Allelic variations in gene expression

Duke University Medical Center, Department of Pathology, Durham, North Carolina 27710, USA.
Current Opinion in Oncology (Impact Factor: 3.76). 02/2004; 16(1):39-43. DOI: 10.1097/00001622-200401000-00008
Source: PubMed

ABSTRACT 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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    • "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 · 2.08 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 · 3.80 Impact Factor
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    • "Studies that compare genetic differentiation and differ - entiation in expression could be instrumental when attempting to understand the relationship of genotypic with phenotypic differentiation in natural populations , to close the gap between the genotype - phenotype relation - ship , and to identify the targets of selection . We suspect that this will require a better future understanding of the genetic architecture of gene expression and the genotype - phenotype relationship ( Gibson , 2002 ; Wittkopp , 2007 ; Yan and Zhou , 2004 ) . "
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    ABSTRACT: Owing to the relevance to evolutionary theories of genotypic and phenotypic evolution, the correspondence of differentiation among natural populations in complex phenotypic traits and genetic markers has been studied extensively, and generally found to be poor. In contrast, the correspondence of differentiation among natural populations in gene expression, now often considered a genomic era proxy for the phenotype, and genetic markers, remains largely unexplored. Here, an analysis of expression and nucleotide sequence polymorphism of 106 genes in Drosophila melanogaster strains of the Cosmopolitan (M) and Zimbabwe, Africa (Z) mating races showed that differentiation of gene expression and of coding sequences, measured as QST and GST, respectively, were uncorrelated and, generally, QST > GST. However, an exploratory analysis showed that GST of the 5 prime sequences of genes was correlated with QST calculated from expression data, while GST of the coding sequences remained uncorrelated with QST. This scenario is consistent with the population differentiation at cis-regulatory regions that is decoupled from differentiation of the coding regions. However, despite evidence for selection on global levels of gene expression (deduced from QST > GST), 5 prime sequence polymorphisms generally were compatible with selective neutrality, suggesting differentiation in cis-regulated gene expression for these genes has been promoted by drift or selection too weak or too long ago to be detected, or higher organizational levels underlying the genetic architecture of expression are targets of selection. In all, this raises the question how selection on the expression changes (i.e. the phenotype) can be so obvious yet elusive at the level of the nucleotide sequence. Our contrasts between genetic differentiation of populations in expression and sequences revealed that even when genotype and phenotype can be connected the sources of variation that are the target of selection remain to be identified.
    Genes & Genetic Systems 06/2008; 83(3):265-73. DOI:10.1266/ggs.83.265 · 0.87 Impact Factor
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