RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data. Issue Volume 44:Issue D1(2016) (12th October 2015)

• Record Type: Journal Article
• Authors: Sun, Wen-Ju; Li, Jun-Hao; Liu, Shun; Wu, Jie; Zhou, Hui; Qu, Liang-Hu; Yang, Jian-Hua
• Is Part Of: Nucleic acids research. Volume 44:Issue D1(2016)
• Page Start: D259
• Page End: D265
• Publication Date: 2015-10-12
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkv1036
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Although more than 100 different types of RNA modifications have been characterized across all living organisms, surprisingly little is known about the modified positions and their functions. Recently, various high-throughput modification sequencing methods have been developed to identify diverse post-transcriptional modifications of RNA molecules. In this study, we developed a novel resource, RMBase (R NA M odification Base, http://mirlab.sysu.edu.cn/rmbase/ ), to decode the genome-wide landscape of RNA modifications identified from high-throughput modification data generated by 18 independent studies. The current release of RMBase includes ∼9500 pseudouridine (Ψ) modifications generated from Pseudo-seq and CeU-seq sequencing data, ∼1000 5-methylcytosines (m 5 C) predicted from Aza-IP data, ∼124 200 N6-Methyladenosine (m 6 A) modifications discovered from m 6 A-seq and ∼1210 2′-O-methylations (2′-O-Me) identified from RiboMeth-seq data and public resources. Moreover, RMBase provides a comprehensive listing of other experimentally supported types of RNA modifications by integrating various resources. It provides web interfaces to show thousands of relationships between RNA modification sites and microRNA target sites. It can also be used to illustrate the disease-related SNPs residing in the modification sites/regions. RMBase provides a genome browser and a web-based modTool to query, annotate and visualize various RNA modifications. This database will help expand our understanding of potential functions of RNA modifications.