Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 417-428 |
| Number of pages | 12 |
| Journal | American journal of respiratory cell and molecular biology |
| Volume | 61 |
| Issue number | 4 |
| DOIs | |
| State | Published - Oct 1 2019 |
Funding
The author thanks Shang-Yang (Sam) Chen and Kishore Anekalla for their work in developing the initial code sets for the DNA methylation processing and analysis pipelines, as well as the members of his laboratory and research group for their helpful comments on the manuscript. This work was supported in part by the computational resources and staff contributions provided by the Genomics Compute Cluster, which is jointly supported by the Feinberg School of Medicine, the Center for Genetic Medicine, and Feinberg's Department of Biochemistry and Molecular Genetics, the Office of the Provost, the Office for Research, and Northwestern Information Technology. The Genomics Compute Cluster is part of Quest, Northwestern University's high-performance computing facility, with the purpose to advance research in genomics. Acknowledgment: The author thanks Shang-Yang (Sam) Chen and Kishore Anekalla for their work in developing the initial code sets for the DNA methylation processing and analysis pipelines, as well as the members of his laboratory and research group for their helpful comments on the manuscript. This work was supported in part by the computational resources and staff contributions provided by the Genomics Compute Cluster, which is jointly supported by the Feinberg School of Medicine, the Center for Genetic Medicine, and Feinberg’s Department of Biochemistry and Molecular Genetics, the Office of the Provost, the Office for Research, and Northwestern Information Technology. The Genomics Compute Cluster is part of Quest, Northwestern University’s high-performance computing facility, with the purpose to advance research in genomics. Supported by National Institutes of Health grants K08HL128867 and U19AI135964, and a Parker B. Francis Research Opportunity Award.
Keywords
- Bioinformatics
- Bisulfite sequencing
- DNA methylation
- Epigenetics
- Next-generation sequencing
ASJC Scopus subject areas
- Molecular Biology
- Pulmonary and Respiratory Medicine
- Clinical Biochemistry
- Cell Biology