Arabidopsis 2010: Metabolomics: A Functional Genomics Tool for Deciphering Functions of Arabidopsis Genes in the Context of Metabolic and Regulatory Networks

拟南芥基因组中超过1/3的已注释蛋白编码基因的功能尚不清楚，更大一部分基因组的注释不够准确，无法在生化和生理水平上明确功能分配。该项目将汇集多学科合作者的联盟，建立生成代谢组学数据流的管道，并提供由此产生的综合数据集的统计和计算解释。目标是发展代谢物分析能力，这将提高研究界制定有关拟南芥基因功能的可测试假设的能力。该联盟开发了代谢组学平台，共同检测大约1800种代谢物，其中900种是化学定义的。该项目的目的是应用这些已建立的代谢物分析平台来揭示与多达200个未知功能的拟南芥基因敲除突变相关的代谢组变化，并将这些变化与50个已知功能基因的类似突变进行比较。该联盟将通过现有的多功能代谢组学数据库www.plantmetabolomics.org传播这些数据。该数据库的增强以及相关的统计和可视化工具集将使研究人员能够制定拟南芥代谢网络的可测试计算模型。这些目标的成功完成以及与其他nsf赞助的功能基因组学和网络基础设施开发的整合将为最终模拟拟南芥的复杂代谢产生转型资源。更广泛的影响该项目将为研究界开发新的资源，从而提高在代谢物水平上全球分析基因组表达的能力。这些代谢物资源与其他nsf资助的资源开发项目合作，将使社区的研究人员能够制定有关基因功能的可信、可测试的假设。该项目将通过研讨会、实习和组织国内和国际会议，促进代谢组学作为功能基因组学工具的发展。该项目还将发展新的活动，通过在联合实验室和国际生物学会议上为研究人员举办讲习班来加强科学教育和培训在社区中的影响。此外，将为本科生提供研究实习机会，其中8名学生将有机会在欧洲基因组学实验室体验国际科学培训。这些以研究为基础的培训实习将向学生展示化学、生物化学、遗传学、生物信息学和计算科学的综合应用在解决复杂生物问题方面的协同作用。

The functions of over 1/3 of the annotated protein-coding genes of the Arabidopsis genome are still unknown, and the annotation of an even larger portion of the genome is not sufficiently accurate for unambiguous assignment of function at the biochemical and physiological levels. This project will bring together a consortium of multidisciplinary collaborators to establish pipelines for generating metabolomics data-streams and to provide statistical and computational interpretation of the resulting integrated datasets. The goal is to develop metabolite-profiling capabilities that will enhance the research community's ability to formulate testable hypotheses concerning Arabidopsis gene functions. The consortium has developed metabolomic platforms that together detect approximately 1,800 metabolites, of which 900 are chemically defined. The aim of the project is to apply these established metabolite-profiling platforms to reveal changes in the metabolome associated with knockout mutations in up to 200 Arabidopsis genes of unknown function and compare these to similar mutants in 50 genes of known function. The consortium will disseminate these data via the existing multi-functional metabolomics database: www.plantmetabolomics.org. Enhancement of this database and associated statistical and visualization toolsets will enable researchers to formulate testable computational models of the metabolic network of Arabidopsis. The successful completion of these goals and integration with other NSF-sponsored functional genomics and cyber infrastructure developments will generate transformational resources for ultimately modeling the complex metabolism of Arabidopsis. Broader ImpactsThe project will develop new resources for the research community that will enhance the capability to globally profile genome expression at the metabolite level. These metabolite resources, in collaboration with other NSF-funded resource development projects, will enable researchers in the community to formulate credible, testable hypotheses concerning gene function. The project will foster the development of the science of metabolomics as a functional genomics tool through workshops, internships and organization of national and international meetings. The project will also develop new activities to enhance the impact of science education and training in the community, by conducting workshops for researchers at consortium labs and at international biological meetings. In addition, research internships will be offered to undergraduate students, eight of whom will have the opportunity to experience international science training in a European genomics laboratory. These research-based training internships will illustrate to the students the synergy that accompanies the integrated applications of chemistry, biochemistry, genetics, bioinformatics and computational sciences to solving complex biological problems.