QTL analysis of pest resistance in the wild tomato Lycopersicon pennellii: QTLs controlling acylsugar level and composition

Some accessions of Lycopersicon pennellii, a wild relative of the tomato Lycopersicon esculentum, are resistant to a number of important pests of cultivated tomato due to the accumulation of acylsugars, which constitute 90% of the exudate of type-IV trichomes in L. pennellii LA716. An interspecific F2 population, created by the cross L. esculentum x L. pennellii LA 716, was surveyed for acylsugar accumulation and subjected to RFLP/QTL analysis to determine the genomic regions associated with the accumulation of acylglucoses, acylsucroses, and total acylsugars, as well as with acylglucoses as a percentage of total acylsugars (mole percent acylglucoses). Data were analyzed using MAPMAKER/QTL with and without a log10 transformation. A threshold value of 2.4 (default value for MAPMAKER/QTL) was used, as well as 95% empirically derived threshold values. Five genomic regions, two on chromosome 2 and one each on chromosomes 3, 4 and 11, were detected as being associated with one or more aspects of acylsugar production. The L. esculentum allele is partially dominant to the L. pennellii allele in the regions on chromosomes 2 and 11, but the L. pennellii allele is dominant in the region on chromosome 3. Throughout this study, we report the comparative effects of analytical methodology on the identification of acylsugar QTLs. Similarities between our results and published results for the genus Solanum are also discussed.

Permutation tests for multiple loci affecting a quantitative character

The problem of detecting minor quantitative trait loci (QTL) responsible for genetic variation not explained by major QTL is of importance in the complete dissection of quantitative characters. Two extensions of the permutation-based method for estimating empirical threshold values are presented. These methods, the conditional empirical threshold (CET) and the residual empirical threshold (RET), yield critical values that can be used to construct tests for the presence of minor QTL effects while accounting for effects of known major QTL. The CET provides a completely nonparametric test through conditioning on markers linked to major QTL. It allows for general nonadditive interactions among QTL, but its practical application is restricted to regions of the genome that are unlinked to the major QTL. The RET assumes a structural model for the effect of major QTL, and a threshold is constructed using residuals from this structural model. The search space for minor QTL is unrestricted, and RET-based tests may be more powerful than the CET-based test when the structural model is approximately true.

QTL mapping in rice

In the past 10 years, interest in applying the tools of molecular genetics to the problem of increasing world rice production has resulted in the generation of two highly saturated, molecular linkage maps of rice, and the localization of numerous genes and quantitative trait loci (QTLs). Primary studies have identified QTLs associated with disease resistance, abiotic stress tolerance and yield potential of rice in a range of ecosystems. The ability to identify, manipulate and potentially clone individual genes involved in quantitatively inherited characters, combined with the demonstrated conservation of numerous linkage blocks among members of the grass family, emphasizes the contribution of map-based genetic analyses both to applied and to basic crop research.

Testing for linkage: phase known/unknown

It has been well established in human genetics that when one is testing for linkage between two loci, the significance test must be one-sided for the purpose of reflecting the theoretical limits placed on the estimated recombination fraction. However, the issue becomes obscure when phase-known/-unknown data are considered. This paper presents the subtle difference in hypotheses for testing linkage between two loci when data from which one estimates recombination fractions is phase known or phase unknown. It is shown that a one-sided significance test is appropriate for phase-known data, while a two-sided significance test is correct for phase-unknown data.

Empirical threshold values for quantitative trait mapping

The detection of genes that control quantitative characters is a problem of great interest to the genetic mapping community. Methods for locating these quantitative trait loci (QTL) relative to maps of genetic markers are now widely used. This paper addresses an issue common to all QTL mapping methods, that of determining an appropriate threshold value for declaring significant QTL effects. An empirical method is described, based on the concept of a permutation test, for estimating threshold values that are tailored to the experimental data at hand. The method is demonstrated using two real data sets derived from F(2) and recombinant inbred plant populations. An example using simulated data from a backcross design illustrates the effect of marker density on threshold values.