ArticleGenomics, proteomics & bioinformatics2025
Distinct Co-methylation Patterns in African and European Populations and Their Genetic Associations.
Article in Genomics, proteomics & bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Population epigenetics: deciphering DNA methylation diversity and its implications for health, disease, and evolution.Molecular biology and evolution · 2026Review
- Harnessing Large Cohorts and AI to Bridge Genomic Discovery and Clinical Practice.Genomics, proteomics & bioinformatics · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Human populations have substantial genetic diversity, but the extent of epigenetic diversity remains unclear, as population-specific DNA methylation (DNAm) has only been studied for ∼ 3.0% of CpGs. In this study, we quantified DNAm using whole-genome bisulfite sequencing (WGBS) and analyzed it alongside whole-genome genotype data to provide a more comprehensive view of population-specific DNAm. Using a co-methylated region (CMR) approach, 36,657 CMRs were identified in WGBS data from 62 lymphoblastoid B-cell line (LCL) samples, with subsequent validation in a combined array dataset of 326 LCL samples. Between individuals of European and African ancestry, 101 CMRs exhibited population-specific DNAm patterns (Pop-CMRs), including 91 Pop-CMRs not reported in previous investigations. These regions spanned genes (e.g., CCDC42, GYPE, MAP3K20, and OBI1) related to diseases (e.g., malaria infection and diabetes) with differing prevalence and incidence between populations. Over half of the Pop-CMRs were associated with genetic variants, displaying population-specific allele frequencies and primarily mapped to genes involved in metabolic and infectious processes. Additionally, subsets of Pop-CMRs were applicable in East Asian populations and peripheral blood-based tissues. This study highlights genome-wide DNAm differences between populations and examines their associations with genetic varation and biological relevance, advancing our understanding of epigenetic contributions to population specificity.
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