Dataset Information

I6mA-DNCP: Computational Identification of DNA N6-Methyladenine Sites in the Rice Genome Using Optimized Dinucleotide-Based Features.

ABSTRACT: DNA N6-methyladenine (6mA) plays an important role in regulating the gene expression of eukaryotes. Accurate identification of 6mA sites may assist in understanding genomic 6mA distributions and biological functions. Various experimental methods have been applied to detect 6mA sites in a genome-wide scope, but they are too time-consuming and expensive. Developing computational methods to rapidly identify 6mA sites is needed. In this paper, a new machine learning-based method, i6mA-DNCP, was proposed for identifying 6mA sites in the rice genome. Dinucleotide composition and dinucleotide-based DNA properties were first employed to represent DNA sequences. After a specially designed DNA property selection process, a bagging classifier was used to build the prediction model. The jackknife test on a benchmark dataset demonstrated that i6mA-DNCP could obtain 84.43% sensitivity, 88.86% specificity, 86.65% accuracy, a 0.734 Matthew's correlation coefficient (MCC), and a 0.926 area under the receiver operating characteristic curve (AUC). Moreover, three independent datasets were established to assess the generalization ability of our method. Extensive experiments validated the effectiveness of i6mA-DNCP.

SUBMITTER: Kong L

PROVIDER: S-EPMC6826501 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

i6mA-DNCP: Computational Identification of DNA N6-Methyladenine Sites in the Rice Genome Using Optimized Dinucleotide-Based Features.

Kong Liang L Zhang Lichao L

Genes 20191020 10

DNA N6-methyladenine (6mA) plays an important role in regulating the gene expression of eukaryotes. Accurate identification of 6mA sites may assist in understanding genomic 6mA distributions and biological functions. Various experimental methods have been applied to detect 6mA sites in a genome-wide scope, but they are too time-consuming and expensive. Developing computational methods to rapidly identify 6mA sites is needed. In this paper, a new machine learning-based method, i ...[more]

PMID: 31635172

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Project description:DNA N6-Methyladenine (6mA) is a common epigenetic modification, which plays some significant roles in the growth and development of plants. It is crucial to identify 6mA sites for elucidating the functions of 6mA. In this article, a novel model named i6mA-vote is developed to predict 6mA sites of plants. Firstly, DNA sequences were coded into six feature vectors with diverse strategies based on density, physicochemical properties, and position of nucleotides, respectively. To find the best coding strategy, the feature vectors were compared on several machine learning classifiers. The results suggested that the position of nucleotides has a significant positive effect on 6mA sites identification. Thus, the dinucleotide one-hot strategy which can describe position characteristics of nucleotides well was employed to extract DNA features in our method. Secondly, DNA sequences of Rosaceae were divided into a training dataset and a test dataset randomly. Finally, i6mA-vote was constructed by combining five different base-classifiers under a majority voting strategy and trained on the Rosaceae training dataset. The i6mA-vote was evaluated on the task of predicting 6mA sites from the genome of the Rosaceae, Rice, and Arabidopsis separately. In Rosaceae, the performances of i6mA-vote were 0.955 on accuracy (ACC), 0.909 on Matthew correlation coefficients (MCC), 0.955 on sensitivity (SN), and 0.954 on specificity (SP). Those indicators, in the order of ACC, MCC, SN, SP, were 0.882, 0.774, 0.961, and 0.803 on Rice while they were 0.798, 0.617, 0.666, and 0.929 on Arabidopsis. According to the indicators, our method was effectiveness and better than other concerned methods. The results also illustrated that i6mA-vote does not only well in 6mA sites prediction of intraspecies but also interspecies plants. Moreover, it can be seen that the specificity is distinctly lower than the sensitivity in Rice while it is just the opposite in Arabidopsis. It may be resulted from sequence similarity among Rosaceae, Rice and Arabidopsis.

Project description:BackgroundIn recent years, the prevalence of Alzheimer's disease (AD) has increased, which places a great burden on society and families and creates considerable challenges for medical services. N6-methyladenine (m6A) deoxyribonucleic acid (DNA) adenine methylation is a novel biomarker and is abundant in the brain, but less common in AD. We support to analyze the relationship between DNA m6A and cognition in patients with AD and normal controls (NCs) in China.AimTo analyze the relationship between the novel m6A DNA and cognition in patients with AD and NCs in China.MethodsA total of 179 AD patients (mean age 71.60 ± 9.89 years; males: 91; females: 88) and 147 NCs (mean age 69.59 ± 11.22 years; males: 77; females: 70) who were age- and sex-matched were included in our study. All subjects underwent neuropsychological scale assessment and magnetic resonance imaging examination. Apolipoprotein E (APOE) genotypes were measured through agarose gel electrophoresis. Global m6A levels were evaluated by a MethylFlash m6A DNA Methylation ELISA Kit (colorimetric). Global m6A levels in total DNA from ten AD patients with 18F-AV-45 (florbetapir) positron emission tomography (PET) positivity and ten NCs with PET negativity were analyzed by dot blotting to determine the results.ResultsOur ELISA results showed that the global m6A DNA levels in peripheral blood were different between patients with AD and NCs (P = 0.002; < 0.05). And ten AD patients who were PET positive and ten NCs who were PET negative also showed the same results through dot blotting. There were significant differences between the two groups, which indicated that the leukocyte m6A DNA levels were different (P = 0.005; < 0.05). The m6A level was approximately 8.33% lower in AD patients than in NCs (mean 0.011 ± 0.006 vs 0.012 ± 0.005). A significant correlation was found between the Montreal Cognitive Assessment score and the peripheral blood m6A level in the tested population (r = 0.143, P = 0.01; < 0.05). However, no relationship was found with APOE ε4 (P = 0.633, > 0.05). Further studies should be performed to validate these findings.ConclusionOur results show that reduced global m6A DNA methylation levels are significantly lower in AD patients than in NCs by approximately 8.33% in China.

Dataset Information

I6mA-DNCP: Computational Identification of DNA N6-Methyladenine Sites in the Rice Genome Using Optimized Dinucleotide-Based Features.

Publications

i6mA-DNCP: Computational Identification of DNA <i>N</i><sup>6</sup>-Methyladenine Sites in the Rice Genome Using Optimized Dinucleotide-Based Features.

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