A practical guide to the measurement and analysis of DNA methylation

BD Singer - American journal of respiratory cell and molecular …, 2019 - atsjournals.org
American journal of respiratory cell and molecular biology, 2019atsjournals.org
DNA methylation represents a fundamental epigenetic mark that is associated with
transcriptional repression during development, maintenance of homeostasis, and disease.
In addition to methylation-sensitive PCR and targeted deep-amplicon bisulfite sequencing to
measure DNA methylation at defined genomic loci, numerous unsupervised techniques
exist to quantify DNA methylation on a genome-wide scale, including affinity enrichment
strategies and methods involving bisulfite conversion. Both affinity-enriched and bisulfite …
DNA methylation represents a fundamental epigenetic mark that is associated with transcriptional repression during development, maintenance of homeostasis, and disease. In addition to methylation-sensitive PCR and targeted deep-amplicon bisulfite sequencing to measure DNA methylation at defined genomic loci, numerous unsupervised techniques exist to quantify DNA methylation on a genome-wide scale, including affinity enrichment strategies and methods involving bisulfite conversion. Both affinity-enriched and bisulfite-converted DNA can serve as input material for array hybridization or sequencing using next-generation technologies. In this practical guide to the measurement and analysis of DNA methylation, the goal is to convey basic concepts in DNA methylation biology and explore genome-scale bisulfite sequencing as the current gold standard for assessment of DNA methylation. Bisulfite conversion chemistry and library preparation are discussed in addition to a bioinformatics approach to quality assessment, trimming, alignment, and methylation calling of individual cytosine residues. Bisulfite-converted DNA presents challenges for standard next-generation sequencing library preparation protocols and data-processing pipelines, but these challenges can be met with elegant solutions that leverage the power of high-performance computing systems. Quantification of DNA methylation, data visualization, statistical approaches to compare DNA methylation between sample groups, and examples of integrating DNA methylation data with other –omics data sets are also discussed. The reader is encouraged to use this article as a foundation to pursue advanced topics in DNA methylation measurement and data analysis, particularly the application of bioinformatics and computational biology principles to generate a deeper understanding of mechanisms linking DNA methylation to cellular function.
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