A pooling-based approach to mapping genetic variants associated with DNA methylation

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.; McEwen, Lisa M.; Kobor, Michael S.; Fraser, Hunter B.

doi:10.1101/gr.183749.114

Title: A pooling-based approach to mapping genetic variants associated with DNA methylation

Journal Article · Fri Apr 24 00:00:00 EDT 2015 · Genome Research

DOI:https://doi.org/10.1101/gr.183749.114· OSTI ID:1344874

Kaplow, Irene M. ^[1]; MacIsaac, Julia L. ^[2]; Mah, Sarah M. ^[2]; McEwen, Lisa M. ^[3]; Kobor, Michael S. ^[3]; Fraser, Hunter B. ^[4]

Stanford Univ., CA (United States). Dept. of Computer Science and Dept. of Biology
Univ. of British Columbia, Vancouver, BC (Canada). Centre for Molecular Medicine and Therapeutics and Child and Family Research Inst.
Univ. of British Columbia, Vancouver, BC (Canada). Centre for Molecular Medicine and Therapeutics and Child and Family Research Inst. and Dept. of Medical Genetics
Stanford Univ., CA (United States). Dept. of Biology

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.

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Research Organization:: Stanford Univ., CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); National Institutes of Health (NIH); National Science Foundation (NSF)

Grant/Contract Number:: FG02-97ER25308

OSTI ID:: 1344874

Journal Information:: Genome Research, Vol. 25, Issue 6; ISSN 1088-9051

Publisher:: Cold Spring Harbor Laboratory PressCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 19 works

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