WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach. Issue 7 (14th February 2019)

• Record Type: Journal Article
• Authors: Chen, Kunqi; Wei, Zhen; Zhang, Qing; Wu, Xiangyu; Rong, Rong; Lu, Zhiliang; Su, Jionglong; de Magalhães, João Pedro; Rigden, Daniel J; Meng, Jia
• Is Part Of: Nucleic acids research. Volume 47:Issue 7(2019)
• Page Start: e41
• Page End: e41
• Publication Date: 2019-02-14
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkz074
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: N 6 -methyladenosine (m 6 A) is the most prevalent post-transcriptional modification in eukaryotes, and plays a pivotal role in various biological processes, such as splicing, RNA degradation and RNA–protein interaction. We report here a prediction framework WHISTLE for transcriptome-wide m 6 A RNA-methylation site prediction. When tested on six independent datasets, our approach, which integrated 35 additional genomic features besides the conventional sequence features, achieved a major improvement in the accuracy of m 6 A site prediction (average AUC: 0.948 and 0.880 under the full transcript or mature messenger RNA models, respectively) compared to the state-of-the-art computational approaches MethyRNA (AUC: 0.790 and 0.732) and SRAMP (AUC: 0.761 and 0.706). It also out-performed the existing epitranscriptome databases MeT-DB (AUC: 0.798 and 0.744) and RMBase (AUC: 0.786 and 0.736), which were built upon hundreds of epitranscriptome high-throughput sequencing samples. To probe the putative biological processes impacted by changes in an individual m 6 A site, a network-based approach was implemented according to the 'guilt-by-association' principle by integrating RNA methylation profiles, gene expression profiles and protein–protein interaction data. Finally, the WHISTLE web server was built to facilitate the query of our high-accuracy map of the human m 6 A epitranscriptome, and the server is freely available at:www.xjtlu.edu.cn/biologicalsciences/whistle andhttp://whistle-epitranscriptome.com .