Detecting Functional Groups of Arabidopsis Mutants by Metabolic Profiling and Evaluation of Pleiotropic Responses

Metabolic profiles and fingerprints of Arabidopsis thaliana plants with various defects in plastidic sugar metabolism or photosynthesis were analyzed to elucidate if the genetic mutations can be traced by comparing their metabolic status. Using a platform of chromatographic and spectrometric tools data from untargeted full MS scans as well as from selected metabolites including major carbohydrates, phosphorylated intermediates, carboxylates, free amino acids, major antioxidants, and plastidic pigments were evaluated. Our key observations are that by multivariate statistical analysis each mutant can be separated by a unique metabolic signature. Closely related mutants come close. Thus metabolic profiles of sugar mutants are different but more similar than those of photosynthesis mutants. All mutants show pleiotropic responses mirrored in their metabolic status. These pleiotropic responses are typical and can be used for separating and grouping of the mutants. Our findings show that metabolite fingerprints can be taken to classify mutants and hence may be used to sort genes into functional groups.

• Publication year

  2011

• Venue

  Frontiers in Plant Science

• Publication date

  2011-11-23

• Fields of study

  Biology, Medicine, Environmental Science

• Identifiers
  DOI 10.3389/fpls.2011.00082PMID 22639613PMCID 3355665
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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