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Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association.

ABSTRACT: The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.

ORGANISM(S): Homo sapiens

PROVIDER: GSE48152 | GEO | 2013/06/21

SECONDARY ACCESSION(S): PRJNA209050

REPOSITORIES: GEO

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Project description:Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2,112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters, and enrichment of co-localised functional elements. We found eQTLs for about 85% of analysed genes, 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 MB to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might often be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels, and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. We show for strongly heritable transcripts that a considerable gap still exists between total heritability resulting from all trans-chromosomes and explained variance of all identified trans-eSNPs. In contrast, the vast majority of most cis-heritability of these genes is already explained. Dissection of co-localised functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene-expression, pathways and disease related processes. Gene expression from human blood mononuclear cells from individuals of the Leipzig LIFE Heart Study was analyzed applying Illumina HT-12 v4 Expression BeadChips. After preprocessing, 28,295 expression probes for 2,112 individuals remained for analysis. In a population-based analysis, we identified associations between DNA variants and RNA expression levels and characterized these findings.

Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Total gene expression of normal breast sample from healthy controls. This submission represents transcriptome component of study.

Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Genotype of normal breast sample from healthy controls.

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Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association.

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