Prediction of methylated CpGs in DNA sequences using a support vector machine

Abstract

DNA methylation plays a key role in the regulation of gene expression. The most common type of DNA modification consists of the methylation of cytosine in the CpG dinucleotide. At the present time, there is no method available for the prediction of DNA methylation sites. Therefore, in this study we have developed a support vector machine (SVM)-based method for the prediction of cytosine methylation in CpG dinucleotides. Initially a SVM module was developed from human data for the prediction of human-specific methylation sites. This module achieved a MCC and AUC of 0.501 and 0.814, respectively, when evaluated using a 5-fold cross-validation. The performance of this SVM-based module was better than the classifiers built using alternative machine learning and statistical algorithms including artificial neural networks, Bayesian statistics, and decision trees. Additional SVM modules were also developed based on mammalian-and vertebrate-specific methylation patterns. The SVM module based on human methylation patterns was used for genome-wide analysis of methylation sites. This analysis demonstrated that the percentage of methylated CpGs is higher in UTRs as compared to exonic and intronic regions of human genes. This method is available on line for public use under the name of Methylator at http://bio.dfci.harvard.edu/Methylator/.

Human ZCCHC12 activates AP-1 and CREB signaling as a transcriptional co-activator

“…Yet, quantitative RT -PCR experiments detected ZCCHC12 not only from brain-derived cell lines (SK-N-SH and A172) but also from other tissue-derived cell lines (HeLa, MCF7, MDA-MB-231, HEK293FT, HT1080, and HepG2). Because DNA methylation plays a key role in the regulation of gene expression in specific tissues and tumor cells [24], we used online software Methylator (http://www.bioinfo.tsinghua.edu.cn/~tigerchen/memo/ form.html) to predict methylation sites and found many potential methylation sites present in the promoter region of ZCCHC12. Therefore, we speculate that expression of ZCCHC12 in other tissue-derived cell lines is possibly caused by alteration of DNA methylation in ZCCHC12 promoter region.…”

Prediction of MHC-Peptide Binding: A Systematic and Comprehensive Overview

“…SVMs are a relatively new type of MLA that are increasingly being used in the life sciences to identify patterns [47][48][49]; they classify by constructing an N-dimensional hyperplane that separates the data optimally into categories. Using this approach, Donnes and Elofsson [50] developed the SVMHC method (Table I), which is available online to predict peptide binding to MHCI.…”

Disclosing the crosstalk among DNA methylation, transcription factors, and histone marks in human pluripotent cells through discovery of DNA methylation motifs

“…Genomewide methylation next-generation sequencing (NGS) has shown that CpG islands are usually unmethylated (Deaton and Bird 2011;Meissner 2011) and methylation alterations in cancer occur neither in promoters, nor in CpG islands, but in sequences up to 2 kb called CpG island shores (Doi et al 2009;Irizarry et al 2009). With some exceptions (Bhasin et al 2005;Bock et al 2006), research on CpG methylation prediction outside the aforementioned regions is scarce.…”