Metabolomics-based post-genome science in plants

组学的综合分析可以为基因功能的鉴定提供线索，并提供基因-代谢物和/或代谢物-代谢物网络的精确信息。我们在拟南芥中运行了结合代谢组和转录组的功能基因组学项目。氮、硫营养胁迫导致代谢物组的整体变化，这可能与基因表达调控有关，表明硫苷生物合成中存在基因-代谢物网络。花青苷高产拟南芥品系的基因表达和代谢谱揭示了负责花青苷修饰和储存的新基因的功能。通过对T-DNA插入序列和重组蛋白的分析，对这些基因的功能进行了鉴定。通过扩展这一策略，我们使用了一个公开的转录组数据库，用于未知基因和网络的功能鉴定。在这些共表达分析的基础上，构建了特定代谢途径中共表达基因的模型，从而推测了这些基因的功能，随后用反向遗传学策略进行了证实。通过采用质谱的代谢组分析平台对感兴趣的基因的敲除突变体进行广泛的代谢分析。对突变体的代谢产物分析揭示了突变体代谢类型的变化，表明了基因的功能。这种代谢组和转录组相结合的分析策略不仅适用于模式植物A。thaliana，但也为未开发的植物，预计丰富的各种phychemicals。

Integrated analysis of omics can provide the clues for identification of gene function and precise information about gene-to-metabolite and/or metabolite-to-metabolite networks. We ran the functional genomics project combining metabolome and transcriptome in Arabidopsis thaliana. Nutritional stress of nitrogen and sulfur resulted in global change of metabolome that could be correlated with the modulation of gene expression, indicating the presence of gene-to-metabolite networks, in particular, in glucosinolate biosynthesis. The comprehensive gene expression and metabolite profiles of anthocyanin overproducing Arabidopsis lines revealed the function of novel genes that are responsible for modification and storage of anthocyanins. The function of those genes was identified by analysis of the T-DNA insertion lines and recombinant proteins. By expanding this strategy, we used a transcriptome database publicly available for functional identification of unknown genes and networks. Upon these co-expression analyses, the models of co-expressed genes in particular metabolic pathways were constructed, leading to speculation of functions of those genes followed by confirmation with reverse genetics strategy. Extensive metabolic profiling of the knockout mutants of genes of interest was performed by a metabolome-analytical platform employing mass spectrometry. Detailed metabolite analysis of the mutants revealed the changes in metabolo-types, indicating the gene functions. This strategy of integrated analysis of metabolome and transcriptome is applicable to decipher the function of genes not only for a model plant A. thaliana but also for unexplored plants expected rich with a variety of phychemicals.