The use of allelic expression differences to ascertain functional polymorphisms acting in cis: analysis of MMP1 transcripts in normal lung tissue

Association of SLC11A1 (NRAMP1) polymorphisms with pulmonary Mycobacterium avium complex infection

Although genetic variants in SLC11A1 (NRAMP1) have been associated with mycobacterial diseases, these findings have not been extensively validated in pulmonary Mycobacterium avium complex (MAC) infection. This study investigated the genomic structure of SLC11A1 and its association with MAC infection. Nineteen polymorphic loci were genotyped in European descendents and the Japanese population. Linkage disequilibrium (LD) structures and frequencies of major haplotypes differed between these 2 populations. Tag single nucleotide polymorphisms (SNPs) were chosen from the data set, and 6 polymorphic sites were genotyped in 122 pulmonary MAC cases and 211 controls from Japan. We observed that the T allele of rs2279014 in the 3' untranslated region was associated with protection from MAC disease when comparing allele frequencies with an odds ratio of 0.582 (95% confidence interval 0.379-0.894, p = 0.013). The frequencies of haplotypes constructed with the above 6 variants did not differ between cases and controls. Allele-specific expression imbalance of SLC11A1 mRNA was evaluated in peripheral blood cells from heterozygous individuals, but no difference was observed among haplotypes. Although the significance was modest, rs2279014 is in strong LD with nearby SNPs and further studies are required for conclusive validation.

Comparing methods for mapping cis acting polymorphisms using allelic expression ratios

Genome wide association studies frequently reveal associations between disease susceptibility and polymorphisms outside coding regions. Such associations cannot always be explained by linkage disequilibrium with changes affecting the transcription products. This has stimulated the interest in characterising sequence variation influencing gene expression levels, in particular in changes acting in cis. Differences in transcription between the two alleles at an autosomal locus can be used to test the association between candidate polymorphisms and the modulation of gene expression in cis. This type of approach requires at least one transcribed polymorphism and one candidate polymorphism. In the past five years, different methods have been proposed to analyse such data. Here we use simulations and real data sets to compare the power of some of these methods. The results show that when it is not possible to determine the phase between the transcribed and potentially cis acting allele there is some advantage in using methods that estimate phased genotype and effect on expression simultaneously. However when the phase can be determined, simple regression models seem preferable because of their simplicity and flexibility. The simulations and the analysis of experimental data suggest that in the majority of situations, methods that assume a lognormal distribution of the allelic expression ratios are both robust to deviations from this assumption and more powerful than alternatives that do not make these assumptions.

Allelic imbalance (AI) identifies novel tissue-specific cis-regulatory variation for human UGT2B15

Allelic imbalance (AI) is a powerful tool to identify cis-regulatory variation for gene expression. UGT2B15 is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In this study, we measured the relative expression of two alleles at this gene by using SNP rs1902023:G>T. An excess of the G over the T allele was consistently observed in liver (P<0.001), but not in breast (P=0.06) samples, suggesting that SNPs in strong linkage disequilibrium with G253T regulate UGT2B15 expression in liver. Seven such SNPs were identified by resequencing the promoter and exon 1, which define two distinct haplotypes. Reporter gene assays confirmed that one haplotype displayed approximately 20% higher promoter activity compared to the other major haplotype in liver HepG2 (P<0.001), but not in breast MCF-7 (P=0.540) cells. Reporter gene assays with additional constructs pointed to rs34010522:G>T and rs35513228:C>T as the cis-regulatory variants; both SNPs were also evaluated in LNCaP and Caco-2 cells. By ChIP, we showed that the transcription factor Nrf2 binds to the region spanning rs34010522:G>T in all four cell lines. Our results provide a good example for how AI can be used to identify cis-regulatory variation and gain insights into the tissue specific regulation of gene expression.

STK39 polymorphisms and blood pressure: an association study in British Caucasians and assessment of cis-acting influences on gene expression

Background

Blood pressure (BP) has significant heritability, but the genes responsible remain largely unknown. Single nucleotide polymorphisms (SNPs) at the STK39 locus were recently associated with hypertension by genome-wide association in an Amish population; in vitro data from transient transfection experiments using reporter constructs suggested that altered STK39 expression might mediate the effect. However, other large studies have not implicated STK39 in hypertension. We determined whether reported SNPs influenced STK39 expression in vivo, or were associated with BP in a large British Caucasian cohort.

Methods

1372 members of 247 Caucasian families ascertained through a hypertensive proband were genotyped for reported risk variants in STK39 (rs6749447, rs3754777, rs35929607) using Sequenom technology. MERLIN software was used for family-based association testing. Cis-acting influences on expression were assessed in vivo using allelic expression ratios in cDNA from peripheral blood cells in 35 South African individuals heterozygous for a transcribed SNP in STK39 (rs1061471) and quantified by mass spectrometry (Sequenom).

Results

No significant association was seen between the SNPs tested and systolic or diastolic BP in clinic or ambulatory measurements (all p > 0.05). The tested SNPs were all associated with allelic expression differences in peripheral blood cells (p < 0.05), with the most significant association for the intronic SNP rs6749447 (P = 9.9 × 10^-4). In individuals who were heterozygous for this SNP, on average the G allele showed 13% overexpression compared to the T allele.

Conclusions

STK39 expression is modified by polymorphisms acting in cis and the typed SNPs are associated with allelic expression of this gene, but there is no evidence for an association with BP in a British Caucasian cohort.

Analysis of germline variants in CDH1, IGFBP3, MMP1, MMP3, STK15 and VEGF in familial and sporadic renal cell carcinoma

Background

The investigation of rare familial forms of kidney cancer has provided important insights into the biology of sporadic renal cell carcinoma (RCC). In particular, the identification of the von Hippel Lindau (VHL) familial cancer syndrome gene (VHL) provided the basis for the discovery that VHL is somatically inactivated in most sporadic clear cell RCC. Many cases of familial RCC do not have mutations in known RCC susceptibility genes and there is evidence that genetic modifiers may influence the risk of RCC in VHL disease patients. Hence we hypothesised that low-penetrance functional genetic variants in pathways related to the VHL protein (pVHL) function might (a) modify the phenotypic expression of VHL disease and/or (b) predispose to sporadic RCC.

Methodology/Principal Findings

We tested this hypothesis for functional polymorphisms in CDH1 (rs16260), IGFBP3 (rs2854744), MMP1 (rs1799750), MMP3 (rs679620), STK15 (rs2273535) and VEGF (rs1570360). We observed that variants of MMP1 and MMP3 were significant modifiers of RCC risk (and risks of retinal angioma and cerebellar haemangioblastoma) in VHL disease patients. In addition, higher frequencies of the MMP1 rs1799750 2G allele (p = 0.017, OR 1.49, 95%CI 1.06–2.08) and the MMP1/MMP3 rs1799750/rs679620 2G/G haplotype (OR 1.45, 95%CI 1.01–2.10) were detected in sporadic RCC patients than in controls (n = 295).

Conclusions/Significance

These findings (a) represent the first example of genetic modifiers of RCC risk in VHL disease, (b) replicate a previous report of an association between MMP1/MMP3 variants and sporadic RCC and (c) further implicate MMP1/MMP3-related pathways in the pathogenesis of familial and sporadic RCC.

Matrix metalloproteinase 1 (MMP1) is associated with early-onset lung cancer

Matrix metalloproteinases (MMP) play a key role in the breakdown of extracellular matrix and in inflammatory processes. MMP1 is the most highly expressed interstitial collagenase degrading fibrillar collagens. Overexpression of MMP1 has been shown in tumor tissues and has been suggested to be associated with tumor invasion and metastasis. Nine haplotype tagging and additional two intronic single nucleotide polymorphisms (SNP) of MMP1 were genotyped in a case control sample, consisting of 635 lung cancer cases with onset of disease below 51 years of age and 1,300 age- and sex-matched cancer-free controls. Two regions of linkage disequilibrium (LD) of MMP1 could be observed: a region of low LD comprising the 5' region including the promoter and a region of high LD starting from exon 1 to the end of the gene and including the 3' flanking region. Several SNPs were identified to be individually significantly associated with risk of early-onset lung cancer. The most significant effect was seen for rs1938901 (P = 0.0089), rs193008 (P = 0.0108), and rs996999 (P = 0.0459). For rs996999, significance vanished after correction for multiple testing. For each of these SNPs, the major allele was associated with an increase in risk with an odds ratio between 1.2 and 1.3 (95% confidence interval, 1.0-1.5). The haplotype analysis supported these findings, especially for subgroups with high smoking intensity. In summary, we identified MMP1 to be associated with an increased risk for lung cancer, which was modified by smoking.

Promoter polymorphisms and allelic imbalance in ABCB1 expression

OBJECTIVE

The ABCB1 (MDR1) gene, encoding the transporter P-glycoprotein, is known to act on a broad range of prescription medicines. For this reason a large number of studies have assessed the functional consequences of variation in this gene. Particular attention has focused on the ABCB1_3435C>T polymorphism, an exonic variant resulting in a synonymous change. This variant has been associated with mRNA, protein and serum levels, and with responses to a number of medicines. The results of association studies have, however, been variable and it is not currently clear whether this polymorphism is functional or is in linkage disequilibrium with functionally distinct alleles.

RESULTS

To identify functional variation in the ABCB1 gene we assessed allelic imbalance by pyrosequencing cDNA from 80 lymphoblastoid B cell lines from the Centre d'Etude du Polymorphisme Humain (CEPH) collection, including 74 individuals heterozygous for 3435C>T. We found that the degree of ABCB1 allelic imbalance differed among B-cell lines. In an effort to fine-map variants that influence the proportion of the two allelic mRNA species we genotyped representative common variations near the 3435C>T polymorphism by using a tagging single nucleotide polymorphism (SNP) approach. In one approach, we assessed in segregating families the impact of cis-acting variants on mRNA levels by using allelic imbalance as the phenotype in a regression analysis that distinguishes the coupling arrangements (phase) among alleles. In a second approach, we assessed allelic imbalance levels in lymphoblastoid B-cell lines from unrelated HapMap individuals, and performed an association using tagSNPs in a 5-Mb region surrounding the gene. Two potential cis-acting variants, a promoter rs28656907/rs28373093 dinucleotide polymorphism (P=0.007) and the rs10245483 SNP (P=0.0003) located 2 Mb upstream from the gene, were predictors of ABCB1 expression.

CONCLUSIONS

The study outlines a general experimental approach for fine mapping gene variants that influence mRNA expression by using cultured cell lines.

Differential haplotypic expression of the interleukin-18 gene

Interleukin 18 (IL-18) is suspected to play an important role in atherosclerosis and plaque vulnerability. We had previously shown that haplotypes combining two IL18 gene polymorphisms in complete linkage disequilibrium, C-105T (rs360717) in 5'-untranslated region (UTR) and A+183G (rs5744292) in 3'-UTR, were related to IL-18 circulating levels and cardiovascular outcome, the C(-105) G(+183) haplotype being associated with lower IL-18 levels and lower cardiovascular risk. This study was aimed at investigating the functional role of the two polymorphisms and their haplotypes on IL18 expression levels. Allelic imbalance experiments conducted in 24 and 20 subjects heterozygous for the C-105T and the A+183G polymorphisms did not detect any difference when subjects were considered as a whole (-0.009+/-0.044, P=0.85 and +0.114+/-0.082, P=0.18, respectively). However, when splitting individuals according to their haplo-genotype, the haplotype C(-105) G(+183) was associated with a lower expression level than C(-105) A(+183) (-0.287+/-0.076, P=0.005), but did not differ from T(-105) A(+183) (-0.138+/-0.083, P=0.13). The lower expression associated with C(-105) G(+183) was confirmed by real-time reverse transcription-PCR. Transfection of different haplotypic versions of the 3'-UTR did not show any difference in the expression of an upstream reporter gene. A 10-h study of the mRNA degradation kinetics by allelic imbalance with the A+183G polymorphism did not show any differential allelic degradation. In conclusion, the haplotype associated with lower IL-18 circulating concentrations and a lower cardiovascular risk was consistently associated with decreased IL18 expression levels, although the exact functional mechanisms remain to be elucidated.

Allelic imbalance in gene expression as a guide to cis-acting regulatory single nucleotide polymorphisms in cancer cells

Using the relative expression levels of two SNP alleles of a gene in the same sample is an effective approach for identifying cis-acting regulatory SNPs (rSNPs). In the current study, we established a process for systematic screening for cis-acting rSNPs using experimental detection of AI as an initial approach. We selected 160 expressed candidate genes that are involved in cancer and anticancer drug resistance for analysis of AI in a panel of cell lines that represent different types of cancers and have been well characterized for their response patterns against anticancer drugs. Of these genes, 60 contained heterozygous SNPs in their coding regions, and 41 of the genes displayed imbalanced expression of the two cSNP alleles. Genes that displayed AI were subjected to bioinformatics-assisted identification of rSNPs that alter the strength of transcription factor binding. rSNPs in 15 genes were subjected to electrophoretic mobility shift assay, and in eight of these genes (APC, BCL2, CCND2, MLH1, PARP1, SLIT2, YES1, XRCC1) we identified differential protein binding from a nuclear extract between the SNP alleles. The screening process allowed us to zoom in from 160 candidate genes to eight genes that may contain functional rSNPs in their promoter regions.

An expectation-maximization algorithm for the analysis of allelic expression imbalance

A significant proportion of the variation between individuals in gene expression levels is genetic, and it is likely that these differences correlate with phenotypic differences or with risk of disease. Cis-acting polymorphisms are important in determining interindividual differences in gene expression that lead to allelic expression imbalance, which is the unequal expression of homologous alleles in individuals heterozygous for such a polymorphism. This expression imbalance can be detected using a transcribed polymorphism, and, once it is established, the next step is to identify the polymorphisms that are responsible for or predictive of allelic expression levels. We present an expectation-maximization algorithm for such analyses, providing a formal statistical framework to test whether a candidate polymorphism is associated with allelic expression differences.

Bayesian mapping of genotype x expression interactions in quantitative and qualitative traits

A novel Bayesian gene mapping method, which can simultaneously utilize both molecular marker and gene expression data, is introduced. The approach enables a quantitative or qualitative phenotype to be expressed as a linear combination of the marker genotypes, gene expression levels, and possible genotype x gene expression interactions. The interaction data, given as marker-gene pairs, contains possible in cis and in trans effects obtained from earlier allelic expression studies, genetical genomics studies, biological hypotheses, or known pathways. The method is presented for an inbred line cross design and can be easily generalized to handle other types of populations and designs. The model selection is based on the use of effect-specific variance components combined with Jeffreys' non-informative prior--the method operates by adaptively shrinking marker, expression, and interaction effects toward zero so that non-negligible effects are expected to occur only at very few positions. The estimation of the model parameters and the handling of missing genotype or expression data is performed via Markov chain Monte Carlo sampling. The potential of the method including heritability estimation is presented using simulated examples and novel summary statistics. The method is also applied to a real yeast data set with known pathways.