Genetic impacts on DNA methylation help elucidate regulatory genomic processes
Authors/Creators
- 1. Department of Twin Research and Genetic Epidemiology, King's College London, UK
- 2. University of Exeter Medical School, UK
- 3. MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, UK
- 4. MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- 5. Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, UK
- 6. Centre for Longitudinal Studies, Institute of Education, University College London, UK
- 7. School of Sport, Exercise & Health Sciences, Loughborough University \& UCL Social Research Institute, University College London, UK
- 8. MRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, UK
Description
Background: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.
Results: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2,358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1,520 co-localisations across 1,325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs, (e.g. through disruption of transcription factor binding sites for CTCF and SMC3), and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites).
Conclusions: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk/.
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Related works
- Continues
- Dataset: https://epicmeqtl.kcl.ac.uk/ (URL)
- Is derived from
- Workflow: 10.5281/zenodo.11164534 (DOI)
- Is supplement to
- Journal article: 10.1186/s13059-023-03011-x (DOI)
- Preprint: 10.1101/2023.03.31.535045 (DOI)