Literature DB >> 27694136

RNAEditor: easy detection of RNA editing events and the introduction of editing islands.

David John, Tyler Weirick, Stefanie Dimmeler, Shizuka Uchida.   

Abstract

RNA editing of adenosine residues to inosine ('A-to-I editing') is the most common RNA modification event detectible with RNA sequencing (RNA-seq). While not directly detectable, inosine is read by next-generation sequencers as guanine. Therefore, mapping RNA-seq reads to their corresponding reference genome can detect potential editing events by identifying 'A-to-G' conversions. However, one must exercise caution when searching for editing sites, as A-to-G conversions also arise from sequencing errors as well as mutations. To address these complexities, several algorithms and software products have been developed to accurately identify editing events. Here, we survey currently available methods to analyze RNA editing events and introduce a new easy-to-use bioinformatics tool 'RNAEditor' for the detection of RNA editing events. During the development of RNAEditor, we noticed editing often happened in clusters, which we named 'editing islands'. We developed a clustering algorithm to find editing islands and included it in RNAEditor. RNAEditor is freely available at http://rnaeditor.uni-frankfurt.de. We anticipate that RNAEditor will provide biologists with an easy-to-use tool for studying RNA editing events and the newly defined editing islands.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  RNA editing; RNA modification; editing island; software

Mesh:

Year:  2017        PMID: 27694136     DOI: 10.1093/bib/bbw087

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  28 in total

Review 1.  Single-nucleotide variants in human RNA: RNA editing and beyond.

Authors:  Yan Guo; Hui Yu; David C Samuels; Wei Yue; Scott Ness; Ying-Yong Zhao
Journal:  Brief Funct Genomics       Date:  2019-02-14       Impact factor: 4.241

Review 2.  RNA Editing: Unexplored Opportunities in the Cardiovascular System.

Authors:  Shizuka Uchida; Steven P Jones
Journal:  Circ Res       Date:  2018-02-02       Impact factor: 17.367

3.  EditPredict: Prediction of RNA editable sites with convolutional neural network.

Authors:  Jiandong Wang; Scott Ness; Roger Brown; Hui Yu; Olufunmilola Oyebamiji; Limin Jiang; Quanhu Sheng; David C Samuels; Ying-Yong Zhao; Jijun Tang; Yan Guo
Journal:  Genomics       Date:  2021-09-23       Impact factor: 4.310

4.  An Evolutionary Landscape of A-to-I RNA Editome across Metazoan Species.

Authors:  Li-Yuan Hung; Yen-Ju Chen; Te-Lun Mai; Chia-Ying Chen; Min-Yu Yang; Tai-Wei Chiang; Yi-Da Wang; Trees-Juen Chuang
Journal:  Genome Biol Evol       Date:  2018-02-01       Impact factor: 3.416

5.  Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

Authors:  Zhangyi Ouyang; Feng Liu; Chenghui Zhao; Chao Ren; Gaole An; Chuan Mei; Xiaochen Bo; Wenjie Shu
Journal:  Sci Rep       Date:  2018-04-16       Impact factor: 4.379

6.  SPRINT: an SNP-free toolkit for identifying RNA editing sites.

Authors:  Feng Zhang; Yulan Lu; Sijia Yan; Qinghe Xing; Weidong Tian
Journal:  Bioinformatics       Date:  2017-11-15       Impact factor: 6.937

7.  Profiling of hepatocellular carcinoma neoantigens reveals immune microenvironment and clonal evolution related patterns.

Authors:  Zhenli Li; Geng Chen; Zhixiong Cai; Xiuqing Dong; Lei He; Liman Qiu; Yongyi Zeng; Xiaolong Liu; Jingfeng Liu
Journal:  Chin J Cancer Res       Date:  2021-06-30       Impact factor: 5.087

Review 8.  Elucidating the Functions of Non-Coding RNAs from the Perspective of RNA Modifications.

Authors:  Venkata Naga Srikanth Garikipati; Shizuka Uchida
Journal:  Noncoding RNA       Date:  2021-05-11

9.  High-Throughput Methods to Detect Long Non-Coding RNAs.

Authors:  Shizuka Uchida
Journal:  High Throughput       Date:  2017-08-31

Review 10.  Long Non-coding RNAs in Endothelial Biology.

Authors:  Tyler Weirick; Giuseppe Militello; Shizuka Uchida
Journal:  Front Physiol       Date:  2018-05-14       Impact factor: 4.566

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