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GeneHancer: genome-wide integration of enhancers and target genes in GeneCards
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467550/ https://www.ncbi.nlm.nih.gov/pubmed/28605766 http://dx.doi.org/10.1093/database/bax028 |
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author | Fishilevich, Simon Nudel, Ron Rappaport, Noa Hadar, Rotem Plaschkes, Inbar Iny Stein, Tsippi Rosen, Naomi Kohn, Asher Twik, Michal Safran, Marilyn Lancet, Doron Cohen, Dana |
author_facet | Fishilevich, Simon Nudel, Ron Rappaport, Noa Hadar, Rotem Plaschkes, Inbar Iny Stein, Tsippi Rosen, Naomi Kohn, Asher Twik, Michal Safran, Marilyn Lancet, Doron Cohen, Dana |
author_sort | Fishilevich, Simon |
collection | PubMed |
description | 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/ |
format | Online Article Text |
id | pubmed-5467550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54675502017-06-19 GeneHancer: genome-wide integration of enhancers and target genes in GeneCards Fishilevich, Simon Nudel, Ron Rappaport, Noa Hadar, Rotem Plaschkes, Inbar Iny Stein, Tsippi Rosen, Naomi Kohn, Asher Twik, Michal Safran, Marilyn Lancet, Doron Cohen, Dana Database (Oxford) Original Article 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/ Oxford University Press 2017-04-17 /pmc/articles/PMC5467550/ /pubmed/28605766 http://dx.doi.org/10.1093/database/bax028 Text en © The Author(s) 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Fishilevich, Simon Nudel, Ron Rappaport, Noa Hadar, Rotem Plaschkes, Inbar Iny Stein, Tsippi Rosen, Naomi Kohn, Asher Twik, Michal Safran, Marilyn Lancet, Doron Cohen, Dana GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title_full | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title_fullStr | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title_full_unstemmed | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title_short | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards |
title_sort | genehancer: genome-wide integration of enhancers and target genes in genecards |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467550/ https://www.ncbi.nlm.nih.gov/pubmed/28605766 http://dx.doi.org/10.1093/database/bax028 |
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