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How far from the SNP may the causative genes be?
While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291268/ https://www.ncbi.nlm.nih.gov/pubmed/27269582 http://dx.doi.org/10.1093/nar/gkw500 |
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author | Brodie, Aharon Azaria, Johnathan Roy Ofran, Yanay |
author_facet | Brodie, Aharon Azaria, Johnathan Roy Ofran, Yanay |
author_sort | Brodie, Aharon |
collection | PubMed |
description | While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions. |
format | Online Article Text |
id | pubmed-5291268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-52912682017-02-10 How far from the SNP may the causative genes be? Brodie, Aharon Azaria, Johnathan Roy Ofran, Yanay Nucleic Acids Res Computational Biology While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions. Oxford University Press 2016-07-27 2016-06-06 /pmc/articles/PMC5291268/ /pubmed/27269582 http://dx.doi.org/10.1093/nar/gkw500 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Computational Biology Brodie, Aharon Azaria, Johnathan Roy Ofran, Yanay How far from the SNP may the causative genes be? |
title | How far from the SNP may the causative genes be? |
title_full | How far from the SNP may the causative genes be? |
title_fullStr | How far from the SNP may the causative genes be? |
title_full_unstemmed | How far from the SNP may the causative genes be? |
title_short | How far from the SNP may the causative genes be? |
title_sort | how far from the snp may the causative genes be? |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291268/ https://www.ncbi.nlm.nih.gov/pubmed/27269582 http://dx.doi.org/10.1093/nar/gkw500 |
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