Article
Localization of a long-range cis-regulatory element of IL13 by allelic transcript ratio mapping.
Department of Paediatrics, Oxford University, Oxford OX3 7BN, United Kingdom.
Genome Research (impact factor:
13.61).
02/2007;
17(1):82-7.
DOI:10.1101/gr.5663007
pp.82-7
Source: PubMed
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Citations (0)
- Cited In (3)
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Article: Validating discovered Cis-acting regulatory genetic variants: application of an allele specific expression approach to HapMap populations.
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ABSTRACT: 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. 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. 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.PLoS ONE 02/2008; 3(12):e4105. · 4.09 Impact Factor -
Article: TLR9 polymorphisms in African populations: no association with severe malaria, but evidence of cis-variants acting on gene expression.
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ABSTRACT: During malaria infection the Toll-like receptor 9 (TLR9) is activated through induction with plasmodium DNA or another malaria motif not yet identified. Although TLR9 activation by malaria parasites is well reported, the implication to the susceptibility to severe malaria is not clear. The aim of this study was to assess the contribution of genetic variation at TLR9 to severe malaria. This study explores the contribution of TLR9 genetic variants to severe malaria using two approaches. First, an association study of four common single nucleotide polymorphisms was performed on both family- and population-based studies from Malawian and Gambian populations (n>6000 individual). Subsequently, it was assessed whether TLR9 expression is affected by cis-acting variants and if these variants could be mapped. For this work, an allele specific expression (ASE) assay on a panel of HapMap cell lines was carried out. No convincing association was found with polymorphisms in TLR9 for malaria severity, in either Gambian or Malawian populations, using both case-control and family based study designs. Using an allele specific expression assay it was observed that TLR9 expression is affected by cis-acting variants, these results were replicated in a second experiment using biological replicates. By using the largest cohorts analysed to date, as well as a standardized phenotype definition and study design, no association of TLR9 genetic variants with severe malaria was found. This analysis considered all common variants in the region, but it is remains possible that there are rare variants with association signals. This report also shows that TLR9 expression is potentially modulated through cis-regulatory variants, which may lead to differential inflammatory responses to infection between individuals.Malaria Journal 02/2009; 8:44. · 3.19 Impact Factor -
Article: Genotype-based test in mapping cis-regulatory variants from allele-specific expression data.
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ABSTRACT: Identifying and understanding the impact of gene regulatory variation is of considerable importance in evolutionary and medical genetics; such variants are thought to be responsible for human-specific adaptation and to have an important role in genetic disease. Regulatory variation in cis is readily detected in individuals showing uneven expression of a transcript from its two allelic copies, an observation referred to as allelic imbalance (AI). Identifying individuals exhibiting AI allows mapping of regulatory DNA regions and the potential to identify the underlying causal genetic variant(s). However, existing mapping methods require knowledge of the haplotypes, which make them sensitive to phasing errors. In this study, we introduce a genotype-based mapping test that does not require haplotype-phase inference to locate regulatory regions. The test relies on partitioning genotypes of individuals exhibiting AI and those not expressing AI in a 2×3 contingency table. The performance of this test to detect linkage disequilibrium (LD) between a potential regulatory site and a SNP located in this region was examined by analyzing the simulated and the empirical AI datasets. In simulation experiments, the genotype-based test outperforms the haplotype-based tests with the increasing distance separating the regulatory region from its regulated transcript. The genotype-based test performed equally well with the experimental AI datasets, either from genome-wide cDNA hybridization arrays or from RNA sequencing. By avoiding the need of haplotype inference, the genotype-based test will suit AI analyses in population samples of unknown haplotype structure and will additionally facilitate the identification of cis-regulatory variants that are located far away from the regulated transcript.PLoS ONE 01/2012; 7(6):e38667. · 4.09 Impact Factor
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Keywords
allelic differences
cis-acting elements
cis-acting regulatory elements
different amounts
dissecting
gene regulation
genes
genetic variation
genotyping data
HapMap project
human 5q31 chromosomal region
plausible explanation
position 250 kb upstream
significant cis-regulatory element
trans-acting genetic factors
transcript
transcription
two alleles