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      • Record: found
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      Genetic effects on gene expression across human tissues

      GTEx consortium

      Nature

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

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          Most cited references 80

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          BEDTools: a flexible suite of utilities for comparing genomic features

          Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            Statistical significance for genomewide studies.

            With the increase in genomewide experiments and the sequencing of multiple genomes, the analysis of large data sets has become commonplace in biology. It is often the case that thousands of features in a genomewide data set are tested against some null hypothesis, where a number of features are expected to be significant. Here we propose an approach to measuring statistical significance in these genomewide studies based on the concept of the false discovery rate. This approach offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted. In doing so, a measure of statistical significance called the q value is associated with each tested feature. The q value is similar to the well known p value, except it is a measure of significance in terms of the false discovery rate rather than the false positive rate. Our approach avoids a flood of false positive results, while offering a more liberal criterion than what has been used in genome scans for linkage.
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              An integrated map of genetic variation from 1,092 human genomes

              Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
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                Author and article information

                Author notes
                Correspondence and requests for materials should be addressed to A.B. ( ajbattle@ 123456cs.jhu.edu ), C.D.Br. ( chrbro@ 123456pennmedicine.upenn.edu ), B.E.E. ( bee@ 123456princeton.edu ) & S.B.M. ( smontgom@ 123456stanford.edu )

                Lead analysts: François Aguet 1 *, Andrew A. Brown 2, 3, 4 *, Stephane E. Castel 5, 6 *, Joe R. Davis 7, 8 *, Yuan He 9 *, Brian Jo 10 *, Pejman Mohammadi 5, 6 *, YoSon Park 11 *, Princy Parsana 12 *, Ayellet V. Segrè 1 *, Benjamin J. Strober 9 *, Zachary Zappala 7, 8 *

                Laboratory, Data Analysis & Coordinating Center (LDACC): Beryl B. Cummings 1, 13 , Ellen T. Gelfand 1 , Kane Hadley 1 , Katherine H. Huang 1 , Monkol Lek 1, 13 , Xiao Li 1 , Jared L. Nedzel 1 , Duyen Y. Nguyen 1 , Michael S. Noble 1 , Timothy J. Sullivan 1 , Taru Tukiainen 1, 13 , Daniel G. MacArthur 1, 13 , Gad Getz 1, 14

                NIH program management: Anjene Addington 15 , Ping Guan 16 , Susan Koester 15 , A. Roger Little 17 , Nicole C. Lockhart 18 , Helen M. Moore 16 , Abhi Rao 16 , Jeffery P. Struewing 19 , Simona Volpi 19

                Biospecimen collection: Lori E. Brigham 20 , Richard Hasz 21 , Marcus Hunter 22 , Christopher Johns 23 , Mark Johnson 24 , Gene Kopen 25 , William F. Leinweber 25 , John T. Lonsdale 25 , Alisa McDonald 25 , Bernadette Mestichelli 25 , Kevin Myer 22 , Bryan Roe 22 , Michael Salvatore 25 , Saboor Shad 25 , Jeffrey A. Thomas 25 , Gary Walters 24 , Michael Washington 24 , Joseph Wheeler 23 , Jason Bridge 26 , Barbara A. Foster 27 , Bryan M. Gillard 27 , Ellen Karasik 27 , Rachna Kumar 27 , Mark Miklos 26 , Michael T. Moser 27 , Scott D. Jewell 28 , Robert G. Montroy 28 , Daniel C. Rohrer 28 , Dana Valley 28 , Deborah C. Mash 29 , David A. Davis 29

                Pathology: Leslie Sobin 30 , Mary E. Barcus 30 , Philip A. Branton 16

                eQTL manuscript working group: Nathan S. Abell 7, 8 , Brunilda Balliu 8 , Olivier Delaneau 2, 3, 4 , Laure Frésard 8 , Eric R. Gamazon 31 , Diego Garrido-Martín 32, 33 , Ariel D. H. Gewirtz 10 , Genna Gliner 34 , Michael J. Gloudemans 8, 35 , Buhm Han 36 , Amy Z. He 12 , Farhad Hormozdiari 37 , Xin Li 8 , Boxiang Liu 8, 38 , Eun Yong Kang 39 , Ian C. McDowell 40 , Halit Ongen 2, 3, 4 , John J. Palowitch 41 , Christine B. Peterson 42 , Gerald Quon 1, 43 , Stephan Ripke 13, 44 , Ashis Saha 12 , Andrey A. Shabalin 45 , Tyler C. Shimko 7, 8 , Jae Hoon Sul 46 , Nicole A. Teran 7, 8 , Emily K. Tsang 8, 35 , Hailei Zhang 1 , Yi-Hui Zhou 47 , Carlos D. Bustamante 7, 48 , Nancy J. Cox 31 , Roderic Guigó 32, 33 , Manolis Kellis 1, 43 , Mark I. McCarthy 49, 50, 51 , Donald F. Conrad 52, 53 , Eleazar Eskin 37, 39 , Gen Li 54 , Andrew B. Nobel 41 , Chiara Sabatti 48, 55 , Barbara E. Stranger 56 , Xiaoquan Wen 57 , Fred A. Wright 58 , Kristin G. Ardlie 1 , Emmanouil T. Dermitzakis 2, 3, 4 , Tuuli Lappalainen 5, 6

                Corresponding authors: Alexis Battle 12 § , Christopher D. Brown 11 § , Barbara E. Engelhardt 59 § & Stephen B. Montgomery 7, 8 §

                [1]

                The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

                [2]

                Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.

                [3]

                Institute for Genetics and Genomics in Geneva (iG3), University of Geneva, 1211 Geneva, Switzerland.

                [4]

                Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland.

                [5]

                New York Genome Center, New York, New York 10013, USA.

                [6]

                Department of Systems Biology, Columbia University, New York, New York 10032, USA.

                [7]

                Department of Genetics, Stanford University, Stanford, California 94305, USA.

                [8]

                Department of Pathology, Stanford University, Stanford, California 94305, USA.

                [9]

                Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.

                [10]

                Lewis Sigler Institute, Princeton University, Princeton, New Jersey 08450, USA.

                [11]

                Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

                [12]

                Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA.

                [13]

                Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

                [14]

                Massachusetts General Hospital Cancer Center and Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA.

                [15]

                Division of Neuroscience and Basic Behavioral Science, National Institute of Mental Health, Bethesda, Maryland 20892, USA.

                [16]

                Biorepositories and Biospecimen Research Branch, Cancer Diagnosis Program, National Cancer Institute, Bethesda, Maryland 20892, USA.

                [17]

                Division of Neuroscience and Behavior, National Institute on Drug Abuse, Bethesda, Maryland 20892, USA.

                [18]

                Division of Genomics and Society, National Human Genome Research Institute, Bethesda, Maryland 20892, USA.

                [19]

                Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, Maryland 20892, USA.

                [20]

                Washington Regional Transplant Community, Annandale, Virginia 22003, USA.

                [21]

                Gift of Life Donor Program, Philadelphia, Pennsylvania 19103, USA.

                [22]

                LifeGift, Houston, Texas 77055, USA.

                [23]

                Center for Organ Recovery and Education, Pittsburgh, Pennsylvania 15238, USA.

                [24]

                LifeNet Health, Virginia Beach, Virginia 23453, USA.

                [25]

                National Disease Research Interchange, Philadelphia, Pennsylvania 19103, USA.

                [26]

                Unyts, Buffalo, New York 14203, USA.

                [27]

                Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, New York 14263, USA.

                [28]

                Van Andel Research Institute, Grand Rapids, Michegan 49503, USA.

                [29]

                Department of Neurology, Miller School of Medicine, University of Miami, Miami, Florida 33136, USA.

                [30]

                Leidos Biomedical Research Inc., Rockville, Maryland 20852, USA.

                [31]

                Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA.

                [32]

                Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 88, 08003 Barcelona, Spain.

                [33]

                Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain.

                [34]

                Department of Operations Research and Financial Engineering, Princeton University, Princeton, New Jersey 84540, USA.

                [35]

                Biomedical Informatics Program, Stanford University, Stanford, California 94305, USA.

                [36]

                Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505, Korea.

                [37]

                Department of Human Genetics, University of California, Los Angeles, California 90095, USA.

                [38]

                Department of Biology, Stanford University, Stanford, California 94305, USA.

                [39]

                Department of Computer Science, University of California, Los Angeles, California 90095, USA.

                [40]

                Computational Biology and Bioinformatics Graduate Program, Duke University, Durham, North Carolina 27708, USA.

                [41]

                Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, North Carolina 27599, USA.

                [42]

                Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.

                [43]

                Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts 02139, USA.

                [44]

                Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

                [45]

                Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University, Richmond, Virginia 23298, USA.

                [46]

                Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, California 90095, USA.

                [47]

                Bioinformatics Research Center and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA.

                [48]

                Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA.

                [49]

                Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK.

                [50]

                Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK.

                [51]

                Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford OX3 7LE, UK.

                [52]

                Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, Missouri 63110, USA.

                [53]

                Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.

                [54]

                Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York 10032, USA.

                [55]

                Department of Statistics, Stanford University, Stanford, California 94305, USA.

                [56]

                Section of Genetic Medicine, Department of Medicine, Institute for Genomics and Systems Biology, Center for Data Intensive Science, University of Chicago, Chicago, Illinois 60637, USA.

                [57]

                Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.

                [58]

                Bioinformatics Research Center, Departments of Statistics and Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA.

                [59]

                Department of Computer Science and Center for Statistics and Machine Learning, Princeton University, Princeton, New Jersey 08540, USA.

                [*]

                These authors contributed equally to this work.

                [§]

                These authors jointly supervised this work.

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                9 December 2017
                11 October 2017
                22 January 2018
                : 550
                : 7675
                : 204-213
                29022597 5776756 10.1038/nature24277 NIHMS925370

                This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons licence, users will need to obtain permission from the licence holder to reproduce the material. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                Reprints and permissions information is available at www.nature.com/reprints.

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