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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2014
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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. |
format | Online Article Text |
id | pubmed-4217187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
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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