Academic journal article Genetics

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

Academic journal article Genetics

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

Article excerpt

ABSTRACT

In the data collection of the QTL experiments using recombinant inbred (RI) populations, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be obtained from the genotyped individuals (from the same population) or from some progeny of the genotyped individuals (from the different populations). Let F^sub u^ be the genotyped population and F^sub v^ (v ≥ u) be the phenotyped population. The experimental designs that both marker genotypes and phenotypes are recorded on the same populations can be denoted as (F^sub u^/F^sub v^ , u = v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (F^sub u^/F^sub v^ , v > u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F^sub 2^(F^sub 2^/F^sub 2^) designs, the other (F^sub u^/F^sub v^, v ≥ u) designs are also very popular. The great benefits of using the other (F^sub u^/F^sub v^, v ≥ u) designs in QTL mapping include reducing cost and environmental variance by phenotyping several progeny for the genotyped individuals and taking advantages of the changes in population structures of other RI populations. Current QTL mapping methods including those for the (F^sub u^/F^sub v^ , u = v) designs, mostly for the backcross or F^sub 2^/F^sub 2^ design, and for the F^sub 2^/F^sub 3^ design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (F^sub u^/F^sub v^, u ≤ v) designs, and they can be problematic due to ignoring their differences in population structures. In this article, a statistical method considering the differences in population structures between different RI populations is proposed on the basis of a multiple-QTL model to map for QTL in different (F^sub u^/F^sub v^, v ≥ u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were performed to evaluate the performance of the proposed and approximate methods. The proposed method is proven to be able to correct the problems of the approximate and current methods for improving the resolution of genetic architecture of quantitative traits and can serve as an effective tool to explore the QTL mapping study in the system of RI populations.

(ProQuest Information and Learning: ... denotes formulae omitted.)

MOST biologically important traits show continuous variations and have poor heritability. Traditional study of quantitative genetics based on the phenotype evaluation to investigate quantitative trait loci (QTL) controlling these traits is difficult and limited. Recently, the advent of fine-scale molecular markers has provided researchers with an efficient tool for the detection of the underlying QTL. Most QTL detection experiments for producing marker genotypes and phenotypic traits in species have been conducted with populations derived from crosses between inbred lines, e.g., backcross, advanced backcross, F^sub 2^, recombinant inbred (RI) populations, intermated recombinant inbred (IRI) populations, advanced intercross (AI) populations, advanced backcross populations, double haploid (DH) populations, and NC Design III, etc. (COMSTOCK and ROBINSON 1952; STUBER et al. 1992; BEAVIS et al. 1994; VELDBOOM et al. 1994; DARVASI and SOLLER 1995; AUSTIN and LEE 1996; LIU et al. 1996; CHAPMAN et al. 2003; WINKLER et al. 2003; COMPLEX TRAIT CONSORTIUM 2004; BROMAN 2005). These different populations may show different properties in QTL mapping as they have different population structures, such as homozygosity, genotypic frequencies, and linkage disequilibrium (WEIR 1996, Chap. 5). In principle, the use of the information about genotypes and phenotypes of individuals in these populations has become a key approach to detect the underlying QTL for the understanding of the genetic basis and the improvement of important traits in genetic study.

In the data collection of these QTL experiments, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be recorded on the genotyped individuals (on the same population) or on some progeny of the genotyped individuals (on the progeny population). …

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