@misc{SchmaelzlinDongenKlimantetal.2005,
  author    = {Schm{\"a}lzlin, Elmar and Dongen, Joost T. van and Klimant, Ingo and Marmod{\´e}e, Bettina and Steup, Martin and Fishahn, Joachim and Geigenberger, Peter and L{\"o}hmannsr{\"o}ben, Hans-Gerd},
  title     = {An optical multifrequency phase-modulation method using microbeads for measuring intracellular oxygen concentrations in plants},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-12232},
  year      = {2005},
  abstract  = {A technique has been developed to measure absolute intracellular oxygen concentrations in green plants. Oxygen-sensitive phosphorescent microbeads were injected into the cells and an optical multifrequency phase-modulation technique was used to discriminate the sensor signal from the strong autofluorescence of the plant tissue. The method was established using photosynthesis-competent cells of the giant algae Chara corallina L., and was validated by application to various cell types of other plant species.},
  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}
}
@article{PaparelliGonzaliParlantietal.2012,
  author    = {Paparelli, Eleonora and Gonzali, Silvia and Parlanti, Sandro and Novi, Giacomo and Giorgi, Federico M. and Licausi, Francesco and Kosmacz, Monika and Feil, Regina and Lunn, John Edward and Brust, Henrike and van Dongen, Joost T. and Steup, Martin and Perata, Pierdomenico},
  title     = {Misexpression of a chloroplast aspartyl protease leads to severe growth defects and alters carbohydrate metabolism in arabidopsis},
  series = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  volume    = {160},
  journal   = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  number    = {3},
  publisher = {American Society of Plant Physiologists},
  address   = {Rockville},
  issn      = {0032-0889},
  doi       = {10.1104/pp.112.204016},
  pages     = {1237 -- 1250},
  year      = {2012},
  abstract  = {The crucial role of carbohydrate in plant growth and morphogenesis is widely recognized. In this study, we describe the characterization of nana, a dwarf Arabidopsis (Arabidopsis thaliana) mutant impaired in carbohydrate metabolism. We show that the nana dwarf phenotype was accompanied by altered leaf morphology and a delayed flowering time. Our genetic and molecular data indicate that the mutation in nana is due to a transfer DNA insertion in the promoter region of a gene encoding a chloroplast-located aspartyl protease that alters its pattern of expression. Overexpression of the gene (oxNANA) phenocopies the mutation. Both nana and oxNANA display alterations in carbohydrate content, and the extent of these changes varies depending on growth light intensity. In particular, in low light, soluble sugar levels are lower and do not show the daily fluctuations observed in wild-type plants. Moreover, nana and oxNANA are defective in the expression of some genes implicated in sugar metabolism and photosynthetic light harvesting. Interestingly, some chloroplast-encoded genes as well as genes whose products seem to be involved in retrograde signaling appear to be down-regulated. These findings suggest that the NANA aspartic protease has an important regulatory function in chloroplasts that not only influences photosynthetic carbon metabolism but also plastid and nuclear gene expression.},
  language  = {en}
}