Mapping Quantitative Trait Loci in F2 Incorporating Phenotypes of F3 Progeny

Abstract

In plants and laboratory animals, QTL mapping is commonly performed using F 2 or BC individuals derived from the cross of two inbred lines. Typical QTL mapping statistics assume that each F 2 individual is genotyped for the markers and phenotyped for the trait. For plant traits with low heritability, it has been suggested to use the average phenotypic values of F 3 progeny derived from selfing F 2 plants in place of the F 2 phenotype itself. All F 3 progeny derived from the same F 2 plant belong to the same F 2:3 family, denoted by F 2:3 . If the size of each F 2:3 family (the number of F 3 progeny) is sufficiently large, the average value of the family will represent the genotypic value of the F 2 plant, and thus the power of QTL mapping may be significantly increased. The strategy of using F 2 marker genotypes and F 3 average phenotypes for QTL mapping in plants is quite similar to the daughter design of QTL mapping in dairy cattle. We study the fundamental principle of the plant version of the daughter design and develop a new statistical method to map QTL under this F 2:3 strategy. We also propose to combine both the F 2 phenotypes and the F 2:3 average phenotypes to further increase the power of QTL mapping. The statistical method developed in this study differs from published ones in that the new method fully takes advantage of the mixture distribution for F 2:3 families of heterozygous F 2 plants. Incorporation of this new information has significantly increased the statistical power of QTL detection relative to the classical F 2 design, even if only a single F 3 progeny is collected from each F 2:3 family. The mixture model is developed on the basis of a single-QTL model and implemented via the EM algorithm. Substantial computer simulation was conducted to demonstrate the improved efficiency of the mixture model. Extension of the mixture model to multiple QTL analysis is developed using a Bayesian approach. The computer program performing the Bayesian analysis of the simulated data is available to users for real data analysis.

Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

“…QTL mapping was carried out for data sets from single environment (separate analysis for each environment in three generations) following Zhang and Xu [31], and a set of data from the means of different environments in F 2:3 generation (combined analysis). The graphic representation of the linkage group and QTLs marked were created by Map Chart 2.2, following Voorrips et al [32].…”

A mixture model approach to the mapping of QTL controlling endosperm traits with bulked samples

“…For instance, under the same simulation setting where the heredity of QTL is 10%, 5 endosperms collected per plant and the number of plants is 50, the power is greater than 90% with either the proposed exact or approximate algorithm, whereas only 75% with the IRWLS (Xu et al 2003). Note also that the approximate algorithm suggested here is distinguished from the one used in Zhang and Xu (2004)'s diploid model, where multinomial distributions are replaced by the joint bivariate normal ones. Such approximation is inapplicable to ours because the distributions of x 2i and x 3i are too skewed for multivariate normals.…”

“…One can take the family mean as the unit of phenotypic measurement, namely that the input data set be analyzed as results from averaging over phenotypic values sampled from one plant. This idea has also been adopted in the method of Zhang and Xu (2004) to handle the traits with low heritability and to reduce the residual error variance. But such method was developed under the diploid model and up to now no bulked sample method has been available for the QTL mapping of endosperm traits.…”

Mapping Quantitative Trait Loci Using the Experimental Designs of Recombinant Inbred Populations

“…As multiple (m) intervals are used to infer the multiple QTL, this model is a multiple-interval mapping-based (MIM-based) method for the (F u /F v , u , v) designs. A single-QTL model for the F 2 /F 3 design was first proposed by Zhang and Xu (2004).…”

“…Fisch et al (1996) illustrated the situations of data collection by F u /F v , where F u is the genotyped population and F v (v $ u) is the phenotyped population, in the system of RI populations 1 article, the one-QTL model by Zhang and Xu (2004) and the approximate method may have confounding problems in the estimation of QTL parameters and lose power of QTL detection. Ideally, we would like to extend the one-QTL model to a multiple-QTL model and the F 2 /F 3 design to the more general (F u /F v , u # v) designs for more practical and broad use in a way that multiple QTL and their possible epistasis can be considered in the model to correct the problems and the benefit of other RI populations as mentioned can be utilized to further improve and study QTL mapping.…”