title: The metabolic signature related to high plant growth rate in Arabidopsis thaliana.
abstract: The decline of available fossil fuel reserves has triggered world-wide efforts to develop alternative energy sources based on plant biomass. Detailed knowledge of the relations of metabolism and biomass accumulation can be expected to yield powerful novel tools to accelerate and enhance energy plant breeding programs. We used metabolic profiling in the model Arabidopsis to study the relation between biomass and metabolic composition using a recombinant inbred line (RIL) population. A highly significant canonical correlation (0.73) was observed, revealing a close link between biomass and a specific combination of metabolites. Dividing the entire data set into training and test sets resulted in a median correlation between predicted and true biomass of 0.58. The demonstrated high predictive power of metabolic composition for biomass features this composite measure as an excellent biomarker and opens new opportunities to enhance plant breeding specifically in the context of renewable resources.
authors.affiliation: Department of Genetics, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Strasse 24-25, 14476 Potsdam, Germany. rcmeyer@uni-potsdam.de
authors.forename: Rhonda C
authors.initials: RC
authors.lastname: Meyer
authors.forename: Matthias
authors.initials: M
authors.lastname: Steinfath
authors.forename: Jan
authors.initials: J
authors.lastname: Lisec
authors.forename: Martina
authors.initials: M
authors.lastname: Becher
authors.forename: Hanna
authors.initials: H
authors.lastname: Witucka-Wall
authors.forename: Ottó
authors.initials: O
authors.lastname: Törjék
authors.forename: Oliver
authors.initials: O
authors.lastname: Fiehn
authors.forename: Anne
authors.initials: A
authors.lastname: Eckardt
authors.forename: Lothar
authors.initials: L
authors.lastname: Willmitzer
authors.forename: Joachim
authors.initials: J
authors.lastname: Selbig
authors.forename: Thomas
authors.initials: T
authors.lastname: Altmann
mesh_terms: D017360:Arabidopsis / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000737:chemistry* / Q000378:metabolism; D015415:Biomarkers / Q000378:metabolism; D018533:Biomass; D017343:Genes, Plant; D053858:Metabolic Networks and Pathways; D015999:Multivariate Analysis; D010641:Phenotype; D018521:Plant Physiological Phenomena; D040901:Proteomics / Q000379:methods; D011994:Recombinant Proteins / Q000737:chemistry
chemical_list: D029681:Arabidopsis Proteins; D015415:Biomarkers; D011994:Recombinant Proteins