Quantitative trait locus mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits.

From simulation studies it is known that the allocation of experimental resources has a crucial effect on power of QTL detection as well as on accuracy and precision of QTL estimates. In this study, we used a very large experimental data set composed of 976 F(5) maize testcross progenies evaluated in 19 environments and cross-validation to assess the effect of sample size (N), number of test environments (E), and significance threshold on the number of detected QTL, the proportion of the genotypic variance explained by them, and the corresponding bias of estimates for grain yield, grain moisture, and plant height. In addition, we used computer simulations to compare the usefulness of two cross-validation schemes for obtaining unbiased estimates of QTL effects. The maximum, validated genotypic variance explained by QTL in this study was 52.3% for grain moisture despite the large number of detected QTL, thus confirming the infinitesimal model of quantitative genetics. In both simulated and experimental data, the effect of sample size on power of QTL detection as well as on accuracy and precision of QTL estimates was large. The number of detected QTL and the proportion of genotypic variance explained by QTL generally increased more with increasing N than with increasing E. The average bias of QTL estimates and its range were reduced by increasing N and E. Cross-validation performed well with respect to yielding asymptotically unbiased estimates of the genotypic variance explained by QTL. On the basis of our findings, recommendations for planning of QTL mapping experiments and allocation of experimental resources are given.

A molecular marker map in 'Kanota' x 'Ogle' hexaploid oat (Avena spp.) enhanced by additional markers and a robust framework.

Molecular mapping of cultivated oats was conducted to update the previous reference map constructed using a recombinant inbred (RI) population derived from Avena byzantina C. Koch cv. Kanota x Avena sativa L. cv. Ogle. In the current work, 607 new markers were scored, many on a larger set of RI lines (133 vs. 71) than previously reported. A robust, updated framework map was developed to resolve linkage associations among 286 markers. The remaining 880 markers were placed individually within the most likely framework interval using chi2 tests. This molecular framework incorporates and builds on previous studies, including physical mapping and linkage mapping in additional oat populations. The resulting map provides a common tool for use by oat researchers concerned with structural genomics, functional genomics, and molecular breeding.