Sun Yongmei, Li Xing, Wu Di, Pan Qi, Ji Yuefeng, Ren Hong, Ding Keyue
School of Information and Communication Engineering, Beijing University of Posts & Telecommunications, Beijing, P. R. China.
Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
PLoS One. 2016 Mar 1;11(3):e0150465. doi: 10.1371/journal.pone.0150465. eCollection 2016.
RNA editing is one of the post- or co-transcriptional processes that can lead to amino acid substitutions in protein sequences, alternative pre-mRNA splicing, and changes in gene expression levels. Although several methods have been suggested to identify RNA editing sites, there remains challenges to be addressed in distinguishing true RNA editing sites from its counterparts on genome and technical artifacts. In addition, there lacks a software framework to identify and visualize potential RNA editing sites. Here, we presented a software - 'RED' (RNA Editing sites Detector) - for the identification of RNA editing sites by integrating multiple rule-based and statistical filters. The potential RNA editing sites can be visualized at the genome and the site levels by graphical user interface (GUI). To improve performance, we used MySQL database management system (DBMS) for high-throughput data storage and query. We demonstrated the validity and utility of RED by identifying the presence and absence of C→U RNA-editing sites experimentally validated, in comparison with REDItools, a command line tool to perform high-throughput investigation of RNA editing. In an analysis of a sample data-set with 28 experimentally validated C→U RNA editing sites, RED had sensitivity and specificity of 0.64 and 0.5. In comparison, REDItools had a better sensitivity (0.75) but similar specificity (0.5). RED is an easy-to-use, platform-independent Java-based software, and can be applied to RNA-seq data without or with DNA sequencing data. The package is freely available under the GPLv3 license at http://github.com/REDetector/RED or https://sourceforge.net/projects/redetector.
RNA编辑是一种转录后或共转录过程,可导致蛋白质序列中的氨基酸替换、前体mRNA可变剪接以及基因表达水平的变化。尽管已经提出了几种方法来识别RNA编辑位点,但在区分真正的RNA编辑位点与基因组上的对应位点和技术假象方面仍存在挑战。此外,缺乏一个用于识别和可视化潜在RNA编辑位点的软件框架。在这里,我们展示了一款名为“RED”(RNA编辑位点检测器)的软件,它通过整合多个基于规则和统计的过滤器来识别RNA编辑位点。潜在的RNA编辑位点可以通过图形用户界面(GUI)在基因组和位点水平上进行可视化。为了提高性能,我们使用MySQL数据库管理系统(DBMS)进行高通量数据存储和查询。与REDItools(一种用于进行RNA编辑高通量研究的命令行工具)相比,我们通过实验验证了C→U RNA编辑位点的存在与否,从而证明了RED的有效性和实用性。在对一个包含28个经实验验证的C→U RNA编辑位点的样本数据集进行分析时,RED的灵敏度和特异性分别为0.64和0.5。相比之下,REDItools具有更好的灵敏度(0.75)但特异性相似(0.5)。RED是一款易于使用、基于Java且与平台无关的软件,可应用于有无DNA测序数据的RNA-seq数据。该软件包可在GPLv3许可下免费获取,网址为http://github.com/REDetector/RED或https://sourceforge.net/projects/redetector 。