iDNA-MS: An Integrated Computational Tool for Detecting DNA Modification Sites in Multiple Genomes

Hao Lv; Fu-Ying Dao; Dan Zhang; Zheng-Xing Guan; Hui Yang; Wei Su; Meng-Lu Liu; Hui Ding; Wei Chen; Hao Lin

doi:10.1016/j.isci.2020.100991

iDNA-MS: An Integrated Computational Tool for Detecting DNA Modification Sites in Multiple Genomes

iScience. 2020 Apr 24;23(4):100991. doi: 10.1016/j.isci.2020.100991. Epub 2020 Mar 19.

Authors

Hao Lv¹, Fu-Ying Dao¹, Dan Zhang¹, Zheng-Xing Guan¹, Hui Yang¹, Wei Su¹, Meng-Lu Liu¹, Hui Ding¹, Wei Chen², Hao Lin³

Affiliations

¹ Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
² Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan 063000, China; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
³ Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China. Electronic address: hlin@uestc.edu.cn.

Abstract

5hmC, 6mA, and 4mC are three common DNA modifications and are involved in various of biological processes. Accurate genome-wide identification of these sites is invaluable for better understanding their biological functions. Owing to the labor-intensive and expensive nature of experimental methods, it is urgent to develop computational methods for the genome-wide detection of these sites. Keeping this in mind, the current study was devoted to construct a computational method to identify 5hmC, 6mA, and 4mC. We initially used K-tuple nucleotide component, nucleotide chemical property and nucleotide frequency, and mono-nucleotide binary encoding scheme to formulate samples. Subsequently, random forest was utilized to identify 5hmC, 6mA, and 4mC sites. Cross-validated results showed that the proposed method could produce the excellent generalization ability in the identification of the three modification sites. Based on the proposed model, a web-server called iDNA-MS was established and is freely accessible at http://lin-group.cn/server/iDNA-MS.

Keywords: Bioinformatics; Genetics; Quantitative Genetics.