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IC4R-2.0: Rice Genome Reannotation Using Massive RNA-seq Data.
Genomics, Proteomics & Bioinformatics ( IF 9.5 ) Pub Date : 2020-07-16 , DOI: 10.1016/j.gpb.2018.12.011
Jian Sang 1 , Dong Zou 2 , Zhennan Wang 3 , Fan Wang 2 , Yuansheng Zhang 1 , Lin Xia 1 , Zhaohua Li 1 , Lina Ma 2 , Mengwei Li 1 , Bingxiang Xu 4 , Xiaonan Liu 1 , Shuangyang Wu 4 , Lin Liu 1 , Guangyi Niu 1 , Man Li 1 , Yingfeng Luo 4 , Songnian Hu 4 , Lili Hao 2 , Zhang Zhang 1
Affiliation  

Genome reannotation aims for complete and accurate characterization of gene models and thus is of critical significance for in-depth exploration of gene function. Although the availability of massive RNA-seq data provides great opportunities for gene model refinement, few efforts have been made to adopt these precious data in rice genome reannotation. Here we reannotate the rice (Oryza sativa L. ssp. japonica) genome based on integration of large-scale RNA-seq data and release a new annotation system IC4R-2.0. In general, IC4R-2.0 significantly improves the completeness of gene structure, identifies a number of novel genes, and integrates a variety of functional annotations. Furthermore, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) are systematically characterized in the rice genome. Performance evaluation shows that compared to previous annotation systems, IC4R-2.0 achieves higher integrity and quality, primarily attributable to massive RNA-seq data applied in genome annotation. Consequently, we incorporate the improved annotations into the Information Commons for Rice (IC4R), a database integrating multiple omics data of rice, and accordingly update IC4R by providing more user-friendly web interfaces and implementing a series of practical online tools. Together, the updated IC4R, which is equipped with the improved annotations, bears great promise for comparative and functional genomic studies in rice and other monocotyledonous species. The IC4R-2.0 annotation system and related resources are freely accessible at http://ic4r.org/.



中文翻译:

IC4R-2.0:使用大量RNA序列数据对水稻基因组进行重新注释。

基因组重注释旨在完整,准确地表征基因模型,因此对于深入探索基因功能具有至关重要的意义。尽管可获得大量的RNA-seq数据为基因模型的完善提供了巨大的机会,但很少有人努力在水稻基因组重新注释中采用这些宝贵的数据。在这里,我们reannotate稻(L. SSP 。粳)基于大规模RNA-seq数据整合的基因组,并发布了新的注释系统IC4R-2.0。通常,IC4R-2.0可以显着提高基因结构的完整性,识别许多新基因,并整合各种功能注释。此外,水稻基因组中系统地鉴定了长的非编码RNA(lncRNA)和环状RNA(circRNA)。性能评估表明,与以前的注释系统相比,IC4R-2.0具有更高的完整性和质量,主要归因于基因组注释中应用的大量RNA-seq数据。因此,我们将改进的注释纳入了水稻信息共享(IC4R),该数据库集成了水稻的多个组学数据,并通过提供更加用户友好的Web界面并实现了一系列实用的在线工具来相应地更新IC4R。总之,更新的IC4R带有改进的注释,对水稻和其他单子叶植物物种的比较和功能基因组研究具有广阔的前景。可从http://ic4r.org/免费访问IC4R-2.0注释系统和相关资源。

更新日期:2020-07-16
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