funRiceGenes dataset for comprehensive understanding and application of rice functional genes.
funRiceGenes dataset for comprehensive understanding and application of rice functional genes.
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funRiceGenes数据集，全面理解和应用水稻功能基因
DOI：
10.1093/gigascience/gix119
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发表时间：
2018-01-01
期刊：
影响因子：
9.2
通讯作者：
Ouyang Y
中科院分区：
文献类型：
--
作者：
Yao W;Li G;Yu Y;Ouyang Y
摘要 背景水稻作为主要主粮，也是单子叶植物功能基因组研究的模式植物。解码水稻基因组的每个 DNA 元素对于遗传改良以满足日益增长的粮食需求至关重要。过去 15 年见证了水稻功能基因组学的非凡进展。每个水稻基因的系统表征和正确沉积对于功能研究和作物遗传改良都至关重要。研究结果 通过整合现有数据库中的数据并审查有关水稻功能基因组研究的每一篇出版物，我们建立了约 2800 个具有功能特征的水稻基因和约 5000 个不同基因家族成员的全面而准确的数据集。该数据集占 39 045 个带注释的蛋白质编码水稻基因的 19.2%，为研究水稻基因的功能提供了最详尽的档案。我们还基于 1310 个基因之间的 1841 个连接构建了 214 个基因相互作用网络。拥有 762 个基因的最大网络表明多效性基因将不同的生物途径联系起来。在更密切相关的植物中观察到开花途径的保守程度不断增加，这意味着水稻基因对于未来解析其他作物的开花调控具有重要价值。所有数据都存放在funRiceGenes数据库中（https://funricegenes.github.io/）。 Shiny 应用程序 (http://funricegenes.ncpgr.cn/) 提供高级搜索和数据库持续更新的功能。结论 funRiceGenes 数据集将有助于进一步探索水稻基因功能与自然变异之间的交联，也有助于育种设计以改善水稻的目标农艺性状。
Abstract Background As a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement. Findings We built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/). Conclusions The funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice.
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