Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana
Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana
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DOI：
10.1073/pnas.0403218101
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发表时间：
2004-07-06
影响因子：
11.1
通讯作者：
Saito, K
中科院分区：
文献类型：
--
作者：
Hirai, MY;Yano, M;Saito, K
植物新陈代谢是一套复杂的过程，产生各种各样的食物，木材和药物。有了拟南芥和水稻的基因组序列，整合所有“组学”科学的后基因组学研究可以描绘整个细胞过程的精确图像。在这里，我们提出，据我们所知，第一份报告的调查基因代谢物网络调节硫和氮营养和次生代谢在拟南芥中，与代谢组学和转录组学的整合。转录组和代谢组学分析，分别进行了DNA宏阵列和几种化学分析方法，包括超高分辨率傅立叶变换离子回旋质谱。数学分析，包括主成分分析和批量学习自组织图谱分析的转录组和代谢组学数据表明存在的一般反应，硫和氮的缺乏。此外，在几种代谢途径中观察到对硫或氮缺乏的特异性反应：特别是，参与芥子油苷代谢的基因和代谢产物被证明是协调调节的。通过整合转录组学和代谢组学来理解初级和次级代谢中的这种基因-代谢物网络，可以鉴定基因功能并随后改善植物中有用化合物的生产。
Plant metabolism is a complex set of processes that produce a wide diversity of foods, woods, and medicines. With the genome sequences of Arabidopsis and rice in hands, postgenomics studies integrating all "omics" sciences can depict precise pictures of a whole-cellular process. Here, we present, to our knowledge, the first report of investigation for gene-to-metabolite networks regulating sulfur and nitrogen nutrition and secondary metabolism in Arabidopsis, with integration of metabolomics and transcriptomics. Transcriptome and metabolome analyses were carried out, respectively, with DNA macroarray and several chemical analytical methods, including ultra high-resolution Fourier transform-ion cyclotron MS. Mathematical analyses, including principal component analysis and batch-learning self-organizing map analysis of transcriptome and metabolome data suggested the presence of general responses to sulfur and nitrogen deficiencies. In addition, specific responses to either sulfur or nitrogen deficiency were observed in several metabolic pathways: in particular, the genes and metabolites involved in glucosinolate metabolism were shown to be coordinately modulated. Understanding such gene-to-metabolite networks in primary and secondary metabolism through integration of transcriptomics and metabolomics can lead to identification of gene function and subsequent improvement of production of useful compounds in plants.