期刊
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
卷 -, 期 -, 页码 -出版社
OXFORD UNIV PRESS
DOI: 10.1093/database/bax028
关键词
-
资金
- LifeMap Sciences Inc. (Massachusetts, USA)
- Crown Human Genome Center at the Weizmann Institute of Science
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 genonne-wide databases: the Encyclopedia of DNA Elements (ENCODE), the Ensennbl regulatory build, the functional annotation of the mammalian genonne (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 genonne), 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 genonne conformation assay. The individual scores based on each of these four methods, along with gene-enhancer genonnic 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.
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