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Associating disease-related genetic variants in intergenic regions to the genes they impact

We present a method to assist in interpretation of the functional impact of intergenic disease-associated SNPs that is not limited to search strategies proximal to the SNP. The method builds on two sources of external knowledge: the growing understanding of three-dimensional spatial relationships in...

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Autores principales: Macintyre, Geoff, Jimeno Yepes, Antonio, Ong, Cheng Soon, Verspoor, Karin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4217187/
https://www.ncbi.nlm.nih.gov/pubmed/25374782
http://dx.doi.org/10.7717/peerj.639
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author Macintyre, Geoff
Jimeno Yepes, Antonio
Ong, Cheng Soon
Verspoor, Karin
author_facet Macintyre, Geoff
Jimeno Yepes, Antonio
Ong, Cheng Soon
Verspoor, Karin
author_sort Macintyre, Geoff
collection PubMed
description We present a method to assist in interpretation of the functional impact of intergenic disease-associated SNPs that is not limited to search strategies proximal to the SNP. The method builds on two sources of external knowledge: the growing understanding of three-dimensional spatial relationships in the genome, and the substantial repository of information about relationships among genetic variants, genes, and diseases captured in the published biomedical literature. We integrate chromatin conformation capture data (HiC) with literature support to rank putative target genes of intergenic disease-associated SNPs. We demonstrate that this hybrid method outperforms a genomic distance baseline on a small test set of expression quantitative trait loci, as well as either method individually. In addition, we show the potential for this method to uncover relationships between intergenic SNPs and target genes across chromosomes. With more extensive chromatin conformation capture data becoming readily available, this method provides a way forward towards functional interpretation of SNPs in the context of the three dimensional structure of the genome in the nucleus.
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spelling pubmed-42171872014-11-05 Associating disease-related genetic variants in intergenic regions to the genes they impact Macintyre, Geoff Jimeno Yepes, Antonio Ong, Cheng Soon Verspoor, Karin PeerJ Bioinformatics We present a method to assist in interpretation of the functional impact of intergenic disease-associated SNPs that is not limited to search strategies proximal to the SNP. The method builds on two sources of external knowledge: the growing understanding of three-dimensional spatial relationships in the genome, and the substantial repository of information about relationships among genetic variants, genes, and diseases captured in the published biomedical literature. We integrate chromatin conformation capture data (HiC) with literature support to rank putative target genes of intergenic disease-associated SNPs. We demonstrate that this hybrid method outperforms a genomic distance baseline on a small test set of expression quantitative trait loci, as well as either method individually. In addition, we show the potential for this method to uncover relationships between intergenic SNPs and target genes across chromosomes. With more extensive chromatin conformation capture data becoming readily available, this method provides a way forward towards functional interpretation of SNPs in the context of the three dimensional structure of the genome in the nucleus. PeerJ Inc. 2014-10-23 /pmc/articles/PMC4217187/ /pubmed/25374782 http://dx.doi.org/10.7717/peerj.639 Text en © 2014 Macintyre et al. 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 use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Macintyre, Geoff
Jimeno Yepes, Antonio
Ong, Cheng Soon
Verspoor, Karin
Associating disease-related genetic variants in intergenic regions to the genes they impact
title Associating disease-related genetic variants in intergenic regions to the genes they impact
title_full Associating disease-related genetic variants in intergenic regions to the genes they impact
title_fullStr Associating disease-related genetic variants in intergenic regions to the genes they impact
title_full_unstemmed Associating disease-related genetic variants in intergenic regions to the genes they impact
title_short Associating disease-related genetic variants in intergenic regions to the genes they impact
title_sort associating disease-related genetic variants in intergenic regions to the genes they impact
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4217187/
https://www.ncbi.nlm.nih.gov/pubmed/25374782
http://dx.doi.org/10.7717/peerj.639
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