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A pooling-based approach to mapping genetic variants associated with DNA methylation
Irene M Kaplow1, Julia L MacIsaac2, Sarah M Mah2
1Department of Computer Science, Stanford University, Stanford, California 94305, USA; Department of Biology, Stanford University, Stanford, California 94305, USA;
Genome Research
|April 26, 2015
Summary
This study introduces a new pooled sequencing method for genome-wide DNA methylation mapping. This approach enhances the power to detect genetic variants associated with DNA methylation across the entire genome.
Area of Science:
- Epigenetics
- Genomics
- Molecular Biology
Background:
- DNA methylation is crucial for gene regulation.
- Previous methods for mapping genetic variants associated with DNA methylation were limited in scope and could not fully account for allele-specific methylation (ASM).
- Existing whole-genome bisulfite sequencing studies on limited individuals lacked statistical power.
Purpose of the Study:
- To develop a novel, cost-effective, and statistically powerful genome-wide approach for mapping genetic variants associated with DNA methylation.
- To overcome the limitations of previous microarray and low-sample whole-genome sequencing studies.
Main Methods:
- A novel pooled sequencing approach using bisulfite-treated DNA from multiple individuals.
- Deep sequencing of pooled DNA to generate a comprehensive genome-wide map of DNA methylation.
- Analysis of genetic variants associated with DNA methylation across the genome.
Main Results:
- The approach enabled a truly genome-wide map of DNA methylation, significantly increasing statistical power and reducing costs.
- Analysis of 60 pooled human cell lines identified over 2000 genetic variants associated with DNA methylation, covering more CpGs than previous large microarray studies.
- Identified variants showed strong associations with chromatin accessibility and CTCF binding, but weaker associations with gene expression and disease phenotypes.
Conclusions:
- The developed method allows for cost-effective, genome-wide mapping of genetic variants associated with DNA methylation.
- This approach is applicable to any tissue and species, without requiring individual-level genotype or methylation data.
- The findings highlight the enrichment of methylation-associated variants in regulatory elements like chromatin and CTCF binding sites.
