Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks.

Summary: Plant growth and development are tightly linked to primary metabolism and are subject to natural variation. In order to obtain an insight into the genetic factors controlling biomass and primary metabolism and to determine their relationships, two Arabidopsis thaliana populations [429 recombinant inbred lines (RIL) and 97 introgression lines (IL), derived from accessions Col‐0 and C24] were analyzed with respect to biomass and metabolic composition using a mass spectrometry‐based metabolic profiling approach. Six and 157 quantitative trait loci (QTL) were identified for biomass and metabolic content, respectively. Two biomass QTL coincide with significantly more metabolic QTL (mQTL) than statistically expected, supporting the notion that the metabolic profile and biomass accumulation of a plant are linked. On the same basis, three out the six biomass QTL can be simulated purely on the basis of metabolic composition. QTL based on analysis of the introgression lines were in substantial agreement with the RIL‐based results: five of six biomass QTL and 55% of the mQTL found in the RIL population were also found in the IL population at a significance level of P ≤ 0.05, with >80% agreement on the allele effects. Some of the differences could be attributed to epistatic interactions. Depending on the search conditions, metabolic pathway‐derived candidate genes were found for 24–67% of all tested mQTL in the database AraCyc 3.5. This dataset thus provides a comprehensive basis for the detection of functionally relevant variation in known genes with metabolic function and for identification of genes with hitherto unknown roles in the control of metabolism.

Summary: The metabolic function of the predicted Arabidopsis tyrosine aminotransferase (TAT) encoded by the At5g53970 gene was studied using two independent knock‐out mutants. Gas chromatography‐mass spectrometry based metabolic profiling revealed a specific increase in tyrosine levels, supporting the proposed function of At5g53970 as a tyrosine‐specific aminotransferase not involved in tyrosine biosynthesis, but rather in utilization of tyrosine for other metabolic pathways. The TAT activity of the At5g53970‐encoded protein was verified by complementation of the Escherichia coli tyrosine auxotrophic mutant DL39, and in vitro activity of recombinantly expressed and purified At5g53970 was found to be specific for tyrosine. To investigate the physiological role of At5g53970, the consequences of reduction in tyrosine utilization on metabolic pathways having tyrosine as a substrate were analysed. We found that tocopherols were substantially reduced in the mutants and we conclude that At5g53970 encodes a TAT important for the synthesis of tocopherols in Arabidopsis.