M6Acomet: Large-scale functional prediction of individual m 6 A RNA methylation sites from an RNA co-methylation network

Abstract

Background: Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics. Results: To date, the study of epitranscriptome layer gene regulation is mostly focused on the function of mediator proteins of RNA methylation, i.e., the readers, writers and erasers. There is limited investigation of the functional relevance of individual m 6 A RNA methylation site. To address this, we annotated human m 6 A sites in large-scale based on the guilt-by-association principle from an RNA co-methylation network. It is constructed based on public human MeRIP-Seq datasets profiling the m 6 A epitranscriptome under 32 independent experimental conditions. By systematically examining the network characteristics obtained from the RNA methylation profiles, a total of 339,158 putative gene ontology functions associated with 1446 human m 6 A sites were identified. These are biological functions that may be regulated at epitranscriptome layer via reversible m 6 A RNA methylation. The results were further validated on a soft benchmark by comparing to a random predictor. Conclusions: An online web server m6Acomet was constructed to support direct query for the predicted biological functions of m 6 A sites as well as the sites exhibiting co-methylated patterns at the epitranscriptome layer. The m6Acomet web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/m6acomet.