Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

DNA methylation is one of the most important epigenetic mechanisms that ensures the maintenance and inheritance of gene-expression programs in mammalian cells. Three highly conserved DNA methyltransferase (DNMT) proteins (DNMT1, DNMT3A, and DNMT3B), which complex together in vivo, establish and maintain the DNA methylation landscape within the human genome. These novel next-generation sequencing (NGS) platforms also have many other advantages over the current platforms such as less bias during template preparation, possible longer read length, lower cost, higher speed, and better accuracy. The chapter presents the enrichment-based sequencing and bisulfite treatment-based approaches have successfully profiled DNA methylation and identified genome-wide differential methylation. The DMRs are segregated based on the location to a gene: promoter, downstream, body, exon, or intron. They are also intergrated into epigenomic marks for histone modification, transcription factors, chromatin structure, and nucleosome positioning in ENCODE, epigenome ATLS, and TCGA by overlapping or distance using BEDTools or FeatureCount.

Original languageEnglish (US)
Title of host publicationComputational Methods for Next Generation Sequencing Data Analysis
Publisherwiley
Pages197-226
Number of pages30
ISBN (Electronic)9781119272182
ISBN (Print)9781118169483
DOIs
StatePublished - Sep 6 2016

Fingerprint

Genes
Transcription factors
Methylation
Gene expression
DNA
Cells
Proteins
DNA Methylation
Costs

Keywords

  • Bisulfite treatment-based approaches
  • Computational approaches
  • DNA methyltransferase
  • Enrichment-based sequencing
  • Gene-expression programs
  • Genome-wide DNA methylation studies
  • Next-generation sequencing data analysis

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies. / Choi, Jeong-Hyeon; Shi, Huidong.

Computational Methods for Next Generation Sequencing Data Analysis. wiley, 2016. p. 197-226.

Research output: Chapter in Book/Report/Conference proceedingChapter

Choi, Jeong-Hyeon ; Shi, Huidong. / Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies. Computational Methods for Next Generation Sequencing Data Analysis. wiley, 2016. pp. 197-226
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