CoChat
Sign Up
PreprintCited by 416Epigenetics and DNA MethylationGenetic Associations and EpidemiologyGenomics and Chromatin Dynamics

The DOI matches its Crossref record; 58 of the 59 references it cites were found in a registry or an index.

DNA methylation contributes to natural human variation

Open access
Heyn, Holger, Moran, Sebastian, Hernando-Herraez, Irene, Sayols, Sergi, Gomez, Antonio, Sandoval, Juan, Monk, Dave, Hata, Kenichiro, Marques-Bonet, Tomas, Wang, Liewei, Esteller, Manel·2013·Genome Research
DOI 10.1101/gr.154187.112PMC PMC3759714
Open this paper in CoChat — free accountOpen PDF

Abstract

DNA methylation patterns are important for establishing cell, tissue, and organism phenotypes, but little is known about their contribution to natural human variation. To determine their contribution to variability, we have generated genome-scale DNA methylation profiles of three human populations (Caucasian-American, African-American, and Han Chinese-American) and examined the differentially methylated CpG sites. The distinctly methylated genes identified suggest an influence of DNA methylation on phenotype differences, such as susceptibility to certain diseases and pathogens, and response to drugs and environmental agents. DNA methylation differences can be partially traced back to genetic variation, suggesting that differentially methylated CpG sites serve as evolutionarily established mediators between the genetic code and phenotypic variability. Notably, one-third of the DNA methylation differences were not associated with any genetic variation, suggesting that variation in population-specific sites takes place at the genetic and epigenetic levels, highlighting the contribution of epigenetic modification to natural human variation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/gr.154187.112

Cites

58 of 58 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1. DNA methylation separates African-American (AF, brown), Caucasian-American (CA, pink), and Han Chinese-American (AS, yellow) individuals. (A) Hierarchical clustering of 439 pop-CpG sites separating the three populations using absolute DNA methylation levels (low: green; high: red). (B) Multiscale bootstrap resampling (n = 10,000) of the 439 pop-CpG sites significantly differentially methylated between African, Asian, and Caucasian individuals. The three populations cluster separately and consistently with prior genetically defined proximities (approximately unbiased P-value > 0.99). (C) Principal component analysis (PCA) of pop-CpGs displaying the first two principal components. (D) ADMIXTURE analysis of pop-CpGs-defined ancestral DNA methylation status. Each individual is represented by a vertical line, with the lengths corresponding to the ancestry coefficients in up to three inferred ancestral groups.
Figure 1. DNA methylation separates African-American (AF, brown), Caucasian-American (CA, pink), and Han Chinese-American (AS, yellow) individuals. (A) Hierarchical clustering of 439 pop-CpG sites separating the three populations using absolute DNA methylation levels (low: green; high: red). (B) Multiscale bootstrap resampling (n = 10,000) of the 439 pop-CpG sites significantly differentially methylated between African, Asian, and Caucasian individuals. The three populations cluster separately and consistently with prior genetically defined proximities (approximately unbiased P-value > 0.99). (C) Principal component analysis (PCA) of pop-CpGs displaying the first two principal components. (D) ADMIXTURE analysis of pop-CpGs-defined ancestral DNA methylation status. Each individual is represented by a vertical line, with the lengths corresponding to the ancestry coefficients in up to three inferred ancestral groups.CC BY-NC · PubMed Central
Figure 2. Differentially methylated gene promoters of KRTCAP3 (A), TNNT1 (B), SEPT8 (C), CD226 (D), PM20D1 (E), and FGFR2 (F) in Han Chinese-American (yellow), Caucasian-American (pink), and African-American (brown) individuals. Absolute DNA methylation levels at population-specific CpG sites in gene promoters (low: green; high: red) are displayed for single individuals (n = 269). The distance to the gene transcription start site is indicated. The samples are ranked according to their average DNA methylation levels (middle panel) at displayed pop-CpGs. Population enrichment (right panel) is illustrated using absolute sample numbers in a 10-sample window.
Figure 2. Differentially methylated gene promoters of KRTCAP3 (A), TNNT1 (B), SEPT8 (C), CD226 (D), PM20D1 (E), and FGFR2 (F) in Han Chinese-American (yellow), Caucasian-American (pink), and African-American (brown) individuals. Absolute DNA methylation levels at population-specific CpG sites in gene promoters (low: green; high: red) are displayed for single individuals (n = 269). The distance to the gene transcription start site is indicated. The samples are ranked according to their average DNA methylation levels (middle panel) at displayed pop-CpGs. Population enrichment (right panel) is illustrated using absolute sample numbers in a 10-sample window.CC BY-NC · PubMed Central
Figure 3. Genotype and DNA methylation regulate gene expression of SPATC1L in a conjoined manner and inversely correlate at the transcription start (TSS) and end site (TES). (A) Schematic overview of the gene structure of SPATC1L. (B) AF individuals have high levels of promoter DNA methylation, a TT phenotype enriched in rs8133082, and reduced expression of SPATC1L. The figure displays the absolute DNA methylation levels (low: green; high: red) for four promoter-related pop-CpGs of African-American (brown), Caucasian-American (pink), and Han Chinese-American (yellow) individuals; the genotype of rs8133082 for the individual samples (GG, GT, TT); the correlation between DNA methylation (cg08742575) and the genotype (rs8133082); and the gene expression level (SPATC1L). Samples are ranked by mean CpG methylation values. (C) Unlike the promoter, AF individuals have CpG hypomethylation, which is positively correlated with SPATC1L gene expression (cg11766577).
Figure 3. Genotype and DNA methylation regulate gene expression of SPATC1L in a conjoined manner and inversely correlate at the transcription start (TSS) and end site (TES). (A) Schematic overview of the gene structure of SPATC1L. (B) AF individuals have high levels of promoter DNA methylation, a TT phenotype enriched in rs8133082, and reduced expression of SPATC1L. The figure displays the absolute DNA methylation levels (low: green; high: red) for four promoter-related pop-CpGs of African-American (brown), Caucasian-American (pink), and Han Chinese-American (yellow) individuals; the genotype of rs8133082 for the individual samples (GG, GT, TT); the correlation between DNA methylation (cg08742575) and the genotype (rs8133082); and the gene expression level (SPATC1L). Samples are ranked by mean CpG methylation values. (C) Unlike the promoter, AF individuals have CpG hypomethylation, which is positively correlated with SPATC1L gene expression (cg11766577).CC BY-NC · PubMed Central
Figure 4. Genetic polymorphisms related to HBV infection influence DNA methylation and gene expression at the HLA-DPA1 locus. Using Circos (Krzywinski et al. 2009), the figure shows a schematic overview of the HLA-DPA1 locus and DNA methylation, genotype and expression data from African-American (brown), Caucasian-American (pink), and Han Chinese-American (yellow) individuals: DNA methylation levels (low: green; high: red) of CpG sites (n = 17) significantly correlated with the genotype of HBV infection-associated SNPs (n = 10) (Kamatani et al. 2009). Samples are ranked by mean CpG methylation values. SNP-CpG relations are displayed by colored lines. The genotype distribution of SNPs in the HLA-DPA1 locus is shown, which is significantly correlated with the level of CpG methylation (gray boxes; risk alleles are highlighted in red) (Kamatani et al. 2009). The distribution of expression levels of HLA-DPA1 is shown in the blue box.
Figure 4. Genetic polymorphisms related to HBV infection influence DNA methylation and gene expression at the HLA-DPA1 locus. Using Circos (Krzywinski et al. 2009), the figure shows a schematic overview of the HLA-DPA1 locus and DNA methylation, genotype and expression data from African-American (brown), Caucasian-American (pink), and Han Chinese-American (yellow) individuals: DNA methylation levels (low: green; high: red) of CpG sites (n = 17) significantly correlated with the genotype of HBV infection-associated SNPs (n = 10) (Kamatani et al. 2009). Samples are ranked by mean CpG methylation values. SNP-CpG relations are displayed by colored lines. The genotype distribution of SNPs in the HLA-DPA1 locus is shown, which is significantly correlated with the level of CpG methylation (gray boxes; risk alleles are highlighted in red) (Kamatani et al. 2009). The distribution of expression levels of HLA-DPA1 is shown in the blue box.CC BY-NC · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Sorted by citations

See all 416

Related

See all

Metadata

Authors
Heyn, H., Moran, S., Hernando-Herraez, I., Sayols, S., Gomez, A., Sandoval, J., Monk, D., Hata, K., Marques-Bonet, T., Wang, L., & Esteller, M.
Affiliations
  • Institut d'Investigació Biomédica de Bellvitge (ES)
  • Consejo Superior de Investigaciones Científicas (ES)
  • National Research Institute for Child Health and Development (JP)
  • Mayo Clinic (US)
  • Institució Catalana de Recerca i Estudis Avançats (ES)
Corresponding author
  • Wang, Liewei
  • Esteller, Manel
ORCID
Venue
Genome Research
Publisher
Cold Spring Harbor Laboratory
Published
2013-08-01
Volume
23
Issue
9
Pages
1363-1372
ISSN
1088-9051 (ISSN-L)
DOI
10.1101/gr.154187.112
PMC
PMC3759714
OpenAlex
W2095727856
Cited by
408
References
59
Citations by year
2026: 8 · 2025: 18 · 2024: 22 · 2023: 23 · 2022: 34 · 2021: 19 · 2020: 40 · 2019: 29 · 2018: 49 · 2017: 40 · 2016: 46 · 2015: 54 · 2014: 22 · 2013: 3
Type
posted content
Language
en
Open access
Licence
other-oa
Locations
  • Genome Research (publishedVersion, other-oa)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by-nc)
  • Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by-nc)
  • HighWire Press Open Archive (submittedVersion)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by-nc)
Funders
  • Fundación Cellex (SAF2011-22803)
  • European Commission (282510)
  • Generalitat de Catalunya
  • Institució Catalana de Recerca i Estudis Avançats
  • Ministerio de Ciencia e Innovación (SAF2011-22803, BFU2011-28549)
  • National Institutes of Health (GM61388)
  • National Cancer Institute (CA138461, R01CA138461)
  • National Institute of General Medical Sciences (U01GM061388, U19GM061388, GM61388)
  • FP7 Ideas: European Research Council (268626, 260372)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
DNA methylation, differentially methylated CpG sites, epigenetic inheritance, genetic variation, disease susceptibility, drug response, phenotypic variability, African Americans, Han Chinese, White Americans
MeSH terms
Adult, Asian, Black or African American, Female, Humans, Male, Population, Genetic Variation, Genome, Human, DNA Methylation, Quantitative Trait Loci, Epigenesis, Genetic, White People, Genome-Wide Association Study

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review