Improved Heterosis Prediction by Combining Information on DNA- and Metabolic Markers Tanja Ga¨ rtner1, Matthias Steinfath1, Sandra Andorf2, Jan Lisec3, Rhonda C. Meyer4, Thomas Altmann 4 , Lothar Willmitzer3, Joachim Selbig1,3* 1 Department of Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam-Golm, Germany, 2 Bioinformatics and Biomathematics Group, Genetics and Biometry Unit, Research Institute for the Biology of Farm Animals (FBN), Dummerstorf, Germany, 3 Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm, Germany, 4 Department of Molecular Biology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany Abstract 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. Conclusion/Significance: 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. Methodology/Principal Findings: 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. Citation: Ga¨rtner T, Steinfath M, Andorf S, Lisec J, Meyer RC, et al. (2009) Improved Heterosis Prediction by Combining Information on DNA- and Metabolic Markers. PLoS ONE 4(4): e5220. doi:10.1371/journal.pone.0005220 Editor: Samuel P. Hazen, University of Massachusetts Amherst, United States of America Received December 1, 2008; Accepted March 18, 2009; Published April 16, 2009 Copyright: 2009 Ga¨rtner et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the German Research Council (DFG) under Grants RE 1654/2-1 and SE 611/3-1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: selbig@mpimp-golm.mpg.de Introduction The introduction of the concept of hybrids probably represents the most important single innovation in plant breeding. Central to the concept of hybrid breeding is the phenomenon of heterosis or hybrid vigour [1], which essentially describes the superiority of the hybrid line derived from two parental inbred lines with respect to numerous parameters, with yield being the most important one. It is crucial to note that the superiority of the hybrid is not only realized in comparison to the two parental lines but most importantly also in comparison to lines obtained by classical line breeding [2]. Crops strongly relying on hybrid breeding include maize [2], rye [3], sugar beet [4], rice [5] or oilseed rape [6,7]. Despite its central importance for the hybrid breeding concept, the molecular basis responsible for the heterosis effects is far from being understood. From a genetics perspective, dominance, overdominance or epistasis based models are commonly used as explanations for heterosis [8]. One central observation in hybrid breeding programs is that the extent of heterosis is strongly dependent on the two parental lines. Thus, with respect to yield, for instance, heterosis can vary strongly depending upon the specific combination. In addition to its puzzling biological complexity, this represents a severe challenge to plant breeding, as usually the best combination of two parental lines can only be determined by trial and error. Therefore many thousands of testcrosses are required in order to find the optimal parental combination for the trait of interest. Numerous attempts have been followed with the goal to reduce the level of uncertainty concerning suitable parental combinations and to achieve some level of predictability. Not surprisingly mostly genetic markers of the two parents were used in these approaches [9–12]. Despite the fact that genetic markers have proven to be highly useful in plant breeding for marker-assisted selection of simple traits that are difficult to assay [13–15], they have their limitations when it comes to complex phenomenons involving many genes, such as heterosis. Even using dense genetic maps, marker intervals can still cover several hundred genes [16], i.e. their genetic resolution is low and their ability to account for complex interactions between several or many genes and their products is limited. We set out to test whether heterosis prediction can be improved by using more complex parameters of the parental line than genetic markers. To this end, we decided to investigate parental PLoS ONE | www.plosone.org 1 April 2009 | Volume 4 | Issue 4 | e5220