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促进水稻功能基因组学研究的系统生物学基础设施。

Infrastructures of systems biology that facilitate functional genomic study in rice.

作者信息

Hong Woo-Jong, Kim Yu-Jin, Chandran Anil Kumar Nalini, Jung Ki-Hong

机构信息

Graduate School of Biotechnology & Crop Biotech Institute, Kyung Hee University, Yongin, 17104, Korea.

出版信息

Rice (N Y). 2019 Mar 14;12(1):15. doi: 10.1186/s12284-019-0276-z.

Abstract

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced.To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

摘要

水稻(Oryza sativa L.)既是全球人口的主要主食,也是用于研究具有重要农艺性状作用模式的模式作物,能提供可应用于其他作物的信息。由于下一代测序和质谱等高通量技术的发展,水稻中积累了大量的多组学数据。通过整合这些数据,水稻系统生物学正变得更加先进。为促进这种系统方法,我们总结了水稻系统生物学的当前资源,如数据库和工具。在本综述中,我们使用六个组学水平对资源进行分类:基因组学、转录组学、蛋白质组学、代谢组学、整合组学和功能基因组学。我们提供每个数据库或工具的名称、网站、参考文献、工作状态和引用次数,并讨论水稻基因功能综合理解的未来前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/6419666/f1a79be41cac/12284_2019_276_Fig1_HTML.jpg

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