i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome.

作者：Hasan Md Mehedi; Manavalan Balachandran; Khatun Mst Shamima; Kurata Hiroyuki

来源：International journal of biological macromolecules, 2020, 157: 752-758.

DOI：10.1016/j.ijbiomac.2019.12.009

• DNA methylation
• Linear regression
• Machine learning
• N4-methylcytosine site
• Sequence encoding

One of the most important epigenetic modifications is N4-methylcytosine, which regulates many biological processes including DNA replication and chromosome stability. Identification of N4-methylcytosine sites is pivotal to understand specific biological functions. Herein, we developed the first bioinformatics tool called i4mC-ROSE for identifying N4-methylcytosine sites in the genomes of Fragaria vesca and Rosa chinensis in the Rosaceae, which utilizes a random forest classifier with six encoding methods that cover various aspects of DNA sequence information. The i4mC-ROSE predictor achieves area under the curve scores of 0.883 and 0.889 for the two genomes during cross-validation. Moreover, the i4mC-ROSE outperforms other classifiers tested in this study when objectively evaluated on the independent datasets. The proposed i4mC-ROSE tool can serve users’ demand for the prediction of 4mC sites in the Rosaceae genome. The i4mC-ROSE predictor and utilized datasets are publicly accessible at http://kurata14.bio.kyutech.ac.jp/i4mC-ROSE/.

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