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代谢组学在功能基因组学、系统生物学和生物技术中的应用。

Metabolomics for functional genomics, systems biology, and biotechnology.

机构信息

RIKEN Plant Science Center, Tsurumi-ku, Yokohama, Japan.

出版信息

Annu Rev Plant Biol. 2010;61:463-89. doi: 10.1146/annurev.arplant.043008.092035.

Abstract

Metabolomics now plays a significant role in fundamental plant biology and applied biotechnology. Plants collectively produce a huge array of chemicals, far more than are produced by most other organisms; hence, metabolomics is of great importance in plant biology. Although substantial improvements have been made in the field of metabolomics, the uniform annotation of metabolite signals in databases and informatics through international standardization efforts remains a challenge, as does the development of new fields such as fluxome analysis and single cell analysis. The principle of transcript and metabolite cooccurrence, particularly transcriptome coexpression network analysis, is a powerful tool for decoding the function of genes in Arabidopsis thaliana. This strategy can now be used for the identification of genes involved in specific pathways in crops and medicinal plants. Metabolomics has gained importance in biotechnology applications, as exemplified by quantitative loci analysis, prediction of food quality, and evaluation of genetically modified crops. Systems biology driven by metabolome data will aid in deciphering the secrets of plant cell systems and their application to biotechnology.

摘要

代谢组学在基础植物生物学和应用生物技术中发挥着重要作用。植物共同产生了大量的化学物质,远远超过大多数其他生物产生的物质;因此,代谢组学在植物生物学中非常重要。尽管代谢组学领域取得了实质性的进展,但通过国际标准化努力,在数据库和信息学中对代谢物信号进行统一注释仍然是一个挑战,通量分析和单细胞分析等新领域的发展也是如此。转录物和代谢物共同出现的原则,特别是转录组共表达网络分析,是解码拟南芥基因功能的有力工具。该策略现在可用于鉴定作物和药用植物中特定途径相关的基因。代谢组学在生物技术应用中变得越来越重要,例如定量位点分析、预测食品质量和评估转基因作物。基于代谢组学数据的系统生物学将有助于破译植物细胞系统的秘密,并将其应用于生物技术。

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