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      Differential Allelic Expression in the Human Genome: A Robust Approach To Identify Genetic and Epigenetic Cis-Acting Mechanisms Regulating Gene Expression

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          Abstract

          The recent development of whole genome association studies has lead to the robust identification of several loci involved in different common human diseases. Interestingly, some of the strongest signals of association observed in these studies arise from non-coding regions located in very large introns or far away from any annotated genes, raising the possibility that these regions are involved in the etiology of the disease through some unidentified regulatory mechanisms. These findings highlight the importance of better understanding the mechanisms leading to inter-individual differences in gene expression in humans. Most of the existing approaches developed to identify common regulatory polymorphisms are based on linkage/association mapping of gene expression to genotypes. However, these methods have some limitations, notably their cost and the requirement of extensive genotyping information from all the individuals studied which limits their applications to a specific cohort or tissue. Here we describe a robust and high-throughput method to directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 60∶40) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms.

          Author Summary

          We describe a new methodology to identify individual differences in the expression of the two copies of one gene. This is achieved by comparing the mRNA level of the two alleles using a heterozygous polymorphism in the transcript as marker. We show that this approach allows an exhaustive survey of cis-acting regulation in the genome; we can identify allelic expression differences due to epigenetic mechanisms of gene regulation (e.g. imprinting or X-inactivation) as well as differences due to the presence of polymorphisms in regulatory elements. The direct comparison of the expression of both alleles nullifies possible trans-acting regulatory effects (that influence equally both alleles) and thus complements the findings from gene expression association studies. Our approach can be easily applied to any cohort of interest for a wide range of studies. It notably allows following up association signals and testing whether a gene sitting on a particular haplotype is over- or under-expressed, or can be used for screening cancer tissues for aberrant gene expression due to newly arisen mutations or alteration of the methylation patterns.

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          Most cited references45

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          Gene action in the X-chromosome of the mouse (Mus musculus L.).

          MARY LYON (1961)
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            Hypomethylation distinguishes genes of some human cancers from their normal counterparts.

            It has been suggested that cancer represents an alteration in DNA, heritable by progeny cells, that leads to abnormally regulated expression of normal cellular genes; DNA alterations such as mutations, rearrangements and changes in methylation have been proposed to have such a role. Because of increasing evidence that DNA methylation is important in gene expression (for review see refs 7, 9-11), several investigators have studied DNA methylation in animal tumours, transformed cells and leukaemia cells in culture. The results of these studies have varied; depending on the techniques and systems used, an increase, decrease, or no change in the degree of methylation has been reported. To our knowledge, however, primary human tumour tissues have not been used in such studies. We have now examined DNA methylation in human cancer with three considerations in mind: (1) the methylation pattern of specific genes, rather than total levels of methylation, was determined; (2) human cancers and adjacent analogous normal tissues, unconditioned by culture media, were analysed; and (3) the cancers were taken from patients who had received neither radiation nor chemotherapy. In four of five patients studied, representing two histological types of cancer, substantial hypomethylation was found in genes of cancer cells compared with their normal counterparts. This hypomethylation was progressive in a metastasis from one of the patients.
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              Genetic dissection of transcriptional regulation in budding yeast.

              To begin to understand the genetic architecture of natural variation in gene expression, we carried out genetic linkage analysis of genomewide expression patterns in a cross between a laboratory strain and a wild strain of Saccharomyces cerevisiae. Over 1500 genes were differentially expressed between the parent strains. Expression levels of 570 genes were linked to one or more different loci, with most expression levels showing complex inheritance patterns. The loci detected by linkage fell largely into two categories: cis-acting modulators of single genes and trans-acting modulators of many genes. We found eight such trans-acting loci, each affecting the expression of a group of 7 to 94 genes of related function.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plge
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                February 2008
                February 2008
                29 February 2008
                : 4
                : 2
                : e1000006
                Affiliations
                [1 ]McGill University, Montreal, Quebec, Canada
                [2 ]Genome Quebec Innovation Centre, Montreal, Quebec, Canada
                [3 ]Illumina Inc., San Diego, California, United States of America
                The Wellcome Trust Sanger Institute, United Kingdom
                Author notes
                [¤a]

                Current address: Genomic Medicine Institute, Cleveland Clinic Foundation, Cleveland, Ohio, United States of America

                [¤b]

                Current address: Merck & Co. Inc., Seattle, Washington, United States of America

                [¤c]

                Current address: Ontario Institute for Cancer Research, Toronto, Ontario, Canada

                Conceived and designed the experiments: DS JF TH. Performed the experiments: SG DS. Analyzed the data: DS SG BG RS TH. Contributed reagents/materials/analysis tools: DS MB EC DB TD JF TH. Wrote the paper: DS RS EH JF TH.

                Article
                07-PLGE-RA-0017R3
                10.1371/journal.pgen.1000006
                2265535
                18454203
                ab3f5cad-7708-4fba-acfc-e3c593077c9e
                Serre et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 10 January 2007
                : 15 January 2008
                Page count
                Pages: 16
                Categories
                Research Article
                Genetics and Genomics
                Genetics and Genomics/Cancer Genetics
                Genetics and Genomics/Complex Traits
                Genetics and Genomics/Epigenetics
                Genetics and Genomics/Functional Genomics
                Genetics and Genomics/Gene Expression
                Genetics and Genomics/Genetics of Disease

                Genetics
                Genetics

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