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

Thibodeau SN, French AJ, McDonnell SK, Cheville J, Middha S, Tillmans L, Riska S, Baheti S, Larson MC, Fogarty Z, Zhang Y, Larson N, Nair A, O'Brien D, Wang L, Schaid DJ - Nat Commun (2015)

Bottom Line: We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, Minnesota 55905, USA.

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.

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Related in: MedlinePlus

Regional association plots for regions containing multiple risk SNPs.Regional association plots are presented for three gene regions, each of which contain two or more PrCa-risk SNPs with varying degrees of LD between them (r2=0.54 for GGCX region, r2<0.2 for BMPR1B region and r2=0.67 for HNF1B region. The x axis shows the chromosomal position of the SNPs (with analyzed gene in the region displayed below) and the y axis is the −log10 (P value) obtained by regressing normalized expression levels for the gene listed in the panel title on the number of minor alleles of each SNP genotype adjusted for histologic characteristics and 14 expression principal components. The position of the PrCa-risk SNP is indicated by a dotted red vertical line with the eQTL result displayed as diamond. All Bonferroni significant results are coloured, with the colour defined by LD between the SNP and the PrCa-risk SNP listed in the panel title (LD r2>0.5 red, between 0.2–0.5 green and ≤0.2 blue). The right y axis shows the recombination rate (purple dotted lines mark recombination locations). The bottom half of each panel contains an LD heat map of the significant SNPs in the region (if >1,000 significant SNPs, only the top 1,000 SNPs in the region are shown). For each gene region, two or more plots are shown depending on the number of risk SNPs in the region, one for each risk SNP. The points are coloured according to LD with the risk SNP listed in the panel title (r2>0.5, red; between 0.2–0.5, green; and ≤0.2, blue). The eQTL result for the PrCa-risk SNP listed in the panel title is displayed as diamond, the data points for all of the other PrCa-risk SNPs are displayed as an open circle.
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f2: Regional association plots for regions containing multiple risk SNPs.Regional association plots are presented for three gene regions, each of which contain two or more PrCa-risk SNPs with varying degrees of LD between them (r2=0.54 for GGCX region, r2<0.2 for BMPR1B region and r2=0.67 for HNF1B region. The x axis shows the chromosomal position of the SNPs (with analyzed gene in the region displayed below) and the y axis is the −log10 (P value) obtained by regressing normalized expression levels for the gene listed in the panel title on the number of minor alleles of each SNP genotype adjusted for histologic characteristics and 14 expression principal components. The position of the PrCa-risk SNP is indicated by a dotted red vertical line with the eQTL result displayed as diamond. All Bonferroni significant results are coloured, with the colour defined by LD between the SNP and the PrCa-risk SNP listed in the panel title (LD r2>0.5 red, between 0.2–0.5 green and ≤0.2 blue). The right y axis shows the recombination rate (purple dotted lines mark recombination locations). The bottom half of each panel contains an LD heat map of the significant SNPs in the region (if >1,000 significant SNPs, only the top 1,000 SNPs in the region are shown). For each gene region, two or more plots are shown depending on the number of risk SNPs in the region, one for each risk SNP. The points are coloured according to LD with the risk SNP listed in the panel title (r2>0.5, red; between 0.2–0.5, green; and ≤0.2, blue). The eQTL result for the PrCa-risk SNP listed in the panel title is displayed as diamond, the data points for all of the other PrCa-risk SNPs are displayed as an open circle.

Mentions: In addition, 10 of these 51 regions had multiple reported risk SNPs in close proximity, ranging from 2 to 5 risk SNPs per region (2 risk SNPs in 7 regions, 3 risk SNPs in 2 regions and 5 risk SNPs in 1 region). The LD between the risk SNPs varied, ranging from an r2 of <0.2 to 1 (15 with an r2 of <0.25, 3 from 0.5 to 0.7 and 4 from 0.7 to 1.0). Examples for 4 of the regions where r2 was <0.7 among the risk SNPs are shown in Figs 2 and 3 (r2=0.54 for the risk SNPs in the GGCX region, r2<0.2 for those associated with BMPR1B, r2=0.67 for HNF1B and r2<0.25 within the CHMP2B region). For GGCX (Fig. 2), the data indicate that the eQTL signal is driven largely by the SNPs in high LD with the risk SNP rs10187424 (lower left panel). The risk SNP rs2028898 (upper left panel) is not likely to be an independent risk factor, as it is in low LD with rs10187424. BMPR1B (Fig. 2) demonstrates a more complex region. The peak eQTL signal is in high LD with the risk SNP rs12500426 (upper middle panel). The risk SNP rs17021918 (lower middle panel), which is not in LD with rs12500426 (r2<0.2), shows another cluster of high-LD-SNPs that have a significant eQTL signal, yet are in moderate to low LD with the peak signal. These data suggest the presence of two independent regulatory domains, each tagged by the two reported risk SNPs. Finally, there is a third cluster of significant eQTL signals that are not in LD with either of the two reported risk SNPs (r2<0.2 for both, blue points clustered around 96 Mb), suggesting a third independent regulatory domain for BMPR1B. Both HNF1B (Fig. 2) and CHMP2B (Fig. 3) demonstrate the presence of reported risk SNPs that are not in LD with each other and where the eQTL signal is driven by one of the risk-SNP clusters. Thus, in each case, there is no eQTL signal for one (HNF1B) or more (CHMP2B) of the reported risk SNPs.


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

Thibodeau SN, French AJ, McDonnell SK, Cheville J, Middha S, Tillmans L, Riska S, Baheti S, Larson MC, Fogarty Z, Zhang Y, Larson N, Nair A, O'Brien D, Wang L, Schaid DJ - Nat Commun (2015)

Regional association plots for regions containing multiple risk SNPs.Regional association plots are presented for three gene regions, each of which contain two or more PrCa-risk SNPs with varying degrees of LD between them (r2=0.54 for GGCX region, r2<0.2 for BMPR1B region and r2=0.67 for HNF1B region. The x axis shows the chromosomal position of the SNPs (with analyzed gene in the region displayed below) and the y axis is the −log10 (P value) obtained by regressing normalized expression levels for the gene listed in the panel title on the number of minor alleles of each SNP genotype adjusted for histologic characteristics and 14 expression principal components. The position of the PrCa-risk SNP is indicated by a dotted red vertical line with the eQTL result displayed as diamond. All Bonferroni significant results are coloured, with the colour defined by LD between the SNP and the PrCa-risk SNP listed in the panel title (LD r2>0.5 red, between 0.2–0.5 green and ≤0.2 blue). The right y axis shows the recombination rate (purple dotted lines mark recombination locations). The bottom half of each panel contains an LD heat map of the significant SNPs in the region (if >1,000 significant SNPs, only the top 1,000 SNPs in the region are shown). For each gene region, two or more plots are shown depending on the number of risk SNPs in the region, one for each risk SNP. The points are coloured according to LD with the risk SNP listed in the panel title (r2>0.5, red; between 0.2–0.5, green; and ≤0.2, blue). The eQTL result for the PrCa-risk SNP listed in the panel title is displayed as diamond, the data points for all of the other PrCa-risk SNPs are displayed as an open circle.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4663677&req=5

f2: Regional association plots for regions containing multiple risk SNPs.Regional association plots are presented for three gene regions, each of which contain two or more PrCa-risk SNPs with varying degrees of LD between them (r2=0.54 for GGCX region, r2<0.2 for BMPR1B region and r2=0.67 for HNF1B region. The x axis shows the chromosomal position of the SNPs (with analyzed gene in the region displayed below) and the y axis is the −log10 (P value) obtained by regressing normalized expression levels for the gene listed in the panel title on the number of minor alleles of each SNP genotype adjusted for histologic characteristics and 14 expression principal components. The position of the PrCa-risk SNP is indicated by a dotted red vertical line with the eQTL result displayed as diamond. All Bonferroni significant results are coloured, with the colour defined by LD between the SNP and the PrCa-risk SNP listed in the panel title (LD r2>0.5 red, between 0.2–0.5 green and ≤0.2 blue). The right y axis shows the recombination rate (purple dotted lines mark recombination locations). The bottom half of each panel contains an LD heat map of the significant SNPs in the region (if >1,000 significant SNPs, only the top 1,000 SNPs in the region are shown). For each gene region, two or more plots are shown depending on the number of risk SNPs in the region, one for each risk SNP. The points are coloured according to LD with the risk SNP listed in the panel title (r2>0.5, red; between 0.2–0.5, green; and ≤0.2, blue). The eQTL result for the PrCa-risk SNP listed in the panel title is displayed as diamond, the data points for all of the other PrCa-risk SNPs are displayed as an open circle.
Mentions: In addition, 10 of these 51 regions had multiple reported risk SNPs in close proximity, ranging from 2 to 5 risk SNPs per region (2 risk SNPs in 7 regions, 3 risk SNPs in 2 regions and 5 risk SNPs in 1 region). The LD between the risk SNPs varied, ranging from an r2 of <0.2 to 1 (15 with an r2 of <0.25, 3 from 0.5 to 0.7 and 4 from 0.7 to 1.0). Examples for 4 of the regions where r2 was <0.7 among the risk SNPs are shown in Figs 2 and 3 (r2=0.54 for the risk SNPs in the GGCX region, r2<0.2 for those associated with BMPR1B, r2=0.67 for HNF1B and r2<0.25 within the CHMP2B region). For GGCX (Fig. 2), the data indicate that the eQTL signal is driven largely by the SNPs in high LD with the risk SNP rs10187424 (lower left panel). The risk SNP rs2028898 (upper left panel) is not likely to be an independent risk factor, as it is in low LD with rs10187424. BMPR1B (Fig. 2) demonstrates a more complex region. The peak eQTL signal is in high LD with the risk SNP rs12500426 (upper middle panel). The risk SNP rs17021918 (lower middle panel), which is not in LD with rs12500426 (r2<0.2), shows another cluster of high-LD-SNPs that have a significant eQTL signal, yet are in moderate to low LD with the peak signal. These data suggest the presence of two independent regulatory domains, each tagged by the two reported risk SNPs. Finally, there is a third cluster of significant eQTL signals that are not in LD with either of the two reported risk SNPs (r2<0.2 for both, blue points clustered around 96 Mb), suggesting a third independent regulatory domain for BMPR1B. Both HNF1B (Fig. 2) and CHMP2B (Fig. 3) demonstrate the presence of reported risk SNPs that are not in LD with each other and where the eQTL signal is driven by one of the risk-SNP clusters. Thus, in each case, there is no eQTL signal for one (HNF1B) or more (CHMP2B) of the reported risk SNPs.

Bottom Line: We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, Minnesota 55905, USA.

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.

Show MeSH
Related in: MedlinePlus