Recent Progresses for Computationally Identifying N6-methyladenosine Sites in Saccharomyces cerevisiae

Corresponding author: Kuo-Chen Chou, Gordon Life Science Institute, Boston, MA 02478, USA. Email: kcchou@gordonlifescience.org Abstract N-methyladenosine (mA) plays critical roles in a broad set of biological processes. Knowledge about the precise location of mA site in the transcriptome is vital for deciphering its biological functions. Although experimental techniques have made substantial contributions to identify mA methylations, they are still labor intensive, costly and time consuming. As good complements to experimental methods, in the past few years, a series of computational approaches have been proposed to identify mA sites in Saccharomyces cerevisiae. In order to facilitate researchers to select appropriate methods for identifying mA sites, it is necessary to give a comprehensive review and comparison on existing computational methods. In this review, we summarized the current progresses in computational prediction of mA sites and also assessed the performance of computational methods for identifying mA sites on an independent dataset. Finally, challenges and future directions of computationally identifying mA sites were presented as well. Taken together, we anticipate that this review will provide an important guide for future computational analysis of mA and other RNA modifications.