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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

BMC NEUROscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

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Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

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Author Correction: A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

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Nature communications 2019年第1期10卷 2956页

作者： Lohith Madireddy Kicheol Kim Xiaoming Jia Adam Santaniello Stacy J. Caillier Bruce A. C. Cree Roland Henry Stephen L. Hauser Jorge R. Oksenberg Sergio E. Baranzini Nikolaos A. Patsopoulos Philip De Jager Chris Cotsapas Matthew R. Lincoln David A. Hafler Steffan D. Bos Hanne F. Harbo Tone Berge Elisabeth G. Celius Ashley Beecham Jacob McCauley Margaret A. Pericak-Vance Till F. M. Andlauer Christiane Gasperi Bernhard Hemmer Lisa F. Barcellos Luisa Bernardinelli Filippo Martinelli-Boneschi David R. Booth Graeme J. Stewart Farren Briggs Jonathan Haines Manuel Comabella Giancarlo Comi Federica Esposito Sandra D’Alfonso Katrina Dedham Pierre Duquette Efthimios Dardiotis Bertrand Fontaine An Goris Bénédicte Dubois Pierre-Antoine Gourraud Georgios Hadjigeorgiou Clive Hawkins Seema Kalra Rogier Hintzen Dana Horakova Noriko Isobe Jun-ichi Kira Michael Khalil Ingrid Kockum Tomas Olsson Christina M. Lill Felix Luessi Frauke Zipp Roland Martin Annette Oturai Aarno Palotie Janna Saarela Adrian Ivinson Bruce V. Taylor Alastair Compston Stephen Sawcer Weill Institute for Neurosciences Department of Neurology University of California San Francisco San Francisco CA 94158 USA Bakar Institute for Computational Health Science. University of California San Francisco San Francisco CA 94158 USA Systems Biology and Computer Science Program Ann Romney Center for Neurological Diseases Department of Neurology and Division of Genetics Department of Medicine Brigham & Women’s Hospital Harvard Medical School Boston MA 02115 USA Broad Institute of Harvard University and Massachusetts Institute of Technology Cambridge MA 02142 USA Department of Neurology Center for Translational and Computational Neuroimmunology and Multiple Sclerosis Center Columbia University Medical Center New York NY 10032 USA Departments of Neurology Yale School of Medicine 300 George St New Haven CT 06511 USA Department of Genetics Yale School of Medicine 300 George St New Haven CT 06511 USA Institute of Clinical Medicine University of Oslo Oslo 0318 Norway Department of Neurology Oslo University Hospital Oslo 0424 Norway Department of Mechanical Electronics and Chemical Engineering Oslo Metropolitan University Oslo 0167 Norway Institute of Health and Society University of Oslo Oslo 0318 Norway John P. Hussman Institute for Human Genomics University of Miami Miller School of Medicine Miami FL 33136 USA Dr. John T. Macdonald Foundation Department of Human Genetics University of Miami Miller School of Medicine Miami FL 33136 USA Department of Neurology Klinikum rechts der Isar School of Medicine Technical University of Munich 81675 Munich Germany Munich Cluster for Systems Neurology (SyNergy) 81377 Munich Germany Division of Epidemiology School of Public HealthUniversity of California 324 Stanley Hall MC#3220 Berkeley CA 94720 USA Section of Biostatistics Neurophyisiology and Psychiatry Unit of medical and genomic statistics Universita of Pavia Pavia 27100 Italy Department of Biomedical Sciences for Health Univers

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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DDX5 and its associated lncRNA Rmrp modulate T_H17 cell effector functions

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Nature 2015年第7583期528卷 517-522页

作者： Huang, Wendy Thomas, Benjamin Flynn, Ryan A. Gavzy, Samuel J. Wu, Lin Kim, Sangwon V. Hall, Jason A. Miraldi, Emily R. Ng, Charles P. Rigo, Frank W. Meadows, Sarah Montoya, Nina R. Herrera, Natalia G. Domingos, Ana I. Rastinejad, Fraydoon Myers, Richard M. Fuller-Pace, Frances V. Bonneau, Richard Chang, Howard Y. Acuto, Oreste Littman, Dan R. Kimmel Center for Biology and Medicine Skirball Institute New York University School of Medicine New York 10016 NY United States Sir William Dunn School of Pathology University of Oxford Oxford OX1 3RE United Kingdom Center for Personal Dynamic Regulomes Stanford University Stanford 94305 CA United States Center for Genomics and Systems Biology Department of Biology New York University New York 10003 NY United States Courant Institute of Mathematical Sciences Computer Science Department New York University New York 10012 NY United States Simons Center for Data Analysis Simons Foundation New York 10010 NY United States Isis Pharmaceuticals Carlsbad 92010 CA United States HudsonAlpha Institute for Biotechnology Huntsville 35806 AL United States Instituto Gulbenkian de Ciencia Oeiras 2780-156 Portugal Integrative Metabolism Program Sanford Burnham Prebys Medical Discovery Institute Orlando 32827 FL United States Division of Cancer Research University of Dundee Dundee DD1 9SY United Kingdom Howard Hughes Medical Institute New York University School of Medicine New York 10016 NY United States

T helper 17 (TH17) lymphocytes protect mucosal barriers from infections, but also contribute to multiple chronic inflammatory diseases. Their differentiation is controlled by RORγt, a ligand-regulated nuclear recepto...

T helper 17 (T_H17) lymphocytes protect mucosal barriers from infections, but also contribute to multiple chronic inflammatory diseases. Their differentiation is controlled by RORγt, a ligand-regulated nuclear receptor. Here we identify the RNA helicase DEAD-box protein 5 (DDX5) as a RORγt partner that coordinates transcription of selective T_H17 genes, and is required for T_H17-mediated inflammatory pathologies. Surprisingly, the ability of DDX5 to interact with RORγt and coactivate its targets depends on intrinsic RNA helicase activity and binding of a conserved nuclear long noncoding RNA (lncRNA), Rmrp, which is mutated in patients with cartilage-hair hypoplasia. A targeted Rmrp gene mutation in mice, corresponding to a gene mutation in cartilage-hair hypoplasia patients, altered lncRNA chromatin occupancy, and reduced the DDX5-RORγt interaction and RORγt target gene transcription. Elucidation of the link between Rmrp and the DDX5-RORγt complex reveals a role for RNA helicases and lncRNAs in tissue-specific transcriptional regulation, and provides new opportunities for therapeutic intervention in T_H17-dependent diseases. © 2015 Macmillan Publishers Limited. All rights reserved.

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme

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systems Biomedicine 2013年第2期1卷 130-136页

作者： Riku Louhimo Viljami Aittom?ki Ali Faisal Marko Laakso Ping Chen Kristian Ovaska Erkka Valo Leo Lahti Vladimir Rogojin Samuel Kaski Sampsa Hautaniemi* Systems Biology Laboratory Genome-scale Biology Research Program University of Helsinki Helsinki Institute of Information Technology (HIIT) Department of Information and Computer Science Aalto University

Background:Cancers are complex diseases whose comprehensive characterization requires genome-scale molecular data at multiple levels from genetics to transcriptomics and clinical data. Using our recently published Anduril bioinformatics framework and novel computational approaches, such as dependency analysis, we identify key variables at miRNA, copy number variation, expression, methylation, and pathway levels in glioblastoma multiforme (GBM) progression and drug resistance. Furthermore, we identify characteristics of clinically relevant subgroups, such as patients treated with temozolomide and patients with an EGFRvIII mutation, which is a constitutively active variant of ***:We identify several novel genomic regions and transcript profiles that may contribute to GBM progression and drug resistance. All results and Anduril scripts are available at http://***/camda/.Conclusions:Our results highlight the need for approaches that define context at several levels in order to identify genomic regions or transcript profiles playing key roles in cancer progression and drug resistance.

关键词： data integration data mining dependency analysis

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Spectral clustering strategies for heterogeneous disease expression data 18

Spectral clustering strategies for heterogeneous disease exp...

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18th Pacific Symposium on Biocomputing, PSB 2013

作者： Huang, Grace T. Cunningham, Kathryn I. Benos, Panayiotis V. Chennubhotla, Chakra S. Department of Computational and Systems Biology University of Pittsburgh PittsburghPA United States Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh PittsburghPA United States Clinical and Translational Science Institute University of Pittsburgh PittsburghPA United States Department of Computer Science University of Arizona TucsonAZ United States

Clustering of gene expression data simplifies subsequent data analyses and forms the basis of numerous approaches for biomarker identification, prediction of clinical outcome, and personalized therapeutic strategies. The most popular clustering methods such as K-means and hierarchical clustering are intuitive and easy to use, but they require arbitrary choices on their various parameters (number of clusters for K-means, and a threshold to cut the tree for hierarchical clustering). Human disease gene expression data are in general more difficult to cluster efficiently due to background (genotype) heterogeneity, disease stage and progression differences and disease subtyping;all of which cause gene expression datasets to be more heterogeneous. Spectral clustering has been recently introduced in many fields as a promising alternative to standard clustering methods. The idea is that pairwise comparisons can help reveal global features through the eigen techniques. In this paper, we developed a new recursive K-means spectral clustering method (ReKS) for disease gene expression data. We benchmarked ReKS on three large-scale cancer datasets and we compared it to different clustering methods with respect to execution time, background models and external biological knowledge. We found ReKS to be superior to the hierarchical methods and equally good to K-means, but much faster than them and without the requirement for a priori knowledge of K. Overall, ReKS offers an attractive alternative for efficient clustering of human disease data.

关键词： Cluster analysis

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The FAIR Guiding Principles for scientific data management and stewardship

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Scientific data 2016年第1期3卷 160018页

作者： Mark D Wilkinson Michel Dumontier I Jsbrand Jan Aalbersberg Gabrielle Appleton Myles Axton Arie Baak Niklas Blomberg Jan-Willem Boiten Luiz Bonino da Silva Santos Philip E Bourne Jildau Bouwman Anthony J Brookes Tim Clark Mercè Crosas Ingrid Dillo Olivier Dumon Scott Edmunds Chris T Evelo Richard Finkers Alejandra Gonzalez-Beltran Alasdair J G Gray Paul Groth Carole Goble Jeffrey S Grethe Jaap Heringa Peter A C 't Hoen Rob Hooft Tobias Kuhn Ruben Kok Joost Kok Scott J Lusher Maryann E Martone Albert Mons Abel L Packer Bengt Persson Philippe Rocca-Serra Marco Roos Rene van Schaik Susanna-Assunta Sansone Erik Schultes Thierry Sengstag Ted Slater George Strawn Morris A Swertz Mark Thompson Johan van der Lei Erik van Mulligen Jan Velterop Andra Waagmeester Peter Wittenburg Katherine Wolstencroft Jun Zhao Barend Mons Center for Plant Biotechnology and Genomics Universidad Politécnica de Madrid Madrid 28223 Spain. Stanford University Stanford 94305-5411 USA. Nature Genetics New York 10004-1562 USA. Euretos and Phortos Consultants Rotterdam 2741 CA The Netherlands. ELIXIR Wellcome Genome Campus Hinxton CB10 1SA UK. Lygature Eindhoven 5656 AG The Netherlands. Vrije Universiteit Amsterdam Dutch Techcenter for Life Sciences Amsterdam 1081 HV The Netherlands. Office of the Director National Institutes of Health Rockville 20892 USA. TNO Zeist 3700 AJ The Netherlands. Department of Genetics University of Leicester Leicester LE1 7RH UK. Harvard Medical School Boston Massachusetts MA 02115 USA. Harvard University Cambridge Massachusetts MA 02138 USA. Data Archiving and Networked Services (DANS) The Hague 2593 HW The Netherlands. GigaScience Beijing Genomics Institute Shenzhen 518083 China. Department of Bioinformatics Maastricht University Maastricht 6200 MD The Netherlands. Wageningen UR Plant Breeding Wageningen 6708 PB The Netherlands. Oxford e-Research Center University of Oxford Oxford OX1 3QG UK. Heriot-Watt University Edinburgh EH14 4AS UK. School of Computer Science University of Manchester Manchester M13 9PL UK. Center for Research in Biological Systems School of Medicine University of California San Diego La Jolla California 92093-0446 USA. Dutch Techcenter for the Life Sciences Utrecht 3501 DE The Netherlands. Department of Human Genetics Leiden University Medical Center Dutch Techcenter for the Life Sciences Leiden 2300 RC The Netherlands. Dutch TechCenter for Life Sciences and ELIXIR-NL Utrecht 3501 DE The Netherlands. VU University Amsterdam Amsterdam 1081 HV The Netherlands. Leiden Center of Data Science Leiden University Leiden 2300 RA The Netherlands. Netherlands eScience Center Amsterdam 1098 XG The Netherlands. National Center for Microscopy and Imaging Research UCSD San Diego 92103 USA. Phortos Consultants San Diego 92011 USA. SciELO/FAPESP Pr

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

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Nature communications 2017年第1期8卷 1414页

作者： M Carola Zillikens Serkalem Demissie Yi-Hsiang Hsu Laura M Yerges-Armstrong Wen-Chi Chou Lisette Stolk Gregory Livshits Linda Broer Toby Johnson Daniel L Koller Zoltán Kutalik Jian'an Luan Ida Malkin Janina S Ried Albert V Smith Gudmar Thorleifsson Liesbeth Vandenput Jing Hua Zhao Weihua Zhang Ali Aghdassi Kristina Åkesson Najaf Amin Leslie J Baier Inês Barroso David A Bennett Lars Bertram Rainer Biffar Murielle Bochud Michael Boehnke Ingrid B Borecki Aron S Buchman Liisa Byberg Harry Campbell Natalia Campos Obanda Jane A Cauley Peggy M Cawthon Henna Cederberg Zhao Chen Nam H Cho Hyung Jin Choi Melina Claussnitzer Francis Collins Steven R Cummings Philip L De Jager Ilja Demuth Rosalie A M Dhonukshe-Rutten Luda Diatchenko Gudny Eiriksdottir Anke W Enneman Mike Erdos Johan G Eriksson Joel Eriksson Karol Estrada Daniel S Evans Mary F Feitosa Mao Fu Melissa Garcia Christian Gieger Thomas Girke Nicole L Glazer Harald Grallert Jagvir Grewal Bok-Ghee Han Robert L Hanson Caroline Hayward Albert Hofman Eric P Hoffman Georg Homuth Wen-Chi Hsueh Monica J Hubal Alan Hubbard Kim M Huffman Lise B Husted Thomas Illig Erik Ingelsson Till Ittermann John-Olov Jansson Joanne M Jordan Antti Jula Magnus Karlsson Kay-Tee Khaw Tuomas O Kilpeläinen Norman Klopp Jacqueline S L Kloth Heikki A Koistinen William E Kraus Stephen Kritchevsky Teemu Kuulasmaa Johanna Kuusisto Markku Laakso Jari Lahti Thomas Lang Bente L Langdahl Lenore J Launer Jong-Young Lee Markus M Lerch Joshua R Lewis Lars Lind Cecilia Lindgren Yongmei Liu Tian Liu Youfang Liu Östen Ljunggren Mattias Lorentzon Robert N Luben William Maixner Fiona E McGuigan Carolina Medina-Gomez Thomas Meitinger Håkan Melhus Dan Mellström Simon Melov Karl Michaëlsson Braxton D Mitchell Andrew P Morris Leif Mosekilde Anne Newman Carrie M Nielson Jeffrey R O'Connell Ben A Oostra Eric S Orwoll Aarno Palotie Stephen C J Parker Munro Peacock Markus Perola Annette Peters Ozren Polasek Richard L Prince Katri Räikkönen Stuart H Ralston Samuli Ripatti John A Robbins Jerome I Rotter Igor Rudan Veikko Department of Internal Medicine Erasmus MC Rotterdam 3000 The Netherlands. Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA) Leiden 2593 The Netherlands. Department of Biostatistics Boston University School of Public Health Boston MA 02118 USA. Hebrew SeniorLife Institute for Aging Research Roslindale MA 02131 USA. Harvard Medical School Boston MA 02115 USA. Molecular and Integrative Physiological Sciences Program Harvard School of Public Health Boston MA 02115 USA. Program in Personalized and Genomic Medicine and Department of Medicine Division of Endocrinology Diabetes and Nutrition University of Maryland School of Medicine Baltimore MD 21201 USA. Broad Institute Cambridge MA 02142 USA. Sackler Faculty of Medicine Department of Anatomy and Anthropology Tel Aviv University Tel Aviv 6997801 Israel. Department of Twin Research and Genetic Epidemiology King's College London St Thomas' Campus London WC2R 2LS UK. Department of Epidemiology Erasmus MC Rotterdam 3000 The Netherlands. Department of Medical Genetics University of Lausanne Lausanne 1011 Switzerland. Swiss Institute of Bioinformatics Lausanne 1015 Switzerland. Centre Hospitalier Universitaire (CHUV) University Institute for Social and Preventive Medicine Lausanne 1010 Switzerland. Department of Medical and Molecular Genetics Indiana University School of Medicine Indianapolis IN 46202 USA. MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge Biomedical Campus Cambridge CB2 OQQ UK. Institute of Epidemiology II Helmholtz Zentrum München - German Research Center for Environmental Health Neuherberg 85764 Germany. Icelandic Heart Association Kopavogur 201 Iceland. Faculty of Medicine University of Iceland Reykjavik 101 Iceland. deCODE Genetics Reykjavik 101 Iceland. Department of Internal Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg SE-405 30 Sweden. Dep

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