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Metabolic profiles and fingerprints of Arabidopsis thaliana plants with various defects in photosynthesis or plastidic carbohydrate metabolism were generated 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 metabolite targets including major carbohydrates, phosphorylated intermediates, carboxylates, free aminoacids, 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 as mirrored in their metabolic status. These pleiotropic responses are specific 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.