Marker Pair Selection for Mapping Quantitative Trait Loci

Mapping of quantitative trait loci (QTL) for backcross and F2 populations may be set up as a multiple linear regression problem, where marker types are the regressor variables. It has been shown previously that flanking markers absorb all information on isolated QTL. Therefore, selection of pairs of markers flanking QTL is useful as a direct approach to QTL detection. Alternatively, selected pairs of flanking markers can be used as cofactors in composite interval mapping (CIM). Overfitting is a serious problem, especially if the number of regressor variables is large. We suggest a procedure denoted as marker pair selection (MPS) that uses model selection criteria for multiple linear regression. Markers enter the model in pairs, which reduces the number of models to be considered, thus alleviating the problem of overfitting and increasing the chances of detecting QTL. MPS entails an exhaustive search per chromosome to maximize the chance of finding the best-fitting models. A simulation study is conducted to study the merits of different model selection criteria for MPS. On the basis of our results, we recommend the Schwarz Bayesian criterion (SBC) for use in practice.

Genetic control of meiotic recombination in Petunia hybrida: dosage effect of gene Rm1 on segments Hf1-Lg1 and An2-Rt; role of modifiers

Populations segregating at locus Rm1 were used to measure recombination within two chromosome segments in Petunia hybrida. Gene Rm1 shows incomplete dominance and action that differs according to marker pair studied. It enhances recombination within the segment Hf1-Lg1 and restores it for the pair An2-Rt. Minor modifier genes exist, which act independent of or epistatic to Rm1 action. Like Rm1, they have effects that differ according to the chromosome segment analyzed, with the effects being more pronounced for strongly linked loci. Some of these genes are probably recessive.Key words: Petunia hybrida, gene Rm1, meiotic recombination, dosage effect.