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      Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver

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          Abstract

          Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory elements of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the effects of genetic variation on histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 74 GWAS loci that have been associated with at least one complex phenotype. Our results reveal a repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.

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          Most cited references34

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          Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease

          Genetic association studies have identified 215 risk loci for inflammatory bowel disease 1–8, which have revealed fundamental aspects of its molecular biology. We performed a genome-wide association study of 25,305 individuals, and meta-analyzed with published summary statistics, yielding a total sample size of 59,957 subjects. We identified 25 new loci, three of which contain integrin genes that encode proteins in pathways identified as important therapeutic targets in inflammatory bowel disease. The associated variants are correlated with expression changes in response to immune stimulus at two of these genes (ITGA4, ITGB8) and at previously implicated loci (ITGAL, ICAM1). In all four cases, the expression increasing allele also increases disease risk. We also identified likely causal missense variants in the primary immune deficiency gene PLCG2 and a negative regulator of inflammation, SLAMF8. Our results demonstrate that new common variant associations continue to identify genes relevant to therapeutic target identification and prioritization.
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            An atlas of combinatorial transcriptional regulation in mouse and man.

            Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution. (c) 2010 Elsevier Inc. All rights reserved.
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              DNaseI sensitivity QTLs are a major determinant of human expression variation

              The mapping of expression quantitative trait loci (eQTLs) has emerged as an important tool for linking genetic variation to changes in gene regulation 1-5 . However, it remains difficult to identify the causal variants underlying eQTLs and little is known about the regulatory mechanisms by which they act. To address this gap, we used DNaseI sequencing to measure chromatin accessibility in 70 Yoruba lymphoblastoid cell lines (LCLs), for which genome-wide genotypes and estimates of gene expression levels are also available 6-8 . We obtained a total of 2.7 billion uniquely mapped DNase-seq reads, which allowed us to produce genome-wide maps of chromatin accessibility for each individual. We identified 9,595 locations at which DNase-seq read depth correlates significantly with genotype at a nearby SNP or indel (FDR=10%). We call such variants “DNaseI sensitivity Quantitative Trait Loci” (dsQTLs). We found that dsQTLs are strongly enriched within inferred transcription factor binding sites and are frequently associated with allele-specific changes in transcription factor binding. A substantial fraction (16%) of dsQTLs are also associated with variation in the expression levels of nearby genes, (namely, these loci are also classified as eQTLs). Conversely, we estimate that as many as 55% of eQTL SNPs are also dsQTLs. Our observations indicate that dsQTLs are highly abundant in the human genome, and are likely to be important contributors to phenotypic variation.
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                Author and article information

                Contributors
                Journal
                Am J Hum Genet
                Am. J. Hum. Genet
                American Journal of Human Genetics
                Elsevier
                0002-9297
                1537-6605
                03 July 2019
                13 June 2019
                : 105
                : 1
                : 89-107
                Affiliations
                [1 ]Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [2 ]Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [3 ]Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [4 ]Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [5 ]Department of Biostatistics, Epidemiology, & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [6 ]Division of Transplant Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [7 ]Division of Cardiology, Columbia University, New York, NY 10032, USA
                [8 ]Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
                [9 ]Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [10 ]Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                Author notes
                []Corresponding author minal@ 123456mail.med.upenn.edu
                [∗∗ ]Corresponding author chrbro@ 123456pennmedicine.upenn.edu
                Article
                S0002-9297(19)30197-1
                10.1016/j.ajhg.2019.05.010
                6612522
                31204013
                1c509aec-aab2-4927-b124-58bf56cddc2a
                © 2019 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 5 October 2018
                : 13 May 2019
                Categories
                Article

                Genetics
                liver,chip-seq,rna-seq,capture-c,gene regulation,dna-looping,eqtl,hqtl,fine mapping,gwas
                Genetics
                liver, chip-seq, rna-seq, capture-c, gene regulation, dna-looping, eqtl, hqtl, fine mapping, gwas

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