Mapping Quantitative Trait Loci Using Inter-Crossed F3 Populations

10.29973/JCSA.200903.0003

Miao-Hui Zeng；Chen-Hung Kao

EM algorithm ； maximum likelihood ； normal mixture model ； QTL mapping ； interval mapping ； inter-crossed F3 population ； advanced intercross populations

中國統計學報

47卷1期（2009 / 03 / 01）

39 - 63

英文

Most of the current QTL mapping methods are developed for the backcross and F2 populations. The inter-crossed F3 population is also popular and has been well devised in genetic study. As the F3 population can provide more recombinants than the backcross and F2 populations, it can facilitate the detection of closely linked QTL. In this paper, we propose a statistical model to estimate the effects and positions of QTL for the F3 population by considering the differences in the genome structure between the F3 and F2 populations. As the genotypes of QTL are usually unknown, the statistical model is a finite mixture model. By treating the mixture model as an incomplete data problem, the EM algorithm is implemented to obtain the maximum likelihood estimates of the parameters. Simulations were used to illustrate the performance of the proposed method and evaluate the relative efficiency in the F3 population (as comparing to that of the F2 population) in QTL mapping under several factors, such as sample size, genetic distance between QTL (and markers), the proportion of trait variance contributed by QTL (i.e. heritability). It is found that the QTL mapping by using the F3 population is more powerful and precise in separating closely linked QTL and in estimating the parameters as compare to the use of the F2 population, especially for small sample size, close genetic distance and low heritability. The paper can help outline a strategy of detecting tightly linked QTL for the advanced intercross populations to improve the resolution of genetic architecture of quantitative traits.