Improved heterosis prediction by combining information on DNA- and metabolic markers.
BACKGROUND
Hybrids represent a cornerstone in the success story of breeding programs. The fundamental principle underlying this success is the phenomenon of hybrid vigour, or heterosis. It describes an advantage of the offspring as compared to the two parental lines with respect to parameters such as growth and resistance against abiotic or biotic stress. Dominance, overdominance or epistasis based models are commonly used explanations.


CONCLUSIONS
The heterosis level is clearly a function of the combination of the parents used for offspring production. This results in a major challenge for plant breeders, as usually several thousand combinations of parents have to be tested for identifying the best combinations. Thus, any approach to reliably predict heterosis levels based on properties of the parental lines would be highly beneficial for plant breeding.


RESULTS
Recently, genetic data have been used to predict heterosis. Here we show that a combination of parental genetic and metabolic markers, identified via feature selection and minimum-description-length based regression methods, significantly improves the prediction of biomass heterosis in resulting offspring. These findings will help furthering our understanding of the molecular basis of heterosis, revealing, for instance, the presence of nonlinear genotype-phenotype relationships. In addition, we describe a possible approach for accelerated selection in plant breeding.
Department of Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam-Golm, Germany.
Tanja
T
Gärtner
Matthias
M
Steinfath
Sandra
S
Andorf
Jan
J
Lisec
Rhonda C
RC
Meyer
Thomas
T
Altmann
Lothar
L
Willmitzer
Joachim
J
Selbig
D017360:Arabidopsis / Q000235:genetics; D015415:Biomarkers; D001947:Breeding; D003433:Crosses, Genetic; D004247:DNA; D017343:Genes, Plant; D005819:Genetic Markers; D018745:Genome, Plant; D005838:Genotype; D006823:Hybrid Vigor / Q000235:genetics*; D010641:Phenotype; D040641:Quantitative Trait Loci
D015415:Biomarkers; D005819:Genetic Markers; D004247:DNA