Analysis approaches for the identification and prediction of N6-methyladenosine sites. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Yang, Yuwei; Liu, Zhiyu; Lu, Junru; Sun, Yuqing; Fu, Yue; Pan, Min; Xie, Xueying; Ge, Qinyu
• Is Part Of: Epigenetics. Volume 18:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: m6A methylation -- analytical tools -- detection methods -- prediction; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2022.2158284
• Languages: English
• ISSNs: 1559-2294

Abstract

ABSTRACT: The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m 6 A sites, in particular full-transcriptome m 6 A. And individual m 6 A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m 6 A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m 6 A methylation, including the experimental detection of m 6 A methylation sites, techniques of data analysis, the way of predicting m 6 A methylation sites, m 6 A methylation databases, and detection of m 6 A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area.