Abstract
Recent studies have revealed that the RNA N6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum.
Highlights
Epigenetic regulation, such as, RNA methylation, DNA methylation and post-translational modification (PTM), participates in a variety of important cellular processes, including embryonic development, maintenance of chromosome stability and X-chromosome inactivation (Wu and Zhang, 2014)
To evaluate the performance of this approach, we considered a naïve hypergeometric test-based approach, which assesses the association between a disease and an m6A sites by checking whether they are simultaneously linked to a significant number of genes in the constructed multi-layer heterogeneous network
This suggested that the multi-layer network model coupled with Random Walk with Restart (RWR) algorithm could effectively predict the disease-m6A site associations, or potentially unveil the disease circuits regulated at epitranscriptome layer
Summary
Epigenetic regulation, such as, RNA methylation, DNA methylation and post-translational modification (PTM), participates in a variety of important cellular processes, including embryonic development, maintenance of chromosome stability and X-chromosome inactivation (Wu and Zhang, 2014). Xu and Wang investigated the disease-associated phosphorylation sites of protein from a multi-layer heterogeneous network using the random walk algorithm (Xu and Wang, 2016) These studies greatly advanced our understanding of the role epigenetic modifications play in disease pathology. Comparing with the research dedicated to the experimental investigation of m6A site regulatory functions, bioinformatics is a possible method to identify the putative disease association of the m6A sites, thereby urgently needed at present Till this day, the computational approaches for studying the association between m6A methylation and diseases have been limited to the disease-associated mutations that may potentially disrupt or form an m6A-containing motif, which may be regulated through epitranscriptome layer. The DRUM website is freely available at: www.xjtlu.edu.cn/ biologicalsciences/drum
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
