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Search Results: 1 - 10 of 118086 matches for " Emmanouil T Dermitzakis "
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The genetics of regulatory variation in the human genome
Barbara E Stranger, Emmanouil T Dermitzakis
Human Genomics , 2005, DOI: 10.1186/1479-7364-2-2-126
From DNA to RNA to disease and back: The 'central dogma' of regulatory disease variation
Barbara E Stranger, Emmanouil T Dermitzakis
Human Genomics , 2006, DOI: 10.1186/1479-7364-2-6-383
Rare and Common Regulatory Variation in Population-Scale Sequenced Human Genomes
Stephen B. Montgomery ,Tuuli Lappalainen,Maria Gutierrez-Arcelus,Emmanouil T. Dermitzakis
PLOS Genetics , 2011, DOI: 10.1371/journal.pgen.1002144
Abstract: Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.
Large-Scale Population Study of Human Cell Lines Indicates that Dosage Compensation Is Virtually Complete
Colette M Johnston,Frances L Lovell,Daniel A Leongamornlert,Barbara E Stranger,Emmanouil T Dermitzakis,Mark T Ross
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.0040009
Abstract: X chromosome inactivation in female mammals results in dosage compensation of X-linked gene products between the sexes. In humans there is evidence that a substantial proportion of genes escape from silencing. We have carried out a large-scale analysis of gene expression in lymphoblastoid cell lines from four human populations to determine the extent to which escape from X chromosome inactivation disrupts dosage compensation. We conclude that dosage compensation is virtually complete. Overall expression from the X chromosome is only slightly higher in females and can largely be accounted for by elevated female expression of approximately 5% of X-linked genes. We suggest that the potential contribution of escape from X chromosome inactivation to phenotypic differences between the sexes is more limited than previously believed.
Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations
Alexandra C. Nica,Stephen B. Montgomery,Antigone S. Dimas,Barbara E. Stranger,Claude Beazley,Inês Barroso,Emmanouil T. Dermitzakis
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1000895
Abstract: The recent success of genome-wide association studies (GWAS) is now followed by the challenge to determine how the reported susceptibility variants mediate complex traits and diseases. Expression quantitative trait loci (eQTLs) have been implicated in disease associations through overlaps between eQTLs and GWAS signals. However, the abundance of eQTLs and the strong correlation structure (LD) in the genome make it likely that some of these overlaps are coincidental and not driven by the same functional variants. In the present study, we propose an empirical methodology, which we call Regulatory Trait Concordance (RTC) that accounts for local LD structure and integrates eQTLs and GWAS results in order to reveal the subset of association signals that are due to cis eQTLs. We simulate genomic regions of various LD patterns with both a single or two causal variants and show that our score outperforms SNP correlation metrics, be they statistical (r2) or historical (D'). Following the observation of a significant abundance of regulatory signals among currently published GWAS loci, we apply our method with the goal to prioritize relevant genes for each of the respective complex traits. We detect several potential disease-causing regulatory effects, with a strong enrichment for immunity-related conditions, consistent with the nature of the cell line tested (LCLs). Furthermore, we present an extension of the method in trans, where interrogating the whole genome for downstream effects of the disease variant can be informative regarding its unknown primary biological effect. We conclude that integrating cellular phenotype associations with organismal complex traits will facilitate the biological interpretation of the genetic effects on these traits.
High-Resolution Mapping of Expression-QTLs Yields Insight into Human Gene Regulation
Jean-Baptiste Veyrieras ,Sridhar Kudaravalli,Su Yeon Kim,Emmanouil T. Dermitzakis,Yoav Gilad ,Matthew Stephens ,Jonathan K. Pritchard
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000214
Abstract: Recent studies of the HapMap lymphoblastoid cell lines have identified large numbers of quantitative trait loci for gene expression (eQTLs). Reanalyzing these data using a novel Bayesian hierarchical model, we were able to create a surprisingly high-resolution map of the typical locations of sites that affect mRNA levels in cis. Strikingly, we found a strong enrichment of eQTLs in the 250 bp just upstream of the transcription end site (TES), in addition to an enrichment around the transcription start site (TSS). Most eQTLs lie either within genes or close to genes; for example, we estimate that only 5% of eQTLs lie more than 20 kb upstream of the TSS. After controlling for position effects, SNPs in exons are ~2-fold more likely than SNPs in introns to be eQTLs. Our results suggest an important role for mRNA stability in determining steady-state mRNA levels, and highlight the potential of eQTL mapping as a high-resolution tool for studying the determinants of gene regulation.
Data analysis issues for allele-specific expression using Illumina's GoldenGate assay
Matthew E Ritchie, Matthew S Forrest, Antigone S Dimas, Caroline Daelemans, Emmanouil T Dermitzakis, Panagiotis Deloukas, Simon Tavaré
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-280
Abstract: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available.Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.Preferential expression of one of the two alleles of a gene has been widely studied in the context of development, where key mechanisms such as genomic imprinting and X-inactivation lead to extreme allelic imbalances [1]. Allele-specific expression has been linked to the susceptibility of many human diseases [2-4].Various experimental techniques exist for measuring ASE [5], including microarray-based approaches that have been used in a number of studies to screen for ASE in a high-throughput manner [6-11]. With microarray
Genotype-Based Test in Mapping Cis-Regulatory Variants from Allele-Specific Expression Data
Jean Francois Lefebvre, Emilio Vello, Bing Ge, Stephen B. Montgomery, Emmanouil T. Dermitzakis, Tomi Pastinen, Damian Labuda
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0038667
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 [1] 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.
Modifier Effects between Regulatory and Protein-Coding Variation
Antigone S. Dimas,Barbara E. Stranger,Claude Beazley,Robert D. Finn,Catherine E. Ingle,Matthew S. Forrest,Matthew E. Ritchie,Panos Deloukas,Simon Tavaré,Emmanouil T. Dermitzakis
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000244
Abstract: Genome-wide associations have shown a lot of promise in dissecting the genetics of complex traits in humans with single variants, yet a large fraction of the genetic effects is still unaccounted for. Analyzing genetic interactions between variants (epistasis) is one of the potential ways forward. We investigated the abundance and functional impact of a specific type of epistasis, namely the interaction between regulatory and protein-coding variants. Using genotype and gene expression data from the 210 unrelated individuals of the original four HapMap populations, we have explored the combined effects of regulatory and protein-coding single nucleotide polymorphisms (SNPs). We predict that about 18% (1,502 out of 8,233 nsSNPs) of protein-coding variants are differentially expressed among individuals and demonstrate that regulatory variants can modify the functional effect of a coding variant in cis. Furthermore, we show that such interactions in cis can affect the expression of downstream targets of the gene containing the protein-coding SNP. In this way, a cis interaction between regulatory and protein-coding variants has a trans impact on gene expression. Given the abundance of both types of variants in human populations, we propose that joint consideration of regulatory and protein-coding variants may reveal additional genetic effects underlying complex traits and disease and may shed light on causes of differential penetrance of known disease variants.
Evolutionary Comparison Provides Evidence for Pathogenicity of RMRP Mutations
Luisa Bonafé ,Emmanouil T Dermitzakis,Sheila Unger,Cheryl R Greenberg,Belinda A Campos-Xavier,Andreas Zankl,Catherine Ucla,Stylianos E Antonarakis,Andrea Superti-Furga,Alexandre Reymond
PLOS Genetics , 2005, DOI: 10.1371/journal.pgen.0010047
Abstract: Cartilage-hair hypoplasia (CHH) is a pleiotropic disease caused by recessive mutations in the RMRP gene that result in a wide spectrum of manifestations including short stature, sparse hair, metaphyseal dysplasia, anemia, immune deficiency, and increased incidence of cancer. Molecular diagnosis of CHH has implications for management, prognosis, follow-up, and genetic counseling of affected patients and their families. We report 20 novel mutations in 36 patients with CHH and describe the associated phenotypic spectrum. Given the high mutational heterogeneity (62 mutations reported to date), the high frequency of variations in the region (eight single nucleotide polymorphisms in and around RMRP), and the fact that RMRP is not translated into protein, prediction of mutation pathogenicity is difficult. We addressed this issue by a comparative genomic approach and aligned the genomic sequences of RMRP gene in the entire class of mammals. We found that putative pathogenic mutations are located in highly conserved nucleotides, whereas polymorphisms are located in non-conserved positions. We conclude that the abundance of variations in this small gene is remarkable and at odds with its high conservation through species; it is unclear whether these variations are caused by a high local mutation rate, a failure of repair mechanisms, or a relaxed selective pressure. The marked diversity of mutations in RMRP and the low homozygosity rate in our patient population indicate that CHH is more common than previously estimated, but may go unrecognized because of its variable clinical presentation. Thus, RMRP molecular testing may be indicated in individuals with isolated metaphyseal dysplasia, anemia, or immune dysregulation.
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