Abstract
DNA methylation is a common epigenetic marker that regulates gene expression. A robust and cost-effective way for measuring whole genome methylation is Methyl-CpG binding domain-based capture followed by sequencing (MBDCap-seq). In this study, we proposed BIMMER, a Hidden Markov Model (HMM) for differential Methylation Regions (DMRs) identification, where HMMs were proposed to model the methylation status in normal and cancer samples in the first layer and another HMM was introduced to model the relationship between differential methylation and methylation statuses in normal and cancer samples. To carry out the prediction for BIMMER, an Expectation-Maximization algorithm was derived. BIMMER was validated on the simulated data and applied to real MBDCap-seq data of normal and cancer samples. BIMMER revealed that 8.83% of the breast cancer genome are differentially methylated and the majority are hypo-methylated in breast cancer.
Highlights
DNA methylation refers to the chemical modification of DNA nucleotides
We proposed a novel algorithm for differential methylation regions (DMRs) detection based on Hidden Markov Model (HMM) and we call the algorithm BIMMER
BIMMER was applied to a real breast cancer dataset to explore the state of differential methylation
Summary
DNA methylation refers to the chemical modification of DNA nucleotides. One of the most common DNA methylation is the modification of cytosine, which typically occurs in CpG sites. When CpG sites in the promoter region that transcription factors bind are methylated, permanent silencing of gene expression is observed in the cell. DNA methylation is highly prevalent in cancer, involved in almost all types of cancer development by altering the normal regulation of gene expression and silencing the tumor suppressor genes [1]. There are three sequencing-based technologies for whole-genome DNA methylation profiling: bisulfite treatment[2] based or bisulfite sequencing, methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq)[3], and Methyl-CpG binding domain-base capture followed by sequencing (MBDCapseq)[4].
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