Abstract

DNA N6-methyladenine (6mA) is an important epigenetic modification, which is involved in many biology regulation processes. An accurate and reliable method for 6mA identification can help us gain a better insight into the regulatory mechanism of the modification. Although many experimental techniques have been proposed to identify 6mA sites genome-wide, these techniques are time consuming and laborious. Recently, several machine learning methods have been developed to identify 6mA sites genome-wide. However, there is room for the improvement on their performance for predicting 6mA sites in rice genome. In this paper, we developed a simple and lightweight deep learning model to identify DNA 6mA sites in rice genome. Our model needs no prior knowledge of 6mA or manually crafted sequence feature. We built our model based on two rice 6mA benchmark datasets. Our method got an average prediction accuracy of ∼93% and ∼92% on the two datasets we used. We compared our method with existing 6mA prediction tools. The comparison results show that our model outperforms the state-of-the-art methods.

Highlights

  • DNA N6-methyladenine (6mA) is one important DNA epigenetic modification, which has been found in bacteria, eukaryote, and archaea (O’brown and Greer, 2016)

  • We evaluated the performance of our method SNNRice6mA on two DNA 6mA benchmark datasets (i.e., 6mA-rice-Chen and 6mA-rice-Lv) for rice genome

  • We examined whether iDNA6mA-PseKNC can predict 6mA sites in rice genome

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Summary

Introduction

DNA N6-methyladenine (6mA) is one important DNA epigenetic modification, which has been found in bacteria, eukaryote, and archaea (O’brown and Greer, 2016). It was reported that 6mA is involved in many biological processes. For eukaryote, the study of DNA 6mA”” is still insufficient (Koziol et al, 2016). Studying the distribution of DNA 6mA can provide a deeper understanding of the epigenetic modification process. The development of experimental techniques contributes to studying DNA 6mA modification. Pormraning et al developed a protocol using bisulfite sequencing and methyl-DNA immunoprecipitation technique to analyze genome-wide DNA methylation in eukaryotes (Pomraning et al, 2009). Flusberg et al applied single-molecule, real-time sequencing technique to detect DNA methyladenine directly (Flusberg et al, 2010). Greer et al used ultra-high performance liquid chromatography coupled

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