A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

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Functional mapping and annotation of genetic associations with FUMA

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Understanding how chromatin is organized within the nucleus and how this 3D architecture influences gene regulation, cell fate decisions and evolution are major questions in cell biology. Despite spectacular progress in this field, we still know remarkably little about the mechanisms underlying chromatin structure and how it can be established, reset and maintained. In this Review, we discuss the insights into chromatin architecture that have been gained through recent technological developments in quantitative biology, genomics and cell and molecular biology approaches and explain how these new concepts have been used to address important biological questions in development and disease.

Organization and function of the 3D genome.

A major challenge in understanding gene regulation is the unequivocal identification of enhancer elements and uncovering their connections to genes. We present GeneHancer, a novel database of human enhancers and their inferred target genes, in the framework of GeneCards. First, we integrated a total of 434 000 reported enhancers from four different genome-wide databases: the Encyclopedia of DNA Elements (ENCODE), the Ensembl regulatory build, the functional annotation of the mammalian genome (FANTOM) project and the VISTA Enhancer Browser. Employing an integration algorithm that aims to remove redundancy, GeneHancer portrays 285 000 integrated candidate enhancers (covering 12.4% of the genome), 94 000 of which are derived from more than one source, and each assigned an annotation-derived confidence score. GeneHancer subsequently links enhancers to genes, using: tissue co-expression correlation between genes and enhancer RNAs, as well as enhancer-targeted transcription factor genes; expression quantitative trait loci for variants within enhancers; and capture Hi-C, a promoter-specific genome conformation assay. The individual scores based on each of these four methods, along with gene–enhancer genomic distances, form the basis for GeneHancer’s combinatorial likelihood-based scores for enhancer–gene pairing. Finally, we define ‘elite’ enhancer–gene relations reflecting both a high-likelihood enhancer definition and a strong enhancer–gene association.

GeneHancer predictions are fully integrated in the widely used GeneCards Suite, whereby candidate enhancers and their annotations are displayed on every relevant GeneCard. This assists in the mapping of non-coding variants to enhancers, and via the linked genes, forms a basis for variant–phenotype interpretation of whole-genome sequences in health and disease.

Database URL: http://www.genecards.org/

/pdf/genehancer-genome-wide-integration-of-enhancers-and-target-9fq8xdfgtf.pdf

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

Spatiotemporal gene expression programmes are orchestrated by transcriptional enhancers, which are key regulatory DNA elements that engage in physical contacts with their target-gene promoters, often bridging considerable genomic distances. Recent progress in genomics, genome editing and microscopy methodologies have enabled the genome-wide mapping of enhancer-promoter contacts and their functional dissection. In this Review, we discuss novel concepts on how enhancer-promoter interactions are established and maintained, how the 3D architecture of mammalian genomes both facilitates and constrains enhancer-promoter contacts, and the role they play in gene expression control during normal development and disease.

Long-range enhancer-promoter contacts in gene expression control.

Transcriptional control in large genomes often requires looping interactions between distal DNA elements, such as enhancers and target promoters. Current chromosome conformation capture techniques do not offer sufficiently high resolution to interrogate these regulatory interactions on a genomic scale. Here we use Capture Hi-C (CHi-C), an adapted genome conformation assay, to examine the long-range interactions of almost 22,000 promoters in 2 human blood cell types. We identify over 1.6 million shared and cell type-restricted interactions spanning hundreds of kilobases between promoters and distal loci. Transcriptionally active genes contact enhancer-like elements, whereas transcriptionally inactive genes interact with previously uncharacterized elements marked by repressive features that may act as long-range silencers. Finally, we show that interacting loci are enriched for disease-associated SNPs, suggesting how distal mutations may disrupt the regulation of relevant genes. This study provides new insights and accessible tools to dissect the regulatory interactions that underlie normal and aberrant gene regulation.

Alice N Young

Papers

Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C