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Genetic Relationship Between Five Psychiatric Disorders Estimated from Genome-Wide Snps
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Hong Lee, Stephan Ripke, Benjamin Neale, Stephen Faraone, Shaun Purcell, Roy Perlis, Bryan Mowry, Anita Thapar, Michael Goddard, John Witte, et al. To cite this version: Hong Lee, Stephan Ripke, Benjamin Neale, Stephen Faraone, Shaun Purcell, et al.. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.. Nature Genetics, Nature Publishing Group, 2013, 45 (9), pp.984-94. <10.1038/ng.2711>. <inserm- 00864642> HAL Id: inserm-00864642 http://www.hal.inserm.fr/inserm-00864642 Submitted on 28 Mar 2014 HAL is a multi-disciplinary open access L'archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destin´eeau d´ep^otet `ala diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publi´esou non, lished or not. The documents may come from ´emanant des ´etablissements d'enseignement et de teaching and research institutions in France or recherche fran¸caisou ´etrangers,des laboratoires abroad, or from public or private research centers. publics ou priv´es. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs Cross-Disorder Group of the Psychiatric Genomics Consortium Correspondence to Naomi R. Wray The University of Queensland, Queensland Brain Institute, Brisbane, QLD, 4067 Australia. [email protected] Summary paragraph Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders versus shared across disorders is unclear. We use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) of cases and controls for schizophrenia (SCZ), bipolar disorder (BPD), major depressive disorder (MDD), autism spectrum disorders (ASD), and attention deficit hyperactivity disorder (ADHD). -
Additive Genetic Variability and the Bayesian Alphabet
Copyright Ó 2009 by the Genetics Society of America DOI: 10.1534/genetics.109.103952 Additive Genetic Variability and the Bayesian Alphabet Daniel Gianola,*,†,‡,1 Gustavo de los Campos,* William G. Hill,§ Eduardo Manfredi‡ and Rohan Fernando** *Department of Animal Sciences, University of Wisconsin, Madison, Wisconsin 53706, †Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, N-1432 A˚ s, Norway, ‡Institut National de la Recherche Agronomique, UR631 Station d’Ame´lioration Ge´ne´tique des Animaux, BP 52627, 32326 Castanet-Tolosan, France, §Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom and **Department of Animal Science, Iowa State University, Ames, Iowa 50011 Manuscript received April 14, 2009 Accepted for publication July 16, 2009 ABSTRACT The use of all available molecular markers in statistical models for prediction of quantitative traits has led to what could be termed a genomic-assisted selection paradigm in animal and plant breeding. This article provides a critical review of some theoretical and statistical concepts in the context of genomic- assisted genetic evaluation of animals and crops. First, relationships between the (Bayesian) variance of marker effects in some regression models and additive genetic variance are examined under standard assumptions. Second, the connection between marker genotypes and resemblance between relatives is explored, and linkages between a marker-based model and the infinitesimal model are reviewed. Third, issues associated with the use of Bayesian models for marker-assisted selection, with a focus on the role of the priors, are examined from a theoretical angle. The sensitivity of a Bayesian specification that has been proposed (called ‘‘Bayes A’’) with respect to priors is illustrated with a simulation. -
The Path to New Therapies for Schizophrenia and Bipolar Illness
THE JOURNAL • PERSPECTIVE • www.fasebj.org The Path to New Therapies for Schizophrenia and Bipolar Illness Edward M. Scolnick1 Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts, USA ABSTRACT: Schizophrenia and bipolar illness are two of the most serious forms of mental illness. Until relatively recently, almost nothing was known about the molecular pathogenesis of either illness. The single largest risk factor that predisposes people to schizophrenia or bipolar illness is genetic risk. Heritability is high, and the incidence is significantly higher in identical twins than in nonidentical twins. Despite decades of work aimed at identifying the genes involved in these two illnesses, virtually no progress had been made until the past decade. With the knowledge and technologies that have been gained from the Human Genome Project, it has been possible to begin to understand the underlying genetics and to use the new information to begin the effort to discover new and better medicines to treat these illnesses. This article will describe the past decade of work toward this goal and articulate both the promise that now exists and what is still needed to bring dramatic and tangible change to patients.—Scolnick, E. M. The path to new therapies for schizophrenia and bipolar illness. FASEB J. 31, 1254–1259 (2017). www.fasebj.org KEY WORDS: genetics • pharmacology • progress In the fall of 2004, I became an associate member of the bipolar illness for many years. Virtually no reproducible Broad Institute, founded on the principle of collaboration results had been achieved. The Broad Institute had a su- among scientists at the Massachusetts Institute of Tech- perb group of scientific experts in human genetics, a field nology, Harvard, and Harvard-affiliated hospitals. -
A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits
| INVESTIGATION A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits Daniel Gianola*,†,‡,§,1 and Rohan L. Fernando‡ *Department of Animal Sciences, and †Department of Dairy Science, University of Wisconsin-Madison, Wisconsin 53706, ‡Department of Animal Science, Iowa State University, Ames, Iowa 50011, and §Department of Plant Sciences, Technical University of Munich (TUM), TUM School of Life Sciences, Freising, 85354 Germany ORCID IDs: 0000-0001-8217-2348 (D.G.); 0000-0001-5821-099X (R.L.F.) ABSTRACT A multiple-trait Bayesian LASSO (MBL) for genome-based analysis and prediction of quantitative traits is presented and applied to two real data sets. The data-generating model is a multivariate linear Bayesian regression on possibly a huge number of molecular markers, and with a Gaussian residual distribution posed. Each (one per marker) of the T 3 1 vectors of regression coefficients (T: number of traits) is assigned the same T2variate Laplace prior distribution, with a null mean vector and unknown scale matrix Σ. The multivariate prior reduces to that of the standard univariate Bayesian LASSO when T ¼ 1: The covariance matrix of the residual distribution is assigned a multivariate Jeffreys prior, and Σ is given an inverse-Wishart prior. The unknown quantities in the model are learned using a Markov chain Monte Carlo sampling scheme constructed using a scale-mixture of normal distributions representation. MBL is demonstrated in a bivariate context employing two publicly available data sets using a bivariate genomic best linear unbiased prediction model (GBLUP) for benchmarking results. The first data set is one where wheat grain yields in two different environments are treated as distinct traits. -
2014 Graduates of Iowa State University!
Dear Iowa State University Graduates and Guests: Congratulations to all of the Spring 2014 graduates of Iowa State University! We are very proud of you for the successful completion of your academic programs, and we are pleased to present you with a degree from Iowa State University recognizing this outstanding achievement. We also congratulate and thank everyone who has played a role in the graduates’ successful journey through this university, and we are delighted that many of you are here for this ceremony to share in their recognition and celebration. We have enjoyed having you as students at Iowa State, and we thank you for the many ways you have contributed to our university and community. I wish you the very best as you embark on the next part of your life, and I encourage you to continue your association with Iowa State as part of our worldwide alumni family. Iowa State University is now in its 156th year as one of the nation’s outstanding land-grant universities. We are very proud of the role this university has played in preparing the future leaders of our state, nation and world, and in meeting the needs of our society through excellence in education, research and outreach. As you graduate today, you are now a part of this great tradition, and we look forward to the many contributions you will make. I hope you enjoy today’s commencement ceremony. We wish you all continued success! Sincerely, Steven Leath President of the University TABLE OF CONTENTS The Official University Mace ...........................................................................................................................3 -
Mrsec Program Annual Report and Continuation Request
MRSEC PROGRAM ANNUAL REPORT AND CONTINUATION REQUEST For the Period March 1, 2016 – May 31, 2017 Under Grant No. DMR-1419807 Submitted to THE NATIONAL SCIENCE FOUNDATION by The Center for Materials Science and Engineering Massachusetts Institute of Technology Cambridge, Massachusetts June 1, 2017 TABLE OF CONTENTS 1. EXECUTIVE SUMMARY 1-5 2. PARTICIPANTS IN THE CENTER FOR MATERIALS SCIENCE AND 6-11 ENGINEERING, March 1, 2016 TO May 31, 2017 3. COLLABORATORS WITH THE CENTER FOR MATERIALS SCIENCE AND 12 ENGINEERING OVER THE LAST 63 MONTHS, March 1, 2016 TO May 31, 2017 4. CENTER STRATEGIC PLAN 13 5. RESEARCH ACCOMPLISHMENTS AND PLANS 14-34 6. EDUCATION AND HUMAN RESOURCES 35-39 7. POSTDOC MENTORING PLAN 40 7. DATA MANAGEMENT PLAN 41 8. CENTER DIVERSITY 42-44 9. KNOWLEDGE TRANSFER TO INDUSTRY AND OTHER SECTORS 45-46 10. INTERNATIONAL ACTIVITIES 47 11. SHARED EXPERIMENTAL FACILITIES 48-49 12. ADMINISTRATION AND MANAGEMENT 50-51 13. PH.D.s AWARDED, March 1, 2016 TO May 31, 2017 52-53 13. POSTDOCTORAL ASSOCIATES PLACEMENT, March 1, 2016 TO May 31, 2017 54 14. PUBLICATIONS, March 1, 2016 TO June 1, 2017 55-69 14. CMSE PATENTS APPLIED/GRANTED, March 1, 2016 TO May 31, 2017 70-71 15. BIOGRAPHIES 72-76 16. CENTER PARTICIPANTS’ HONORS AND AWARDS, March 1, 2016 TO May 31, 77-78 2017 17. HIGHLIGHTS: March 1, 2016 TO May 31, 2017 79-92 18. STATEMENT OF UNOBLIGATED FUNDS 93 19. BUDGETS 94- 100 APPENDICES A – K 101- 116 1. EXECUTIVE SUMMARY 1a. Center Vision and Director’s Overview: The underlying mission of the CMSE MRSEC is to enable – through interdisciplinary fundamental research, innovative educational outreach programs and directed knowledge transfer – the development and understanding of new materials, structures and theories that can impact the current and future needs of society. -
SUNDAY PETERS, Phd Dept. of Animal Science, Berry College, Mount Berry, GA 30149 Office: 706-368-6919; Cell: 575-571-9089
SUNDAY PETERS, PhD Dept. of Animal Science, Berry College, Mount Berry, GA 30149 Office: 706-368-6919; Cell: 575-571-9089. Email: [email protected] EDUCATION & TRAINING June 2011 – August, 2012 Postdoctoral Research Associate, Department of Animal Science, Department of Biomedical Sciences, Cornell University, Ithaca, NY 14853. 2008 - 2011 Ph.D. Molecular Biology. New Mexico State University, Las Cruces, NM, 88003, USA. Dissertation: Genome-wide Association Studies of Growth and Fertility in Brangus Heifers. 100pp. 2002 - 2005 Ph.D. Animal Breeding and Genetics. University of Agriculture, Abeokuta. Nigeria. Dissertation: Variation in Semen Quality, Reproductive and Growth Performance of Artificially Inseminated Strains of Pure and Crossbred Chickens. 213pp. 1997 -2000 M.S. Animal Breeding and Genetics. University of Agriculture, Abeokuta. Nigeria. Thesis: Genetic Variation in the Reproductive Performance of the Indigenous Chicken and the Growth Rate of its Pure and Half-bred Progeny. 120pp. 1989 -1995 B.S. - Animal Science. University of Agriculture, Abeokuta. Nigeria. Honor’s Project: Strain Differences in Broiler Performance. 120pp. PATENTS/TRADEMARKS/INTERLLECTUAL PROPERTY FUNAAB Alpha Improved Chicken with registration number NGGGD-18-02 PROFESSIONAL DEV. SHORT COURSES & CONTINUING EDUCATION 2012 Statistical Methods for Genome-Enabled Selection Animal Breeding and Genetics Unit, Department of Animal Science, Iowa State University, Ames, IA, U.S.A, May 6 -10 (Instructors: Daniel Gianola and Gustavo de los Campos). 2011 Summer Institute in Statistical Genetics (Modules: Bayesian Methods for Genetics, MCMC for Genetics, Mixed Models in Quantitative Genetics, Gene Expression Profiling, Advanced R Programming for Bioinformatics and GWAS Data Cleaning) University of Washington, Seattle, WA. June 13 – July 1. 2010 USDA/NRI/AFRI Annual Investigator Meeting. -
Queensland Brain Institute 2014 Annual Report
Queensland Brain Institute 2014 Annual Report Queensland Brain Institute 2014 Annual Report Cover Image: Garden of Neurons by Gonzalo Almarza We are studying different populations of neurons in the cortex. In this image, subplate neurons (green) extend their processes towards the pial surface during early cortical development. These neurons project through the emerging cortical plate (in red), arborising in the marginal zone (in blue). Queensland Brain Institute Annual Report 2014 UQ Vice-Chancellor and President’s Report ........................1 QBI Director’s Report ...........................................2 Discovery 4 Genome analysis reveals schizophrenia’s secrets ...................6 Halting the damaging effects of stroke ............................8 Revealing the complexity of wiring the brain. .10 Redefining how we plan movement in the brain ....................12 Controlling fear may be possible by controlling DNA ................14 Research 16 Anggono Laboratory ........17 Goodhill Laboratory .........27 Mowry Laboratory ..........37 Srinivasan Laboratory .......43 Bartlett Laboratory ..........18 Götz Laboratory ............28 Osborne Laboratory .........38 van Swinderen Laboratory ...44 Bredy Laboratory ...........19 Hilliard Laboratory ..........29 Piper Laboratory ............39 Visscher Laboratory .........45 Burne Laboratory ...........20 Jiang Laboratory ............30 Reinhard Laboratory ........40 Williams Laboratory .........46 Cheung Laboratory .........21 Lynch Laboratory ...........31 Richards Laboratory .........41 -
Acknowledgment of Reviewers, 2015
Acknowledgment of Reviewers, 2015 The PNAS editors would like to thank all the individuals who dedicated their considerable time and expertise to the journal by serving as reviewers in 2015. Their generous contribution is deeply appreciated. A Peter B. Adler Colin J. Akerman Eric E. Allen James Ammerman Duur K. Aanen Ralph Adolphs Joshua M. Akey Heather C. Allen David M. Amodio Adam R. Abate Ruedi Aebersold Anna Akhmanova Jim Allen Valentin Amrhein John T. Abatzoglou Hugo Aerts Hajime Akimoto Karen N. Allen Esther Amstad Jonathan Abbatt Hagit P. Affek Akin Akinc Michael F. Allen Ronald Amundson Allison Abbott Arash Afraz Shizuo Akira Paul M. Allen Weihua An Jeffrey Abbott Theodor Agapie Ozan Akkus Rosalind J. Allen Zhiqiang An Larry F. Abbott David A. Agard Ivona Aksentijevich Morten Erik Allentoft Laura Diaz Anadon Nicholas L. Abbott Sapan Agarwal Serap Aksoy Stefano Allesina Ganesh Srinivasan Anand Chaouki T. Abdallah Joel W. Ager III Yousef Al-Abed David B. Allison Cort Anastasio Omar Abdel-Wahab Ingi Agnarsson Ashraf Al-Amoudi Steven D. Allison Lefteris Jason Ikuro Abe Anurag A. Agrawal Eric E. Alani Julian M. Allwood Anastasopoulos Stephen Tobias Abedon Ashutosh Agrawal Balbino Alarcón Eric J. Alm Hossain Anawar Moshe Abeles Rakesh Agrawal Qais Al-Awqati Benjamin A. Alman Elissar Andari Asa Abeliovich Jon Ågren Joseph Albanesi Ingvild Almas William R. L. Anderegg John Aber Alan Agresti Francis Albarede Steven C. Almo John M. Anderies Clara Abraham Jeremy J. Agresti Umberto Albarella Douglas Almond Mark L. Andermann John Abraham Jay J. Ague Silas D. Alben Uri Alon Bogi Andersen Daniel A. Abrams Fernan Agüero Frank Alber José M. -
Annual Report 2000
ST. KILDA SOAY SHEEP PROJECT: ANNUAL REPORT 2000 J.G. Pilkington1+3, S.D. Albon2, W. Amos3, D.W. Coltman1+8, T.H. Clutton- Brock3, T.N. Coulson3, M.J. Crawley4, M.C. Forchhammer3, I. Gordon5, B.T. Grenfell3, M. Hutchings5, A.W. Illius1, O. Jones4+5, L. Kruuk1, J. Lindström3+7, J.M. Pemberton1, B. Preston6, I.R. Stevenson6, K. Wilson6. 1Institute of Cell, Animal and Population Biology, University of Edinburgh. 2Centre for Ecology and Hydrology, Banchory 3Department of Zoology, University of Cambridge. 4Department of Biology, Imperial College, University of London. 5Macaulay Land Use Research Institute, Aberdeen. 6Institute of Biological Sciences, University of Stirling. New addresses – 7Institute of Biomedical and Life Sciences, University of Glasgow. 8Department of Animal and Plant Sciences, University of Sheffield. POPULATION OVERVIEW..................................................................................................................................... 2 REPORTS ON COMPONENT STUDIES .................................................................................................................... 4 Reproductive energetics of rams, and the maintenance of horn diversity .................................................... 4 Ram behaviour with respect to "favoured" insemination times .................................................................... 5 Sperm depletion in Soay rams....................................................................................................................... 7 Vegetation .................................................................................................................................................... -
Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution Timothée Bonnet , Michael B
Journal of Heredity, 2019, 1–13 doi:10.1093/jhered/esz018 THE 2017 AGA KEY DISTINGUISHED LECTURE Advance Access publication June 26, 2019 Downloaded from https://academic.oup.com/jhered/advance-article-abstract/doi/10.1093/jhered/esz018/5523732 by Da-Collect Chifley Library ANUC user on 01 July 2019 THE 2017 AGA KEY DISTINGUISHED LECTURE Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution Timothée Bonnet , Michael B. Morrissey, and Loeske E. B. Kruuk From the Division of Ecology and Evolution, Research School of Biology, The Australian National University, 46 Sullivans Creek Road, Canberra, ACT 2600, Australia (Bonnet and Kruuk); and School of Biology, University of St Andrews, St Andrews Fife KY16 9TH, UK (Morrissey). Address correspondence to Timothée Bonnet at the address above, or e-mail: [email protected]. Received November 14, 2018; First decision January 23, 2019; Accepted April 7, 2019. Corresponding Editor: Anne Bronikowski Loeske Kruuk is a professor in the Research School of Biology at the Australian National University. She did a PhD in population genetics at the University of Edinburgh, followed by a postdoc at the University of Cambridge, and then held a Royal Society University Research Fellowship at the University of Edinburgh and an Australian Research Council Future Fellowship at the Australian National University. Her research focuses on evolutionary ecology and quantitative genetics of natural populations, with the aim of understanding how both evolutionary processes and environmental conditions shape diversity in natural populations. She has worked on a range of species, largely but not entirely using long-term studies of wild vertebrate populations with individual-level field data. -
Evolutionary Dynamics and Fitness in Wild Populations
2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproductionEvolutionary even in part is prohibited. dynamics and fitness in wild populations 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited. 2018 © 48th European Contact Lens Society Of Ophthalmologists. All rights reserved - Any reproduction even in part is prohibited] . Loeske Kruuk 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited] . Charles Darwin, Origin of Species 1859 “ No one supposes that all the individuals of the same species are cast in the same actual mould. These individual differences are of the highest importance for us, 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited. for they are often inherited …and they thus afford materials for natural selection to act on. ” evolutionary change: genetics and selection 2018 © II Joint Congress on Evolutionary Biology 2018. All rights reserved - Any reproduction even in part is prohibited.