A pooling-based approach to mapping genetic variants associated with DNA methylation [electronic resource].
- Washington, D.C. : United States. National Nuclear Security Administration, 2015.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- pages 907-917 : digital, PDF file
- Additional Creators:
- United States. National Nuclear Security Administration
National Institutes of Health (U.S.)
National Science Foundation (U.S.)
United States. Department of Energy. Office of Scientific and Technical Information
- DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a truly genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. Here we found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.
- Published through SciTech Connect.
Genome Research 25 6 ISSN 1088-9051 AM
Irene M. Kaplow; Julia L. MacIsaac; Sarah M. Mah; Lisa M. McEwen; Michael S. Kobor; Hunter B. Fraser.
Stanford Univ., CA (United States)
- Funding Information:
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