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

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For visualization purposes, we generated a UCSC custom track linked from GeneCards , which jointly displays all GeneHancer enhancers and genes in the selected genomic interval (defaulted to ±100 kb surrounding a selected gene). Of note, in the example shown, three of the five candidate enhancers overlapping with the beta globin locus control region are elite enhancers , and they show a total of 10 elite associations with the genes HBB, HBD, HBG1, HBG2 and HBE1. For the clustering procedure, enhancer elements from all of the above sources were used in order to define candidate enhancers.

  • Each candidate enhancer is documented in the GeneHancer database, embedded within the GeneCards knowledgebase and assigned a unique GeneHancer identifier.
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  • Overall, 7% of the gene–enhancer links are supported by multiple methods .
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The unified candidate enhancer compendium generated here forms a solid foundation for seeking gene–enhancer interactions. This was done by several different methods, and again, the principle of unifying several discovery avenues has been employed, as also described elsewhere . The methods included more direct inferences such as CHi-C or gene–enhancer distance, as well as indirect/indicative approaches such as genetic inference and co-expression analyses. It is therefore advisable to maximally rely on their combination, and to perform quality assurance steps, so as to increase reliability and reduce noise. This is reflected in the scoring system and elite status in GeneHancer. We note that at present a large majority (93%) of the gene–enhancer link inferences presented here are based on a single method. Such low overlap between methods questions the accuracy and reliability of single-method inferences.

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In major releases, the entire GeneCards Suite knowledgebase is updated, including rebuilding the genes, diseases and enhancers sets and their relationships; minor versions incorporate localized improvements for particular suite members. We are currently exploring methods to include enhancers and their target asher kohn chicago genes in the minor versions where feasible. As the collection of datasets used to predict enhancers keeps growing [e.g. ChIP-seq data ], our future updates will benefit from improvements in our enhancer sources. In addition, our enhancer pipeline accommodates addition and integration of new data sources.

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We also observe a relationship between the confidence scores of enhancer annotations and enhancer–gene associations, suggesting that the better supported enhancers show more consistent assignment to target genes . Enhancers with higher annotation confidence, as reflected in the enhancer score we developed, not only possess more evidence for https://turbo-tax.org/a enhancer–gene association but also have more links annotated as elite gene–enhancer associations. Each candidate enhancer is documented in the GeneHancer database, embedded within the GeneCards knowledgebase and assigned a unique GeneHancer identifier. Additionally, we define ‘elite enhancers’ as those that have two or more evidence sources.

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Notably, an eQTL signal between a variant within an enhancer and a gene whose expression is modified does not guarantee that the gene is targeted by the enhancer. To address this limitation, we performed two analyses which provided an estimate for the robustness of the methodology. In the first analysis we used promoters as controls, showing that in as much as 33% of the cases the eQTL connected the regulatory element to its known cognate gene, an appreciable rate of accuracy.

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