@misc{GaertnerSteinfathAndorfetal.2009, author = {G{\"a}rtner, Tanja and Steinfath, Matthias and Andorf, Sandra and Lisec, Jan and Meyer, Rhonda C. and Altmann, Thomas and Willmitzer, Lothar and Selbig, Joachim}, title = {Improved heterosis prediction by combining information on DNA- and metabolic markers}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-45132}, year = {2009}, 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.}, language = {en} } @article{SteinfathStrehmelPetersetal.2010, author = {Steinfath, Matthias and Strehmel, Nadine and Peters, Rolf and Schauer, Nicolas and Groth, Detlef and Hummel, Jan and Steup, Martin and Selbig, Joachim and Kopka, Joachim and Geigenberger, Peter and Dongen, Joost T. van}, title = {Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach}, issn = {1467-7644}, doi = {10.1111/j.1467-7652.2010.00516.x}, year = {2010}, abstract = {Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.}, language = {en} } @misc{SteinfathGaertnerLisecetal.2009, author = {Steinfath, Matthias and G{\"a}rtner, Tanja and Lisec, Jan and Meyer, Rhonda C. and Altmann, Thomas and Willmitzer, Lothar and Selbig, Joachim}, title = {Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1324}, issn = {1866-8372}, doi = {10.25932/publishup-43111}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-431115}, pages = {9}, year = {2009}, abstract = {A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80\% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.}, language = {en} } @article{MeyerKustererLisecetal.2009, author = {Meyer, Rhonda Christiane and Kusterer, Barbara and Lisec, Jan and Steinfath, Matthias and Becher, Martina and Scharr, Hanno and Melchinger, Albrecht E. and Selbig, Joachim and Schurr, Ulrich and Willmitzer, Lothar and Altmann, Thomas}, title = {QTL analysis of early stage heterosis for biomass in Arabidopsis}, series = {Theoretical and applied genetics}, volume = {129}, journal = {Theoretical and applied genetics}, number = {2}, publisher = {Springer Nature}, address = {Berlin}, issn = {1432-2242}, doi = {10.1007/s00122-009-1074-6}, pages = {227 -- 237}, year = {2009}, abstract = {The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44\% heterosis for biomass. Mid-parent heterosis in the RILs ranged from -31 to 99\% for dry weight and from -58 to 143\% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7\% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross.}, language = {en} } @misc{MeyerKustererLisecetal.2009, author = {Meyer, Rhonda Christiane and Kusterer, Barbara and Lisec, Jan and Steinfath, Matthias and Becher, Martina and Scharr, Hanno and Melchinger, Albrecht E. and Selbig, Joachim and Schurr, Ulrich and Willmitzer, Lothar and Altmann, Thomas}, title = {QTL analysis of early stage heterosis for biomass in Arabidopsis}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1330}, issn = {1866-8372}, doi = {10.25932/publishup-43127}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-431272}, pages = {11}, year = {2009}, abstract = {The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44\% heterosis for biomass. Mid-parent heterosis in the RILs ranged from -31 to 99\% for dry weight and from -58 to 143\% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7\% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross.}, language = {en} } @article{SteinfathGaertnerLisecetal.2009, author = {Steinfath, Matthias and G{\"a}rtner, Tanja and Lisec, Jan and Meyer, Rhonda Christiane and Altmann, Thomas and Willmitzer, Lothar and Selbig, Joachim}, title = {Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers}, series = {Theoretical and applied genetics : TAG ; international journal of plant breeding research}, volume = {120}, journal = {Theoretical and applied genetics : TAG ; international journal of plant breeding research}, publisher = {Springer}, address = {Berlin}, issn = {0040-5752}, doi = {10.1007/s00122-009-1191-2}, pages = {239 -- 247}, year = {2009}, abstract = {A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80\% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.}, language = {en} } @article{SulpicePylIshiharaetal.2009, author = {Sulpice, Ronan and Pyl, Eva-Theresa and Ishihara, Hirofumi and Trenkamp, Sandra and Steinfath, Matthias and Witucka-Wall, Hanna and Gibon, Yves and Usadel, Bj{\"o}rn and Poree, Fabien and Piques, Maria Conceicao and von Korff, Maria and Steinhauser, Marie Caroline and Keurentjes, Joost J. B. and Guenther, Manuela and Hoehne, Melanie and Selbig, Joachim and Fernie, Alisdair R. and Altmann, Thomas and Stitt, Mark}, title = {Starch as a major integrator in the regulation of plant growth}, issn = {0027-8424}, doi = {10.1073/pnas.0903478106}, year = {2009}, abstract = {Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1- phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.}, language = {en} } @article{LisecSteinfathMeyeretal.2009, author = {Lisec, Jan and Steinfath, Matthias and Meyer, Rhonda C. and Selbig, Joachim and Melchinger, Albrecht E. and Willmitzer, Lothar and Altmann, Thomas}, title = {Identification of heterotic metabolite QTL in Arabidopsis thaliana RIL and IL populations}, issn = {0960-7412}, doi = {10.1111/j.1365-313X.2009.03910.x}, year = {2009}, abstract = {Two mapping populations of a cross between the Arabidopsis thaliana accessions Col-0 and C24 were cultivated and analyzed with respect to the levels of 181 metabolites to elucidate the biological phenomenon of heterosis at the metabolic level. The relative mid-parent heterosis in the F-1 hybrids was <20\% for most metabolic traits. The first mapping population consisting of 369 recombinant inbred lines (RILs) and their test cross progeny with both parents allowed us to determine the position and effect of 147 quantitative trait loci (QTL) for metabolite absolute mid-parent heterosis (aMPH). Furthermore, we identified 153 and 83 QTL for augmented additive (Z(1)) and dominance effects (Z(2)), respectively. We identified putative candidate genes for these QTL using the ARACYC database (http://www.arabidopsis.org/ biocyc), and calculated the average degree of dominance, which was within the dominance and over-dominance range for most metabolites. Analyzing a second population of 41 introgression lines (ILs) and their test crosses with the recurrent parent, we identified 634 significant differences in metabolite levels. Nine per cent of these effects were classified as over-dominant, according to the mode of inheritance. A comparison of both approaches suggested epistasis as a major contributor to metabolite heterosis in Arabidopsis. A linear combination of metabolite levels was shown to significantly correlate with biomass heterosis (r = 0.62).}, language = {en} } @misc{AndorfGaertnerSteinfathetal.2008, author = {Andorf, Sandra and G{\"a}rtner, Tanja and Steinfath, Matthias and Witucka-Wall, Hanna and Altmann, Thomas and Repsilber, Dirk}, title = {Towards systems biology of heterosis}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {949}, issn = {1866-8372}, doi = {10.25932/publishup-43627}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-436274}, pages = {14}, year = {2008}, abstract = {We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity—a known phenomenon in the literature.}, language = {en} }