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Keywords {🔍}

pubmed, article, model, expression, google, scholar, data, gene, cas, snps, regulatory, eqtns, snp, central, eqtn, binding, figure, genome, genes, analysis, eqtls, human, nature, annotations, regions, annotation, elements, hierarchical, promoter, additional, file, core, enrichment, prior, sites, site, variation, chipseq, hapmap, transcription, eqtl, factor, causal, tss, enriched, genet, dnasei, nfκb, number, cell,

Topics {✒️}

terminal b-cell differentiation-induced rel/nf-kappab transcription factors cross-linked protein-dna fragment article number r7 nf-κb chip-seq regions article download pdf detecting cis-regulatory modules nf-κb read-depth expression-qtls yields insight increased t-cell apoptosis chip-seq identifies fragments modifying protein-dna interactions tf chip-seq peaks inferring genotype-trait association high-resolution genome-wide literature-derived regulatory elements mark regulatory elements full size image tf chip-seq data allele-specific chromatin signatures induce large-scale dependencies human genome-wide map rna-seq data set provide base-pair resolution nf-κb tf groups downstream promoter element genome-wide association signals individual dnase-seq footprints cytosolic pattern-recognition receptors generated dnase-seq data genome-wide association studies dnase-seq footprints tested evolutionarily conserved elements roger pique-regi open access database evolutionarily conserved sites privacy choices/manage cookies imputation-based association mapping xie xh schadt ee shows independent data core promoter versus core promoter elements cheung vg tfiib recognition element protein-coding exons prior nf-κb peaks confidence intervals spanning cis-regulatory mutations high-posterior eqtns detected

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         headline:Dissecting the regulatory architecture of gene expression QTLs
         description:Expression quantitative trait loci (eQTLs) are likely to play an important role in the genetics of complex traits; however, their functional basis remains poorly understood. Using the HapMap lymphoblastoid cell lines, we combine 1000 Genomes genotypes and an extensive catalogue of human functional elements to investigate the biological mechanisms that eQTLs perturb. We use a Bayesian hierarchical model to estimate the enrichment of eQTLs in a wide variety of regulatory annotations. We find that approximately 40% of eQTLs occur in open chromatin, and that they are particularly enriched in transcription factor binding sites, suggesting that many directly impact protein-DNA interactions. Analysis of core promoter regions shows that eQTLs also frequently disrupt some known core promoter motifs but, surprisingly, are not enriched in other well-known motifs such as the TATA box. We also show that information from regulatory annotations alone, when weighted by the hierarchical model, can provide a meaningful ranking of the SNPs that are most likely to drive gene expression variation. Our study demonstrates how regulatory annotation and the association signal derived from eQTL-mapping can be combined into a single framework. We used this approach to further our understanding of the biology that drives human gene expression variation, and of the putatively causal SNPs that underlie it.
         datePublished:2012-01-31T00:00:00Z
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            Core Promoter
            Histone Mark
            Regulatory Annotation
            Downstream Promoter Element
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Bioinformatics
            Evolutionary Biology
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      headline:Dissecting the regulatory architecture of gene expression QTLs
      description:Expression quantitative trait loci (eQTLs) are likely to play an important role in the genetics of complex traits; however, their functional basis remains poorly understood. Using the HapMap lymphoblastoid cell lines, we combine 1000 Genomes genotypes and an extensive catalogue of human functional elements to investigate the biological mechanisms that eQTLs perturb. We use a Bayesian hierarchical model to estimate the enrichment of eQTLs in a wide variety of regulatory annotations. We find that approximately 40% of eQTLs occur in open chromatin, and that they are particularly enriched in transcription factor binding sites, suggesting that many directly impact protein-DNA interactions. Analysis of core promoter regions shows that eQTLs also frequently disrupt some known core promoter motifs but, surprisingly, are not enriched in other well-known motifs such as the TATA box. We also show that information from regulatory annotations alone, when weighted by the hierarchical model, can provide a meaningful ranking of the SNPs that are most likely to drive gene expression variation. Our study demonstrates how regulatory annotation and the association signal derived from eQTL-mapping can be combined into a single framework. We used this approach to further our understanding of the biology that drives human gene expression variation, and of the putatively causal SNPs that underlie it.
      datePublished:2012-01-31T00:00:00Z
      dateModified:2012-01-31T00:00:00Z
      pageStart:1
      pageEnd:15
      license:http://creativecommons.org/licenses/by/2.0/
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         Hierarchical Model
         Core Promoter
         Histone Mark
         Regulatory Annotation
         Downstream Promoter Element
         Animal Genetics and Genomics
         Human Genetics
         Plant Genetics and Genomics
         Microbial Genetics and Genomics
         Bioinformatics
         Evolutionary Biology
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      name:Department of Human Genetics, University of Chicago, Chicago, USA
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