• Genomics & Informatics
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• v.9 no.3
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• pp.136-137
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• 2011

Methylation of cytosine is a post-synthesis modification that does not affect the primary DNA sequence but greatly influences gene expression level and phenotypes of an organism. As high-throughput sequencing of bisulfite-treated DNA is the most efficient method to identify methylated sites, several tools to map sequencing reads on a reference are available. But tools to visualize and to interpret the methylation level of methylation sites are currently insufficient. Herein, we present a novel tool to visualize the methylation level of CpG sites.

• Genomics & Informatics
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• v.16 no.3
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• pp.65-70
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• 2018

The non-coding DNA in eukaryotic genomes encodes a language which programs chromatin accessibility, transcription factor binding, and various other activities. The objective of this short report was to determine the impact of primary DNA sequence on the epigenomic landscape across 200-base pair genomic units by integrating nine publicly available ChromHMM Browser Extensible Data files of the Encyclopedia of DNA Elements (ENCODE) project. The nucleotide frequency profiles of nine chromatin annotations with the units of 200 bp were analyzed and integrative Markov chains were built to detect the Markov properties of the DNA sequences in some of the active chromatin states of different ChromHMM regions. Our aim was to identify the possible relationship between DNA sequences and the newly built chromatin states based on the integrated ChromHMM datasets of different cells and tissue types.

• Genomics & Informatics
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• v.16 no.4
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• pp.27.1-27.6
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• 2018

The non-coding DNA in eukaryotic genomes encodes a language that programs chromatin accessibility, transcription factor binding, and various other activities. The objective of this study was to determine the effect of the primary DNA sequence on the epigenomic landscape across a 200-base pair of genomic units by integrating 127 publicly available ChromHMM BED files from the Roadmap Genomics project. Nucleotide frequency profiles of 127 chromatin annotations stratified by chromatin variability were analyzed and integrative hidden Markov models were built to detect Markov properties of chromatin regions. Our aim was to identify the relationship between DNA sequence units and their chromatin variability based on integrated ChromHMM datasets of different cell and tissue types.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.4-12
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• 2022

Objective : We reported the differentially methylated genes in patients with subarachnoid hemorrhage (SAH) using bioinformatics analyses to explore the biological characteristics of the development of delayed cerebral ischemia (DCI). Methods : DNA methylation profiles obtained from 40 SAH patients from an epigenome-wide association study were analyzed. Functional enrichment analysis, protein-protein interaction (PPI) network, and module analyses were carried out. Results : A total of 13 patients (32.5%) experienced DCI during the follow-up. In total, we categorized the genes into the two groups of hypermethylation (n=910) and hypomethylation (n=870). The hypermethylated genes referred to biological processes of organic cyclic compound biosynthesis, nucleobase-containing compound biosynthesis, heterocycle biosynthesis, aromatic compound biosynthesis and cellular nitrogen compound biosynthesis. The hypomethylated genes referred to biological processes of carbohydrate metabolism, the regulation of cell size, and the detection of a stimulus, and molecular functions of amylase activity, and hydrolase activity. Based on PPI network and module analysis, three hypermethylation modules were mainly associated with antigen-processing, Golgi-to-ER retrograde transport, and G alpha (i) signaling events, and two hypomethylation modules were associated with post-translational protein phosphorylation and the regulation of natural killer cell chemotaxis. VHL, KIF3A, KIFAP3, RACGAP1, and OPRM1 were identified as hub genes for hypermethylation, and ALB and IL5 as hub genes for hypomethylation. Conclusion : This study provided novel insights into DCI pathogenesis following SAH. Differently methylated hub genes can be useful biomarkers for the accurate DCI diagnosis.