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Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set
Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663677/ https://www.ncbi.nlm.nih.gov/pubmed/26611117 http://dx.doi.org/10.1038/ncomms9653 |
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author | Thibodeau, S. N. French, A. J. McDonnell, S. K. Cheville, J. Middha, S. Tillmans, L. Riska, S. Baheti, S. Larson, M. C. Fogarty, Z. Zhang, Y. Larson, N. Nair, A. O'Brien, D. Wang, L. Schaid, D J. |
author_facet | Thibodeau, S. N. French, A. J. McDonnell, S. K. Cheville, J. Middha, S. Tillmans, L. Riska, S. Baheti, S. Larson, M. C. Fogarty, Z. Zhang, Y. Larson, N. Nair, A. O'Brien, D. Wang, L. Schaid, D J. |
author_sort | Thibodeau, S. N. |
collection | PubMed |
description | Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals. We analyse cis-acting associations where the transcript is located within 2 Mb (±1 Mb) of the risk SNP interval. Of all SNP–gene combinations tested, 41.7% of SNPs demonstrate a significant eQTL signal after adjustment for sample histology and 14 expression principal component covariates. Of the 100 PrCa-risk intervals, 51 have a significant eQTL signal and these are associated with 88 genes. This study provides a rich resource to study biological mechanisms underlying genetic risk to PrCa. |
format | Online Article Text |
id | pubmed-4663677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46636772015-12-21 Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set Thibodeau, S. N. French, A. J. McDonnell, S. K. Cheville, J. Middha, S. Tillmans, L. Riska, S. Baheti, S. Larson, M. C. Fogarty, Z. Zhang, Y. Larson, N. Nair, A. O'Brien, D. Wang, L. Schaid, D J. Nat Commun Article Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals. We analyse cis-acting associations where the transcript is located within 2 Mb (±1 Mb) of the risk SNP interval. Of all SNP–gene combinations tested, 41.7% of SNPs demonstrate a significant eQTL signal after adjustment for sample histology and 14 expression principal component covariates. Of the 100 PrCa-risk intervals, 51 have a significant eQTL signal and these are associated with 88 genes. This study provides a rich resource to study biological mechanisms underlying genetic risk to PrCa. Nature Pub. Group 2015-11-27 /pmc/articles/PMC4663677/ /pubmed/26611117 http://dx.doi.org/10.1038/ncomms9653 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Thibodeau, S. N. French, A. J. McDonnell, S. K. Cheville, J. Middha, S. Tillmans, L. Riska, S. Baheti, S. Larson, M. C. Fogarty, Z. Zhang, Y. Larson, N. Nair, A. O'Brien, D. Wang, L. Schaid, D J. Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title | Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title_full | Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title_fullStr | Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title_full_unstemmed | Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title_short | Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set |
title_sort | identification of candidate genes for prostate cancer-risk snps utilizing a normal prostate tissue eqtl data set |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663677/ https://www.ncbi.nlm.nih.gov/pubmed/26611117 http://dx.doi.org/10.1038/ncomms9653 |
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