Validating Discovered Cis-Acting Regulatory Genetic Variants: Application of an Allele Specific Expression Approach to HapMap Populations

Campino, Susana; Forton, Julian; Raj, Srilakshmi M.; Mohr, Bert; Auburn, Sarah; Fry, Andrew E.; Mangano, Valentina; Vandiedonck, Claire; Richardson, Anna; Rockett, Kirk A.; Clark, Taane G.; Kwiatkowski, Dominic P.

doi:10.1371/journal.pone.0004105

Cited by 23 publications

(30 citation statements)

References 17 publications

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“…AI for a given gene can be measured when an individual is heterozygous for a transcribed polymorphism. Significant deviations in from a 1:1 ratio in RNA levels indicate genetic and/or epigenetic cis - influences on a gene (Babak et al, 2010; Campino et al, 2008; Ge et al, 2009; Heap et al, 2010). Recently released TCGA RNA-sequencing data enables evaluation of AI in tumor samples (Methods).…”

Section: Eqtl Analysis Of Breast Cancer Risk Locimentioning

confidence: 99%

Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

Seo

Stranger

et al. 2013

Cell

296

317

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Summary Germline determinants of gene expression in tumors are less studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL) based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTL saccounted for 1.2% of the total variation of tumor gene expression, while somatic copy number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in discovery of three variants that are significantly associated with transcript levels (FDR<0.1). In a novel trans- based analysis, an additional three risk loci were identified to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci.

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Section: Eqtl Analysis Of Breast Cancer Risk Locimentioning

confidence: 99%

Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

Seo

Stranger

et al. 2013

Cell

296

317

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“…Many AE studies compare the AER in cDNA to the AER in genomic DNA (gDNA) from the same samples, with the gDNA as a reference for equal levels of the two transcript alleles [Bray et al, 2004; Campino et al, 2008; Pant et al, 2006; Fogarty et al, 2010]. When a single rSNP is in r 2 =1 with the tSNP, the underlying AER will be, on average, consistently higher or lower than the gDNA level (Figure 1A) and a t test comparing the mean AER between cDNA and gDNA or comparing the mean AER of cDNA normalized by gDNA to 1 can be performed [Bray et al, 2004; Campino et al, 2008]. The use of gDNA as a reference assumes that any technical bias in measurement of AER for the cDNA is the same for the gDNA.…”

Section: Introductionmentioning

confidence: 99%

“…For samples with known rSNP-tSNP haplotypes (rSNP-tSNP phase-known data), a regression-based test for AE-rSNP association can be used [Campino et al, 2008; Ge et al, 2009], in which the haplogenotype of the rSNP homozygotes is coded as intermediate to the two haplogenotypes of the double heterozygotes (for example,

\frac{normalr normalT}{normalR normalt} = - 1, \frac{normalR normalT}{normalR normalt} = \frac{normalr normalT}{normalr normalt} = 0, \frac{normalR normalT}{normalr normalt} = 1

).…”

Section: Introductionmentioning

confidence: 99%

Detection of cis-acting regulatory SNPs using allelic expression data

Xiao

Scott

2011

Genet. Epidemiol.

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Allelic expression (AE) imbalance between the two alleles of a gene can be used to detect cis-acting regulatory SNPs (rSNPs) in individuals heterozygous for a transcribed SNP (tSNP). In this paper, we propose three tests for AE analysis focusing on phase-unknown data and any degree of linkage disequilibrium (LD) between the rSNP and tSNP: a test based on the minimum p-value of a one-sided F and two-sided t tests proposed previously for phase-unknown data, a test that combines these two p-values, and a mixture-model based test. We compare these three tests to the F and t tests and an existing regression-based test for phase-known data. We show that the ranking of the tests based on power depends most strongly on the magnitude of the LD between the rSNP and tSNP. For phase-unknown data we find that under a range of scenarios, our proposed tests have higher power than the F and t tests when LD between the rSNP and tSNP is moderate (~.2 < D'RT < ~.8). We further demonstrate that the presence of a second ungenotyped rSNP almost never invalidates the proposed tests nor substantially changes their power rankings. For detection of cis-acting regulatory SNPs using phase-unknown AE data, we recommend the F test when the rSNP and tSNP are in or near linkage equilibrium (D'RT < .2); the t test when the two SNPs are in strong LD (D'RT > .7); and the mixture-model based test for intermediate LD levels (.2 < D'RT < .7).

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“…The linkage disequilibrium structure of these 2 genes was determined, with 2 haplotype blocks determined. The 3′UTR of the ZNRD1 gene is putatively involved in posttranscriptional mRNA regulation [33], [34]. In addition, the SNP we identified (rs16896970) showed a linkage disequilibrium with the SNP (rs3188482) (Table S1; D′ = 0.956), and the SNP (rs3188482) showed a linkage disequilibrium with the SNP (rs1048412) [31].…”

Section: Resultsmentioning

confidence: 80%

Variants in ZNRD1 Gene Predict HIV-1/AIDS Disease Progression in a Han Chinese Population in Taiwan

et al. 2013

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Patients demonstrate notable variations in disease progression following human immunodeficiency virus (HIV) infection. We aimed to identify ZNRD1 and RNF39 genetic variants linked to AIDS progression. We conducted a genetic association study in HIV-1-infected Han Chinese patients residing in Taiwan. The clinical characteristics of 143 HIV-1-infected patients were measured, and patients were split into 2 groups: AIDS progression and AIDS non-progression. Genotyping of ZNRD1 and RNF39 was performed in all participants. We found that patients in the AIDS progression group had higher HIV-1 viral loads and lower CD4 cell counts than did patients in the AIDS non-progression group. The frequency of the AA genotype of ZNRD1 (rs16896970) was lower in the AIDS progression group than in the AIDS non-progression group. Patients with AA genotypes had lower levels of HIV-1 viral loads and higher levels of CD4 cell counts than did patients with AG+GG genotypes. AIDS progression in patients with the AA group is significantly different from that in patients with the AG and GG groups by using Kaplan-Meier survival analysis. The hazard ratio for progression was lower in the AA group than in the AG and GG groups. We identified a SNP that contributes to AIDS progression in HIV-1-infected patients in this population. This SNP had a significant protective influence on AIDS progression, and polymorphisms of the ZNRD1 gene may play a role in the pathogenesis of HIV-1 infection.

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Validating Discovered Cis-Acting Regulatory Genetic Variants: Application of an Allele Specific Expression Approach to HapMap Populations

Cited by 23 publications

References 17 publications

Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

Detection of cis-acting regulatory SNPs using allelic expression data

Variants in ZNRD1 Gene Predict HIV-1/AIDS Disease Progression in a Han Chinese Population in Taiwan

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