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Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set.


ABSTRACT: 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.

SUBMITTER: Thibodeau SN 

PROVIDER: S-EPMC4663677 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set.

Thibodeau S N SN   French A J AJ   McDonnell S K SK   Cheville J J   Middha S S   Tillmans L L   Riska S S   Baheti S S   Larson M C MC   Fogarty Z Z   Zhang Y Y   Larson N N   Nair A A   O'Brien D D   Wang L L   Schaid D J DJ  

Nature communications 20151127


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 wit  ...[more]

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