Abstract
Simple SummaryAberrations of normal DNA methylation patterns are observed in many cancers and are associated with chromatin alterations, changes in gene expression and genomic instability, making the study of DNA methylation paramount to our understanding of cancer biology and evolution and the development of biomarkers. Here, we present an overview of genome-wide approaches for the analysis of DNA methylation with relevance to cancer research and clinics.DNA methylation is an essential epigenetic mark. Alterations of normal DNA methylation are a defining feature of cancer. Here, we review experimental and bioinformatic approaches to showcase the breadth and depth of information that this epigenetic mark provides for cancer research. First, we describe classical approaches for interrogating bulk DNA from cell populations as well as more recently developed approaches for single cells and multi-Omics. Second, we focus on the computational analysis from primary data processing to the identification of unique methylation signatures. Additionally, we discuss challenges such as sparse data and cellular heterogeneity.
Highlights
DNA methylation, as supposed to other epigenetic marks, represents a direct modification of the genome, that is, the addition of a methyl group at the 5th Carbon of the cytosine base
Aberrant DNA methylation patterns have been observed in numerous diseases, in cancer where global hypomethylation and promoter hyper-methylation are characteristic of the disease [2]
Technological advances of genome-wide highthroughput technologies have revealed that a large proportion of regulatory elements for which DNA methylation marks tissue specificity are located in CpG-poor regions far away from genes [6]
Summary
DNA methylation, as supposed to other epigenetic marks, represents a direct modification of the genome, that is, the addition of a methyl group at the 5th Carbon of the cytosine base. DNA methylation is thought to alter chromatin structure in concert with other epigenetic marks, such as histone modifications, transcription factors, etc., and modify transcriptional potential or, in other words, regulate gene expression. Technological advances of genome-wide highthroughput technologies have revealed that a large proportion of regulatory elements for which DNA methylation marks tissue specificity are located in CpG-poor regions far away from genes [6]. DNA methylation within large hypo- or partially methylated regions occurs in a stochastic manner and follows heterochromatic domains—a phenomena that has been observed in cancers and in normal cells and that has been associated with cell proliferation history [8,9]. These, together with the existing technologies for high-throughput genome-wide analysis, have resulted in a large diversity of computational tools to process and analyse methylation data.
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