Int J Biol Sci 2022; 18(6):2472-2483. doi:10.7150/ijbs.69458 This issue

Research Paper

REIA: A database for cancer A-to-I RNA editing with interactive analysis

Huimin Zhu1*, Lu Huang1*, Songbin Liu2*, Zhiming Dai3*, Zhou Songyang1, Zhihui Weng4, Yuanyan Xiong1✉

1. Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510006, China.
2. School of Automation, Guangdong University of Technology, Guangzhou, 510006, China.
3. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510006, China.
4. Faculty of Health Sciences, University of Macau, Macau, 999078, China.
*These authors contribute equally to this work.

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Citation:
Zhu H, Huang L, Liu S, Dai Z, Songyang Z, Weng Z, Xiong Y. REIA: A database for cancer A-to-I RNA editing with interactive analysis. Int J Biol Sci 2022; 18(6):2472-2483. doi:10.7150/ijbs.69458. Available from https://www.ijbs.com/v18p2472.htm

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Abstract

Graphic abstract

Epitranscriptomic changes caused by adenosine-to-inosine (A-to-I) RNA editing contribute to the pathogenesis of human cancers; however, only a small fraction of the millions editing sites detected so far has clear functionality. To facilitate more in-depth studies on the editing, this paper offers REIA (http://bioinfo-sysu.com/reia), an interactive web server that analyses and visualizes the association between human cancers and A-to-I RNA editing sites (RESs). As a comprehensive database, REIA curates not only 8,447,588 RESs from 9,895 patients across 34 cancers, where 33 are from TCGA and 1 from GEO, but also 13 different types of multi-omic data for the cancers. As an interactive server, REIA provides various options for the user to specify the interested sites, to browse their annotation/editing level/profile in cancer, and to compare the difference in multi-omic features between editing and non-editing groups. From the editing profiles, REIA further detects 658 peptides that are supported by mass spectrum data but not yet covered in any prior works.

Keywords: A-to-I RNA editing, Cancer, Interactive analysis, Multi-omics, Database