We use cookies on our website. Some are necessary for the operation of the website. You can also allow cookies for statistical purposes. You can adjust the data protection settings or agree to all cookies directly.
SPP 1149: Transcriptome- and metabolome-based prediction of heterosis and hybrid performance in experimental hybrids of maize
Project
Project code: DFG SPP 1149
Contract period: 01.01.2003
- 31.12.2009
Purpose of research: Basic research
QTL mapping is regarded as a powerful tool to uncover the genetic basis of heterosis. However, the approaches applied hitherto suffer from two drawbacks: (1) The materials analyzed usually originate from one hybrid and, thus, may not be representative for the germplasm of a crop in general. (2) The experiments rely on large segregating populations that are of no further use in hybrid breeding. Here, we propose a new, haplotype-based method for mapping and characterizing heterotic QTL that can be applied directly to experimental hybrids commonly tested in maize breeding programs. The method promises also a solution for the prediction of the large proportion (more than 90%) of untested hybrids - one the biggest unsolved problems in hybrid breeding! The new approach will be examined with (a) simulated data and (b) experimental data of 400 interpool hybrids and their 80 parent lines grown in 6 environments as well as high density maps of AFLP and SSR markers. Based on the observed heterosis values, a small number of genotypes will be chosen and propagated to serve as a common plant resource (CPR) for all molecular groups working in maize including our own assays with mAFLPs on the role of DNA-methylation in heterosis of maize. Thus, our investigations provide a valuable database in maize, which in combination with molecular and genomic tools promises a major contribution in uncovering the basis of heterosis and its optimum exploitation in hybrid breeding.
Section overview
Subjects
- Plant Breeding
Collaborative Project
Funding programme
Excutive institution
Iinterdisciplinary Research Center for Biosystems, Land Use and Nutrition (IFZ)