National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.
College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China.
Gigascience. 2018 Jan 1;7(1):1-9. doi: 10.1093/gigascience/gix119.
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.
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/).
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.
作为主要主食，水稻也是单子叶植物功能基因组研究的模式植物。解析水稻基因组的每一个 DNA 元件对于满足不断增长的粮食需求的遗传改良至关重要。在过去的 15 年中，水稻功能基因组学取得了非凡的进展。对每一个水稻基因的系统特征描述和适当的沉积对于功能研究和作物遗传改良都是至关重要的。
我们通过整合来自现有数据库的数据和审查每一篇关于水稻功能基因组学研究的文献，构建了一个约 2800 个功能表征的水稻基因和约 5000 个不同基因家族成员的综合而准确的数据集。该数据集占 39045 个注释的水稻蛋白编码基因的 19.2%，为研究水稻基因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 个基因互作网络。最大的网络有 762 个基因，表明多效基因连接了不同的生物途径。在亲缘关系较近的植物中，开花途径的保守程度不断增加，这表明水稻基因对于未来在其他作物中解析开花调控具有重要价值。所有数据都存储在 funRiceGenes 数据库中（https://funricegenes.github.io/）。一个闪亮的应用程序（http://funricegenes.ncpgr.cn/）提供了高级搜索和数据库持续更新的功能。
funRiceGenes 数据集将使我们能够进一步探索基因功能与水稻自然变异之间的交叉，这也将有助于设计育种以提高水稻的目标农艺性状。
