Data from: Mapping quantitative trait loci using selected breeding populations: a segregation distortion approach
Cui, Yanru et al. (2015), Data from: Mapping quantitative trait loci using selected breeding populations: a segregation distortion approach, Dryad, Dataset, https://doi.org/10.5061/dryad.f6rr4
Quantitative trait locus (QTL) mapping is often conducted in line crossing experiments where progeny are derived randomly from the original crosses. The detected QTL from such experiments are rarely relevant to breeding populations because they are not detected from the breeding populations. We developed generalized linear model methods to perform QTL mapping in directionally selected populations using a segregation distortion approach. A selected population is often small and thus has low power for QTL detection. The segregation distortion approach actually takes advantage of the small populations because small selected populations often reflected strong selection and thus possess a high degree of segregation distortion. We also developed methods to combine results of several populations and results from different types of data analyses from the same populations. Such a combined analysis can boost statistical powers. Simulation studies showed that the new methods of QTL mapping in selected populations are powerful. We illustrated the methods using two selected rice populations and detected several QTL responsible to yield selection. The new methods can be applied not only to rice breeding programs but also to breeding programs of all crops.