The mapping of expression quantitative trait loci (eQTLs) has emerged as an important tool for linking genetic variation to changes in gene regulation. However, it remains difficult to identify the causal variants underlying eQTLs, and little is known about the regulatory mechanisms by which they act. Here we show that genetic variants that modify chromatin accessibility and transcription factor binding are a major mechanism through which genetic variation leads to gene expression differences among humans. We used DNase I sequencing to measure chromatin accessibility in 70 Yoruba lymphoblastoid cell lines, for which genome-wide genotypes and estimates of gene expression levels are also available. We obtained a total of 2.7 billion uniquely mapped DNase I-sequencing (DNase-seq) reads, which allowed us to produce genome-wide maps of chromatin accessibility for each individual. We identified 8,902 locations at which the DNase-seq read depth correlated significantly with genotype at a nearby single nucleotide polymorphism or insertion/deletion (false discovery rate = 10%). We call such variants 'DNase I 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 (that is, these loci are also classified as eQTLs). Conversely, we estimate that as many as 55% of eQTL single nucleotide polymorphisms 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.

ABSTRACT: BACKGROUND: Expression quantitative trait loci (eQTLs) are likely to play an important role in the genetics of complex traits; however, their functional basis remains poorly understood. Using the HapMap lymphoblastoid cell lines, we combine 1000 Genomes genotypes and an extensive catalogue of human functional elements to investigate the biological mechanisms that eQTLs perturb. RESULTS: We use a Bayesian hierarchical model to estimate the enrichment of eQTLs in a wide variety of regulatory annotations. We find that approximately 40% of eQTLs occur in open chromatin, and that they are particularly enriched in transcription factor binding sites, suggesting that many directly impact protein-DNA interactions. Analysis of core promoter regions shows that eQTLs also frequently disrupt some known core promoter motifs but, surprisingly, are not enriched in other well-known motifs such as the TATA box. We also show that information from regulatory annotations alone, when weighted by the hierarchical model, can provide a meaningful ranking of the SNPs that are most likely to drive gene expression variation. CONCLUSIONS: Our study demonstrates how regulatory annotation and the association signal derived from eQTL-mapping can be combined into a single framework. We used this approach to further our understanding of the biology that drives human gene expression variation, and of the putatively causal SNPs that underlie it.

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the 'missing heritability problem'. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Tuberculosis (TB) is a major public health problem. One-third of the world's population is estimated to be infected with Mycobacterium tuberculosis (MTB), the etiological agent causing TB, and active disease kills nearly 2 million individuals worldwide every year. Several lines of evidence indicate that interindividual variation in susceptibility to TB has a heritable component, yet we still know little about the underlying genetic architecture. To address this, we performed a genome-wide mapping study of loci that are associated with functional variation in immune response to MTB. Specifically, we characterized transcript and protein expression levels and mapped expression quantitative trait loci (eQTL) in primary dendritic cells (DCs) from 65 individuals, before and after infection with MTB. We found 198 response eQTL, namely loci that were associated with variation in gene expression levels in either untreated or MTB-infected DCs, but not both. These response eQTL are associated with natural regulatory variation that likely affects (directly or indirectly) host interaction with MTB. Indeed, when we integrated our data with results from a genome-wide association study (GWAS) for pulmonary TB, we found that the response eQTL were more likely to be genetically associated with the disease. We thus identified a number of candidate loci, including the MAPK phosphatase DUSP14 in particular, that are promising susceptibility genes to pulmonary TB.

The modification of DNA by methylation is an important epigenetic mechanism that affects the spatial and temporal regulation of gene expression. Methylation patterns have been described in many contexts within and across a range of species. However, the extent to which changes in methylation might underlie inter-species differences in gene regulation, in particular between humans and other primates, has not yet been studied. To this end, we studied DNA methylation patterns in livers, hearts, and kidneys from multiple humans and chimpanzees, using tissue samples for which genome-wide gene expression data were also available. Using the multi-species gene expression and methylation data for 7,723 genes, we were able to study the role of promoter DNA methylation in the evolution of gene regulation across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. However, we also found a large number of gene expression differences between species that might be explained, at least in part, by corresponding differences in methylation levels. In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%-18% of differences in gene expression levels between humans and chimpanzees.

BACKGROUND DNA 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. RESULTS Association 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. CONCLUSIONS Our 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.

While the majority of multiexonic human genes show some evidence of alternative splicing, it is unclear what fraction of observed splice forms is functionally relevant. In this study, we examine the extent of alternative splicing in human cells using deep RNA sequencing and de novo identification of splice junctions. We demonstrate the existence of a large class of low abundance isoforms, encompassing approximately 150,000 previously unannotated splice junctions in our data. Newly-identified splice sites show little evidence of evolutionary conservation, suggesting that the majority are due to erroneous splice site choice. We show that sequence motifs involved in the recognition of exons are enriched in the vicinity of unconserved splice sites. We estimate that the average intron has a splicing error rate of approximately 0.7% and show that introns in highly expressed genes are spliced more accurately, likely due to their shorter length. These results implicate noisy splicing as an important property of genome evolution.

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.

Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. Although all eQTL studies so far have assayed messenger RNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. By pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated untranslated regions and more than 100 new putative protein-coding exons. Using the genotypes from the HapMap project, we identified more than a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act by a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within and near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing and allele-specific expression across individuals.