BackgroundDNA methylation is an essential epigenetic mechanism involved in gene regulation and disease, but little is known about the mechanisms underlying inter-individual variation in methylation profiles. Here we measured methylation levels at 22,290 CpG dinucleotides in lymphoblastoid cell lines from 77 HapMap Yoruba individuals, for which genome-wide gene expression and genotype data were also available.ResultsAssociation analyses of methylation levels with more than three million common single nucleotide polymorphisms (SNPs) identified 180 CpG-sites in 173 genes that were associated with nearby SNPs (putatively in cis, usually within 5 kb) at a false discovery rate of 10%. The most intriguing trans signal was obtained for SNP rs10876043 in the disco-interacting protein 2 homolog B gene (DIP2B, previously postulated to play a role in DNA methylation), that had a genome-wide significant association with the first principal component of patterns of methylation; however, we found only modest signal of trans-acting associations overall. As expected, we found significant negative correlations between promoter methylation and gene expression levels measured by RNA-sequencing across genes. Finally, there was a significant overlap of SNPs that were associated with both methylation and gene expression levels.ConclusionsOur results demonstrate a strong genetic component to inter-individual variation in DNA methylation profiles. Furthermore, there was an enrichment of SNPs that affect both methylation and gene expression, providing evidence for shared mechanisms in a fraction of genes.

The mapping of expression quantitative trait loci (eQTLs) has emerged as an important tool for linking genetic variation to changes in gene regulation1-5. However, it remains difficult to identify the causal variants underlying eQTLs and little is known about the regulatory mechanisms by which they act. To address this gap, we used DNaseI sequencing to measure chromatin accessibility in 70 Yoruba lymphoblastoid cell lines (LCLs), for which genome-wide genotypes and estimates of gene expression levels are also available6-8. We obtained a total of 2.7 billion uniquely mapped DNase-seq reads, which allowed us to produce genome-wide maps of chromatin accessibility for each individual. We identified 9,595 locations at which DNase-seq read depth correlates significantly with genotype at a nearby SNP or indel (FDR=10%). We call such variants “DNaseI sensitivity Quantitative Trait Loci” (dsQTLs). We found that dsQTLs are strongly enriched within inferred transcription factor binding sites and are frequently associated with allele-specific changes in transcription factor binding. A substantial fraction (16%) of dsQTLs are also associated with variation in the expression levels of nearby genes, (namely, these loci are also classified as eQTLs). Conversely, we estimate that as many as 55% of eQTL SNPs are also dsQTLs. Our observations indicate that dsQTLs are highly abundant in the human genome, and are likely to be important contributors to phenotypic variation.

Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites corresponding to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-specific experimental data such as histone modifications and DNase I cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell types or tissues under diverse conditions.

Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.

A large fraction of the mammalian genome is organized into inactive chromosomal domains along the nuclear lamina. The mechanism by which these lamina associated domains (LADs) are established remains to be elucidated. Using genomic repositioning assays, we show that LADs, spanning the developmentally regulated IgH and Cyp3a loci contain discrete DNA regions that associate chromatin with the nuclear lamina and repress gene activity in fibroblasts. Lamina interaction is established during mitosis and likely involves the localized recruitment of Lamin B during late anaphase. Fine-scale mapping of LADs reveals numerous lamina-associating sequences (LASs), which are enriched for a GAGA motif. This repeated motif directs lamina association and is bound by the transcriptional repressor cKrox, in a complex with HDAC3 and Lap2β. Knockdown of cKrox or HDAC3 results in dissociation of LASs/LADs from the nuclear lamina. These results reveal a mechanism that couples nuclear compartmentalization of chromatin domains with the control of gene activity.