Identifying RNA N6-Methyladenosine Sites in Escherichia coli Genome

• Main Authors: Jidong Zhang, Pengmian Feng, Hao Lin, Wei Chen
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-05-01
• Series: Frontiers in Microbiology
• Subjects: N6-methyladenosine; machine learning method; nucleotide physicochemical properties; microbial genome; pseudo nucleotide composition
• Online Access: http://journal.frontiersin.org/article/10.3389/fmicb.2018.00955/full

N6-methyladenosine (m6A) plays important roles in a branch of biological and physiological processes. Accurate identification of m6A sites is especially helpful for understanding their biological functions. Since the wet-lab techniques are still expensive and time-consuming, it's urgent to develop computational methods to identify m6A sites from primary RNA sequences. Although there are some computational methods for identifying m6A sites, no methods whatsoever are available for detecting m6A sites in microbial genomes. In this study, we developed a computational method for identifying m6A sites in Escherichia coli genome. The accuracies obtained by the proposed method are >90% in both 10-fold cross-validation test and independent dataset test, indicating that the proposed method holds the high potential to become a useful tool for the identification of m6A sites in microbial genomes.