Single Nucleotide Polymorphisms with Cis-Regulatory Effects on Long Non-Coding Transcripts in Human Primary Monocytes

We applied genome-wide allele-specific expression analysis of monocytes from 188 samples. Monocytes were purified from white blood cells of healthy blood donors to detect cis-acting genetic variation that regulates the expression of long non-coding RNAs. We analysed 8929 regions harboring genes for potential long non-coding RNA that were retrieved from data from the ENCODE project. Of these regions, 60% were annotated as intergenic, which implies that they do not overlap with protein-coding genes. Focusing on the intergenic regions, and using stringent analysis of the allele-specific expression data, we detected robust cis-regulatory SNPs in 258 out of 489 informative intergenic regions included in the analysis. The cis-regulatory SNPs that were significantly associated with allele-specific expression of long non-coding RNAs were enriched to enhancer regions marked for active or bivalent, poised chromatin by histone modifications. Out of the lncRNA regions regulated by cis-acting regulatory SNPs, 20% (n = 52) were co-regulated with the closest protein coding gene. We compared the identified cis-regulatory SNPs with those in the catalog of SNPs identified by genome-wide association studies of human diseases and traits. This comparison identified 32 SNPs in loci from genome-wide association studies that displayed a strong association signal with allele-specific expression of non-coding RNAs in monocytes, with p-values ranging from 6.7×10⁻⁷ to 9.5×10⁻⁸⁹. The identified cis-regulatory SNPs are associated with diseases of the immune system, like multiple sclerosis and rheumatoid arthritis.     

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

Background

Localising regulatory variants that control gene expression is a challenge for genome research. Several studies have recently identified non-coding polymorphisms associated with inter-individual differences in gene expression. These approaches rely on the identification of signals of association against a background of variation due to other genetic and environmental factors. A complementary approach is to use an Allele-Specific Expression (ASE) assay, which is more robust to the effects of environmental variation and trans-acting genetic factors.

Methodology/Principal Findings

Here we apply an ASE method which utilises heterozygosity within an individual to compare expression of the two alleles of a gene in a single cell. We used individuals from three HapMap population groups and analysed the allelic expression of genes with cis-regulatory regions previously identified using total gene expression studies. We were able to replicate the results in five of the six genes tested, and refined the cis- associated regions to a small number of variants. We also showed that by using multi-populations it is possible to refine the associated cis-effect DNA regions.

Conclusions/Significance

We discuss the efficacy and drawbacks of both total gene expression and ASE approaches in the discovery of cis-acting variants. We show that the ASE approach has significant advantages as it is a cleaner representation of cis-acting effects. We also discuss the implication of using different populations to map cis-acting regions and the importance of finding regulatory variants which contribute to human phenotypic variation.     

Powerful Identification of Cis-regulatory SNPs in Human Primary Monocytes Using Allele-Specific Gene Expression

A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.     

A Robust Approach to Identifying Tissue-Specific Gene Expression Regulatory Variants Using Personalized Human Induced Pluripotent Stem Cells

Normal variation in gene expression due to regulatory polymorphisms is often masked by biological and experimental noise. In addition, some regulatory polymorphisms may become apparent only in specific tissues. We derived human induced pluripotent stem (iPS) cells from adult skin primary fibroblasts and attempted to detect tissue-specific cis-regulatory variants using in vitro cell differentiation. We used padlock probes and high-throughput sequencing for digital RNA allelotyping and measured allele-specific gene expression in primary fibroblasts, lymphoblastoid cells, iPS cells, and their differentiated derivatives. We show that allele-specific expression is both cell type and genotype-dependent, but the majority of detectable allele-specific expression loci remains consistent despite large changes in the cell type or the experimental condition following iPS reprogramming, except on the X-chromosome. We show that our approach to mapping cis-regulatory variants reduces in vitro experimental noise and reveals additional tissue-specific variants using skin-derived human iPS cells.     

A common regulatory variant in SLC35B4 influences the recurrence and survival of prostate cancer

Single nucleotide polymorphisms (SNPs) within the regulatory elements of a gene can alter gene expression, making these SNPs of prime importance for candidate gene association studies. We aimed to determine whether such regulatory variants are associated with clinical outcomes in three cohorts of patients with prostate cancer. We used RegulomeDB to identify potential regulatory variants based on in silico predictions and reviewed genome‐wide experimental findings. Overall, 131 putative regulatory SNPs with the highest confidence score on predicted functionality were investigated in two independent localized prostate cancer cohorts totalling 458 patients who underwent radical prostatectomy. The statistically significant SNPs identified in these two cohorts were then tested in an additional cohort of 504 patients with advanced prostate cancer. We identified one regulatory SNPs, rs1646724, that are consistently associated with increased risk of recurrence in localized disease (P = .003) and mortality in patients with advanced prostate cancer (P = .032) after adjusting for known clinicopathological factors. Further investigation revealed that rs1646724 may affect expression of SLC35B4, which encodes a glycosyltransferase, and that down‐regulation of SLC35B4 by transfecting short hairpin RNA in DU145 human prostate cancer cell suppressed proliferation, migration and invasion. Furthermore, we found increased SLC35B4 expression correlated with more aggressive forms of prostate cancer and poor patient prognosis. Our study provides robust evidence that regulatory genetic variants can affect clinical outcomes.     

Sex-Specific Effects of Cis-Regulatory Variants in Drosophila melanogaster

Sexual dimorphism at the level of gene expression is common and well documented, but much less is known about how different cis-regulatory alleles interact with the different trans-regulatory environments present in males and females. Here we show that sex-specific effects of cis-regulatory variants are common in Drosophila.     

Integrating GWAS and Expression Data for Functional Characterization of Disease-Associated SNPs: An Application to Follicular Lymphoma

Development of post-GWAS (genome-wide association study) methods are greatly needed for characterizing the function of trait-associated SNPs. Strategies integrating various biological data sets with GWAS results will provide insights into the mechanistic role of associated SNPs. Here, we present a method that integrates RNA sequencing (RNA-seq) and allele-specific expression data with GWAS data to further characterize SNPs associated with follicular lymphoma (FL). We investigated the influence on gene expression of three established FL-associated loci—rs10484561, rs2647012, and rs6457327—by measuring their correlation with human-leukocyte-antigen (HLA) expression levels obtained from publicly available RNA-seq expression data sets from lymphoblastoid cell lines. Our results suggest that SNPs linked to the protective variant rs2647012 exert their effect by a cis-regulatory mechanism involving modulation of HLA-DQB1 expression. In contrast, no effect on HLA expression was observed for the colocalized risk variant rs10484561. The application of integrative methods, such as those presented here, to other post-GWAS investigations will help identify causal disease variants and enhance our understanding of biological disease mechanisms.     

Identification of regulatory variants of carboxylesterase 1 (CES1): A proof-of-concept study for the application of the Allele-Specific Protein Expression (ASPE) assay in identifying cis-acting regulatory genetic polymorphisms

It is challenging to study regulatory genetic variants as gene expression is affected by both genetic polymorphisms and non-genetic regulators. The mRNA allele-specific expression (ASE) assay has been increasingly used for the study of cis-acting regulatory variants because cis-acting variants affect gene expression in an allele-specific manner. However, poor correlations between mRNA and protein expressions were observed for many genes, highlighting the importance of studying gene expression regulation at the protein level. In the present study, we conducted a proof-of-concept study to utilize a recently developed allele-specific protein expression (ASPE) assay to identify the cis-acting regulatory variants of CES1 using a large set of human liver samples. The CES1 gene encodes for carboxylesterase 1 (CES1), the most abundant hepatic hydrolase in humans. Two cis-acting regulatory variants were found to be significantly associated with CES1 ASPE, CES1 protein expression, and its catalytic activity on enalapril hydrolysis in human livers. Compared to conventional gene expression-based approaches, ASPE demonstrated an improved statistical power to detect regulatory variants with small effect sizes since allelic protein expression ratios are less prone to the influence of non-genetic regulators (e.g., diseases and inducers). This study suggests that the ASPE approach is a powerful tool for identifying cis-regulatory variants.     

Allele-specific expression and eQTL analysis in mouse adipose tissue

Background

The simplest definition of cis-eQTLs versus trans, refers to genetic variants that affect expression in an allele specific manner, with implications on underlying mechanism. Yet, due to technical limitations of expression microarrays, the vast majority of eQTL studies performed in the last decade used a genomic distance based definition as a surrogate for cis, therefore exploring local rather than cis-eQTLs.

Results

In this study we use RNAseq to explore allele specific expression (ASE) in adipose tissue of male and female F1 mice, produced from reciprocal crosses of C57BL/6J and DBA/2J strains. Comparison of the identified cis-eQTLs, to local-eQTLs, that were obtained from adipose tissue expression in two previous population based studies in our laboratory, yields poor overlap between the two mapping approaches, while both local-eQTL studies show highly concordant results. Specifically, local-eQTL studies show ~60% overlap between themselves, while only 15-20% of local-eQTLs are identified as cis by ASE, and less than 50% of ASE genes are recovered in local-eQTL studies. Utilizing recently published ENCODE data, we also find that ASE genes show significant bias for SNPs prevalence in DNase I hypersensitive sites that is ASE direction specific.

Conclusions

We suggest a new approach to analysis of allele specific expression that is more sensitive and accurate than the commonly used fisher or chi-square statistics. Our analysis indicates that technical differences between the cis and local-eQTL approaches, such as differences in genomic background or sex specificity, account for relatively small fraction of the discrepancy. Therefore, we suggest that the differences between two eQTL mapping approaches may facilitate sorting of SNP-eQTL interactions into true cis and trans, and that a considerable portion of local-eQTL may actually represent trans interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-471) contains supplementary material, which is available to authorized users.