Metabolomic Characterization of Knockout Mutants in Arabidopsis: Development of a Metabolite Profiling Database for Knockout Mutants in Arabidopsis
Metabolomic Characterization of Knockout Mutants in Arabidopsis: Development of a Metabolite Profiling Database for Knockout Mutants in Arabidopsis
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DOI：
10.1104/pp.114.240986
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发表时间：
2014-07-01
期刊：
影响因子：
7.4
通讯作者：
Saito, Kazuki
中科院分区：
文献类型：
--
作者：
Fukushima, Atsushi;Kusano, Miyako;Saito, Kazuki
尽管最近在功能基因组学方面进行了大量的研究，但只有有限数量的拟南芥（Arabidopsis thaliana）基因的功能已经通过实验确定，并且改进基因注释仍然是植物科学中的主要挑战。由于代谢物谱分析可以表征植物代谢中遗传扰动的代谢组学表型，因此它提供了感兴趣基因的功能的线索。我们选择了50个拟南芥突变体，包括一组特征和未特征化的突变体，类似于野生型植物。我们使用气相色谱-质谱法进行植物的代谢产物分析。为了使数据集可作为一个有效的公共功能基因组学工具的假设生成，我们开发了代谢产物分析数据库敲除突变体在拟南芥（MeKO）。它允许评估突变是否影响正常植物生长期间的代谢，并包含突变体的图像，代谢物积累差异的数据和交互式分析工具。未经处理的数据，包括色谱图，质谱和实验元数据，遵循代谢组学标准倡议制定的指导方针，可免费下载。概念验证分析表明，MeKO对于产生感兴趣的基因的假设和改进基因注释非常有用。MeKO可在http://prime.psc.riken.jp/meko/上公开获取。
Despite recent intensive research efforts in functional genomics, the functions of only a limited number of Arabidopsis (Arabidopsis thaliana) genes have been determined experimentally, and improving gene annotation remains a major challenge in plant science. As metabolite profiling can characterize the metabolomic phenotype of a genetic perturbation in the plant metabolism, it provides clues to the function(s) of genes of interest. We chose 50 Arabidopsis mutants, including a set of characterized and uncharacterized mutants, that resemble wild-type plants. We performed metabolite profiling of the plants using gas chromatography-mass spectrometry. To make the data set available as an efficient public functional genomics tool for hypothesis generation, we developed the Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO). It allows the evaluation of whether a mutation affects metabolism during normal plant growth and contains images of mutants, data on differences in metabolite accumulation, and interactive analysis tools. Nonprocessed data, including chromatograms, mass spectra, and experimental metadata, follow the guidelines set by the Metabolomics Standards Initiative and are freely downloadable. Proof-of-concept analysis suggests that MeKO is highly useful for the generation of hypotheses for genes of interest and for improving gene annotation. MeKO is publicly available at http://prime.psc.riken.jp/meko/.