Allelic variations in gene expression

Duke University Medical Center, Department of Pathology, Durham, North Carolina 27710, USA.
Current Opinion in Oncology (Impact Factor: 4.47). 02/2004; 16(1):39-43. DOI: 10.1097/00001622-200401000-00008
Source: PubMed


Genetic variants determine phenotypic variability. Many genetic studies suggest that protein structural variations predispose the population to more than 1000 different hereditary diseases. Unfortunately, despite the study of genetic polymorphisms for many decades, the milder phenotypic variations believed to account for most human physical and behavioral differences and underlying the most common human genetic diseases (including cancers) cannot be accounted for easily by these variations in the protein coding sequences. Thus, it has been hypothesized that the study of natural differential expression presenting within and among populations may enhance understanding of human phenotypic variation.
During the last year, reports identifying variations in gene expression in different organisms and finding subtle changes of gene expression associated with common genetic disease have pointed to variations in gene expression as playing a central role in molecular evolution and human disease. Advances in the functional analysis of gene regulatory networks-in particular, new methods for distinguishing cis-acting components from trans-acting factors-have provided the impetus for these discoveries.
This review represents current knowledge about allelic variation in gene expression and its increasingly important role in understanding the genotype-phenotype relation. Characterization of these allelic variations may open largely uncharted territory in genomics for biomedical researchers and may eventually lead to the discovery of the causative genes of common hereditary diseases and their mechanism of action.

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    • "Recent genome-wide association studies failed to identify variants that could be clear indicators of the genetic risk of cancer [1] [2] [3]. An alternative approach for identifying genes with low penetrance associated with cancer is the analysis of allelic imbalance in heterozygous loci that are likely to be differentially expressed in tissues carrying alternative alleles [4] [5] [6]. In sporadic tumors, the phenomenon of loss of heterozygosity (LOH) can be observed as the result of allele deletions. "
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    ABSTRACT: The study aimed to reveal cancer related mutations in DNA repair and cell cycle genes associated with chronic occupational exposure to gamma-radiation in personnel of the Siberian Group of Chemical Enterprises (SGCE). Mutations were analyzed by comparing genotypes of malignant tumors and matched normal tissues of 255 cancer patients including 98 exposed to external gamma-radiation (mean dose 128.1 ± 150.5 mSv). Also a genetic association analysis was carried out in a sample of 149 cancer patients and 908 healthy controls occupationally exposed to gamma-radiation (153.2 ± 204.6 mSv and 150.5 ± 211.2 mSv, respectively). Eight SNPs of genes of DNA excision repair were genotyped (rs13181, rs1052133, rs1042522, rs2305427, rs4244285, rs1045642, rs1805419 and rs1801133). The mutation profiles in heterozygous loci for selected SNP were different between sporadic tumors and tumors in patients exposed to radiation. In sporadic tumors, heterozygous genotype Arg/Pro of the rs1042522 SNP mutated into Arg/0 in 15 cases (9.6%) and 0/Pro in 14 cases (8.9%). The genotype Lys/Gln of the rs13181 SNP mutated into Lys/0 and 0/Gln in 9 and 4 cases, respectively. In tumors of patients exposed to low-level radiation, the rs1042522 Arg/0 mutated genotype was found in 12 cases (12.1%), while in 2 cases (2%) 0/Pro mutation was observed. Finally, the rs13181 0/Gln mutated genotype was observed in 15 cases (16,5%) . Thus, our study showed the difference in patterns of allelic imbalance in tumors appeared under low-level radiation exposure and spontaneous tumors for selected SNPs. This suggests different mechanisms of inactivation of heterozygous genotypes in sporadic and radiation-induced tumors.
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    • "Differential allelic expression (DAE, or allelic imbalance, AI) has been shown to be a robust and accurate way to identify cis-regulatory elements (Pastinen and Hudson, 2004; Stamatoyannopoulos, 2004; Yan and Zhou, 2004; Bray and O'Donovan, 2006). Recently, by studying DAE at the c.253G>T (relative to translation start, rs1902023) site, two tissuespecific cis-regulatory elements for UGT2B15 were identified in the promoter region (Sun et al., 2010). "
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    ABSTRACT: Differential allelic expression (DAE) is a powerful tool to identify cis-regulatory elements for gene expression. The UDP-glucuronosyltransferase 2 family, polypeptide B15 (UGT2B15), is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In the present study, we measured the relative expression of two alleles at SNP c.1568C>A (rs4148269) in this gene, which causes an amino acid substitution (T523K). An excess of the C over the A allele was consistently observed in both liver (P=0.0021) and breast (P=0.012) samples, suggesting that SNP(s) in strong linkage disequilibrium (LD) with c.1568C>A can regulate UGT2B15 expression in both tissues. By resequencing, one such SNP, c.1761T>C (rs3100) in 3' untranslated region (UTR), was identified. Reporter gene assays showed that the 1761T allele results in a significantly higher gene expression level than the 1761C allele in HepG2, MCF-7, LNCaP, and Caco-2 cell lines (all P<0.001), thus indicating that this variation can regulate UGT2B15 gene expression in liver, breast, colon, and prostate tissues. Considering its location, we postulated that this SNP is within an unknown microRNA binding site and can influence microRNA targeting. Considering the importance of UGT2B15 in metabolism, we proposed that this SNP might contribute to multiple cancer risk and variability in drug response.
    Gene 07/2011; 481(1):24-8. DOI:10.1016/j.gene.2011.04.001 · 2.14 Impact Factor
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    • "Therefore, the analysis of DNA sequence variations, related to variations in gene expression, results in a better understanding of transcriptional regulation. Variants that affect gene expression (expression quantitative trait loci, eQTL) may have a substantial impact on quantitative traits, whereas qualitative traits, including hereditary disease, may more often depend on structural variation (Farrall, 2004; Yan and Zhou, 2004). A literature survey revealed that of 107 genes with experimentally verified functional cis regulatory polymorphisms 82% had proven effects on phenotypes (Rockman and Wray, 2002). "
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    ABSTRACT: Genetic analysis of transcriptional profiling is a promising approach for identifying biological pathways and dissecting the genetics of complex traits. Here, we report on expression quantitative trait loci (eQTL) that were estimated from the quantitative real-time RT-PCR data of 276 F(2) animals and compared with eQTL identified using 74 microarrays. In total, 13 genes were selected that showed trait-dependent expression in microarray experiments and exhibited 21 eQTL. Real-time RT-PCR and microarray data revealed seven cis eQTL in total, of which one was only detected by real-time RT-PCR, one was only detected by microarray analysis, three were consistently found in overlapping intervals and two were in neighbouring intervals on the same chromosome; whereas no trans eQTL was confirmed. We demonstrate that cis regulation is a stable characteristic of individual transcripts. Consequently, a global microarray eQTL analysis of a limited number of samples can be used for exploring functional and regulatory gene networks and scanning for cis eQTL, whereas the subsequent analysis of a subset of likely cis-regulated genes by real-time RT-PCR in a larger number of samples is relevant to narrow down a QTL region by targeting these positional candidate genes. In fact, when modelling SNPs of six genes as fixed effects in the eQTL analysis, eQTL peaks were shifted downwards, experimentally confirming the impact of the respective polymorphic genes, although these SNPs were not located in the regulatory sequence and these shifts occur as a result of linkage disequilibrium in the F(2) population.
    Heredity 02/2010; 105(3):309-17. DOI:10.1038/hdy.2010.5 · 3.81 Impact Factor
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