Metabolite profiling for plant functional genomics

Multiparallel analyses of mRNA and proteins are central to today's function al genomics initiatives. We describe here the use of metabolite profiling a s a new tool for a comparative display of gene function. It has the potenti al not only to provide deeper insight into complex regulatory processes but also to determine phenotype directly. Using gas chromatography/mass spectr ometry (GC/MS), we automatically quantified 326 distinct compounds from Ara bidopsis thaliana leaf extracts. It was possible to assign a chemical struc ture to approximately half of these compounds. Comparison of four Arabidops is genotypes (two homozygous ecotypes and a mutant of each ecotype) showed that each genotype possesses a distinct metabolic profile. Data mining tool s such as principal component analysis enabled the assignment of "metabolic phenotypes" using these large data sets. The metabolic phenotypes of the t wo ecotypes were more divergent than were the metabolic phenotypes of the s ingle-loci mutant and their parental ecotypes. These results demonstrate th e use of metabolite profiling as a tool to significantly extend and enhance the power of existing functional genomics approaches.