Figure 4. Passive and active roles of DNA methylation in gene regulation.

(A) Illustration of the three possible causative models tested of mechanistic relationships between genetic variation (SNP), DNA methylation (methyl) and gene expression (expr). Arrows indicate the causal direction of effects. The name of each model is underlined. (B) Mosaicplots illustrate the relative likelihoods of each model (x-axis), partitioned by the relative likelihoods of those involving pos-eQTMs (yellow) and neg-eQTMs (blue; y-axis), in fibroblasts (F), LCLs (L) and T-cells (T). The three types of models (INDEP, SME and SEM) are present in the three cell-types, suggesting that DNA methylation can have both active and passive roles in gene regulation. See Figure 4 –figure supplement 1 and Figure 4–Source data 1. (C) Heatmap of p value relative frequency distributions of spearman correlations between transcription factors (TF) and DNA methylation levels of eQTMs at their binding sites, sorted by π₁. The enrichment of significant associations can be appreciated by the accumulation of reddish colors, reflecting higher relative frequencies, at low p values, and yellowish colors, reflecting lower relative frequencies, at higher p values. These results highlight one of the possible mechanisms of a passive role of DNA methylation regarding gene expression. See Figure 4—figure supplements 2 and 3.

DOI: http://dx.doi.org/10.7554/eLife.00523.018

Figure 4—figure supplement 1. Passive and active roles of DNA methylation on gene regulation.

(A) For all exon-SNP-methyl triplets tested the best model was inferred using Bayesian networks (BN) and relative likelihood. Mosaicplots illustrate the relative frequencies of each model (x-axis), partitioned by the relative frequencies of pos-eQTMs (yellow) and neg-eQTMs (blue; y-axis), in fibroblasts (F), LCLs (L) and T-cells (T). (B) Same as in (A) only including high confidence calls (see ‘Materials and methods’ and Figure 4—source data 1).

DOI: http://dx.doi.org/10.7554/eLife.00523.020

Figure 4—figure supplement 2. Associations between TF abundance and DNA methylation at their target binding sites.

Observed (left panels) and expected (right panels) p value distributions of spearman correlations between transcription factor expression levels and DNA methylation levels of eQTMs at their binding sites (see ‘Materials and methods’) in fibroblasts (F), LCLs (L) and T-cells (T). π₁ statistic, reflecting the fraction of true positives, is indicated on top of each p value distribution.

DOI: http://dx.doi.org/10.7554/eLife.00523.021

Figure 4—figure supplement 3. Interactions between SNPs and transcription factor levels on DNA methylation.

(A) We tested whether genetic variants that could potentially alter TF binding would interact with TF abundance (transcription level) on their effect on DNA methylation levels. To do so we took the top mQTL SNPs that fell in TF peaks and whose associated methylation site correlated significantly with the TF expression level of that peak (10% FDR for both types of associations), and required that the SNP and the TF abundance were not correlated and that the SNP had at least four minor allele homozygotes (N = 114). (B) We find an enrichment of low p values for interactions between genetic variants and TF abundance on DNA methylation levels, with π₁ estimating 15% of true positives. (C) Plotted is the top interaction with p=1×10⁻⁴ involving the TF c-Jun in T-cells. The SNP falls in the binding peak of c-Jun. The methylation site and the SNP are 172 bp away from each other and both fall in an intron of gene SLC9A9.

DOI: http://dx.doi.org/10.7554/eLife.00523.022