm).