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The combined knowledge of the Arabidopsis genome and transcriptome now allows to get an integrated view of the dynamics and evolution of metabolic pathways in plants. We used publicly available sets of microarray data obtained in a wide range of different stress and developmental conditions to investigate the co-expression of genes encoding enzymes of secondary metabolism pathways, in particular indoles, phenylpropanoids, and flavonoids. We performed hierarchical clustering of gene expression profiles and found that major enzymes of each pathway display a clear and robust co-expression throughout all the conditions studied. Moreover, detailed analysis evidenced that some genes display co-regulation in particular physiological conditions only, certainly reflecting their modular recruitment into stress- or developmentally regulated biosynthetic pathways. The combination of these microarray data with sequence analysis allows to draw very precise hypotheses on the function of otherwise uncharacterized genes. To illustrate this approach, we focused our analysis on secondary metabolism glycosyltransferases (UGTs), a multigenic family involved in the conjugation of small molecules to sugars like glucose. We propose that UGT74B1 and UGT74C1 may be involved in aromatic and aliphatic glucosinolates synthesis, respectively. We also suggest that UGT75C1 may function as an anthocyanin-5-O-glucosyltransferase in planta. Therefore, this data-mining approach appears very powerful for the functional prediction of unknown genes, and could be transposed to virtually any other gene family. Finally, we suggest that analysis of expression pattern divergence of duplicated genes also provides some insight into the mechanisms of metabolic pathway evolution.

(C)2005 Kluwer Academic Publishers