Journal
NUCLEIC ACIDS RESEARCH
Volume 47, Issue 7, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkz074
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Funding
- National Natural Science Foundation of China [31671373]
- Jiangsu University Natural Science Program [16KJB180027]
- XJTLU Key Programme Special Fund [KSF-T-01]
- Jiangsu Six Talent Peak Program [XYDXX-118]
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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 and http://whistle-epitranscriptome.com.
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