1
|
Hafner C, Manschein V, Klaus DA, Schaubmayr W, Tiboldi A, Scharner V, Gleiss A, Thal B, Krammel M, Hamp T, Willschke H, Hermann M. Live stream of prehospital point-of-care ultrasound during cardiopulmonary resuscitation - A feasibility trial. Resuscitation 2024; 194:110089. [PMID: 38110144 DOI: 10.1016/j.resuscitation.2023.110089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Current resuscitation guidelines recommend that skilled persons could use ultrasound to detect reversible causes during cardiopulmonary resuscitation (CPR) where the examination can be safely integrated into the Advanced Life Support (ALS) algorithm. However, in a prehospital setting performing and rapidly interpreting ultrasound can be challenging for physicians. Implementing remote, expert-guided, and real-time transmissions of ultrasound examinations offers the opportunity for tele-support, even during an out-of-hospital cardiac arrest (OHCA). The aim of this feasibility study was to evaluate the impact of tele-supported ultrasound in ALS on hands-off time during an OHCA. METHODS In an urban setting, physicians performed point-of-care ultrasound (POCUS) on patients during OHCA using a portable device, either with tele-support (n = 30) or without tele-support (n = 12). Where tele-support was used, the ultrasound image was transmitted via a remote real-time connection to an on-call specialist in anaesthesia and intensive care medicine with an advanced level of critical care ultrasound expertise. The primary safety endpoint of this study was to evaluate whether POCUS can be safely integrated into the algorithm, and to provide an analysis of hands-off time before, during, and after POCUS during OHCA. RESULTS In all 42 cases it was possible to perform POCUS during regular rhythm analyses, and no additional hands-off time was required. In 40 of these 42 cases, the physicians were able to perform POCUS during a single regular rhythm analysis, with two periods required only in two cases. The median hands-off time during these rhythm analyses for POCUS with tele-support was 10 (8-13) seconds, and 11 (9-14) seconds for POCUS without tele-support. Furthermore, as a result of POCUS, in a quarter of all cases the physician on scene altered their diagnosis of the primary suspected cause of cardiac arrest, leading to a change in treatment strategy. CONCLUSIONS This feasibility study demonstrated that POCUS with tele-support can be safely performed during OHCA in an urban environment. Trial Registration (before patient enrolment): ClinicalTrials.gov, NCT04817475.
Collapse
Affiliation(s)
- C Hafner
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; Ludwig Boltzmann Institute Digital Health and Patient Safety, Waehringer Straße 104/10, 1180 Vienna, Austria
| | - V Manschein
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - D A Klaus
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - W Schaubmayr
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - A Tiboldi
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - V Scharner
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - A Gleiss
- Centre for Medical Data Science, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria
| | - B Thal
- Emergency Medical Service Vienna, Radetzkystrasse 1, 1030 Vienna, Austria
| | - M Krammel
- Emergency Medical Service Vienna, Radetzkystrasse 1, 1030 Vienna, Austria; PULS - Austrian Cardiac Arrest Awareness Association, Lichtenthaler Gasse 4/1/R03, 1090 Vienna, Austria
| | - T Hamp
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; Emergency Medical Service Vienna, Radetzkystrasse 1, 1030 Vienna, Austria
| | - H Willschke
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; Ludwig Boltzmann Institute Digital Health and Patient Safety, Waehringer Straße 104/10, 1180 Vienna, Austria
| | - M Hermann
- Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; Ludwig Boltzmann Institute Digital Health and Patient Safety, Waehringer Straße 104/10, 1180 Vienna, Austria.
| |
Collapse
|
2
|
Fiziev PP, McRae J, Ulirsch JC, Dron JS, Hamp T, Yang Y, Wainschtein P, Ni Z, Schraiber JG, Gao H, Cable D, Field Y, Aguet F, Fasnacht M, Metwally A, Rogers J, Marques-Bonet T, Rehm HL, O'Donnell-Luria A, Khera AV, Farh KKH. Rare penetrant mutations confer severe risk of common diseases. Science 2023; 380:eabo1131. [PMID: 37262146 DOI: 10.1126/science.abo1131] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 03/16/2023] [Indexed: 06/03/2023]
Abstract
We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.
Collapse
Affiliation(s)
- Petko P Fiziev
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jacob C Ulirsch
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jacqueline S Dron
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tobias Hamp
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Yanshen Yang
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Pierrick Wainschtein
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zijian Ni
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Joshua G Schraiber
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Hong Gao
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Dylan Cable
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02142, USA
| | - Yair Field
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Francois Aguet
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Marc Fasnacht
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Ahmed Metwally
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Verve Therapeutics, Cambridge, MA 02215, USA
| | - Kyle Kai-How Farh
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| |
Collapse
|
3
|
Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, Fiziev PP, Kuderna LFK, Sundaram L, Wu Y, Adhikari A, Field Y, Chen C, Batzoglou S, Aguet F, Lemire G, Reimers R, Balick D, Janiak MC, Kuhlwilm M, Orkin JD, Manu S, Valenzuela A, Bergman J, Rousselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath JE, Hvilsom C, Juan D, Frandsen P, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, do Amaral JV, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Bataillon T, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin A, Guschanski K, Schierup MH, Beck RMD, Umapathy G, Roos C, Boubli JP, Lek M, Sunyaev S, O'Donnell-Luria A, Rehm HL, Xu J, Rogers J, Marques-Bonet T, Farh KKH. The landscape of tolerated genetic variation in humans and primates. Science 2023; 380:eabn8153. [PMID: 37262156 DOI: 10.1126/science.abn8197] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/22/2023] [Indexed: 06/03/2023]
Abstract
Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.
Collapse
Affiliation(s)
- Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Tobias Hamp
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Jeffrey Ede
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Joshua G Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Jeremy McRae
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Moriel Singer-Berk
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
| | - Yanshen Yang
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | | | - Petko P Fiziev
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Lukas F K Kuderna
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Laksshman Sundaram
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Yibing Wu
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Aashish Adhikari
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Yair Field
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Chen Chen
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Serafim Batzoglou
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Francois Aguet
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Rebecca Reimers
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel Balick
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Mareike C Janiak
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Martin Kuhlwilm
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, 1030 Vienna, Austria
| | - Joseph D Orkin
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Département d'anthropologie, Université de Montréal, 3150 Jean-Brillant, Montréal, QC H3T 1N8, Canada
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Alejandro Valenzuela
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University, 8000 Aarhus, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development, Estrada da Bexiga 2584, Tefé, Amazonas, CEP 69553-225, Brazil
- Evolutionary Biology and Ecology (EBE), Département de Biologie des Organismes, Université libre de Bruxelles (ULB), Av. Franklin D. Roosevelt 50, CP 160/12, B-1050 Brussels, Belgium
| | - Lidia Agueda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Ian Goodhead
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - R Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
| | | | - Julie E Horvath
- North Carolina Museum of Natural Sciences, Raleigh, NC 27601, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | | | - Fabrício Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah, Salt Lake City, UT 84102, USA
| | - Iracilda Sampaio
- Universidade Federal do Para, Guamá, Belém - PA, 66075-110, Brazil
| | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
| | - João Valsecchi do Amaral
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development, Tefé, Amazonas, 69553-225, Brazil
- Rede de Pesquisa para Estudos sobre Diversidade, Conservação e Uso da Fauna na Amazônia - RedeFauna, Manaus, Amazonas, 69080-900, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica - ComFauna, Iquitos, Loreto, 16001, Peru
| | - Mariluce Messias
- Universidade Federal de Rondonia, Porto Velho, Rondônia, 78900-000, Brazil
- PPGREN - Programa de Pós-Graduação "Conservação e Uso dos Recursos Naturais and BIONORTE - Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Rede BIONORTE, Universidade Federal de Rondonia, Porto Velho, Rondônia, 78900-000, Brazil
| | - Maria N F da Silva
- Instituto Nacional de Pesquisas da Amazonia, Petrópolis, Manaus - AM, 69067-375, Brazil
| | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Rogerio Rossi
- Universidade Federal do Mato Grosso, Boa Esperança, Cuiabá - MT, 78060-900, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
- Department of Biology, Trinity University, San Antonio, TX 78212, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | - Clément J Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | | | | | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Christian Abee
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Joe H Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Eduardo Fernandez-Duque
- Yale University, New Haven, CT 06520, USA
- Universidad Nacional de Formosa, Argentina Fundacion ECO, Formosa, Argentina
| | | | - Fekadu Shiferaw
- Guinea Worm Eradication Program, The Carter Center Ethiopia, PoB 16316, Addis Ababa 1000, Ethiopia
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
- Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Shangcheng District, Hangzhou 310006, China
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Head Office, P.O. Box 661, Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, 17493 Greifswald - Insei Riems, Germany
| | - Minh D Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University, Hanoi 100000, Vietnam
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart, 70191 Stuttgart, Germany
| | - Arcadi Navarro
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Av. Doctor Aiguader, N88, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C. Wellington 30, 08005 Barcelona, Spain
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
| | - Tilo Nadler
- Cuc Phuong Commune, Nho Quan District, Ninh Binh Province 430000, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
| | - Jessica Lee
- Mandai Nature, 80 Mandai Lake Road, Singapore 729826, Republic of Singapore
| | - Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore 168582, Republic of Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore 168582, Republic of Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore 168582, Republic of Singapore
| | - Andrew C Kitchener
- Department of Natural Sciences, National Museums Scotland, Chambers Street, Edinburgh EH1 1JF, UK
- School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077 Göttingen, Germany
- Leibniz Science Campus Primate Cognition, 37077 Göttingen, Germany
| | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra, Pg. Luís Companys 23, 08010 Barcelona, Spain
| | - Amanda Melin
- Department of Anthropology & Archaeology, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
- Department of Medical Genetics, 3330 Hospital Drive NW, HMRB 202, Calgary, AB T2N 4N1, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH8 9XP, UK
| | | | - Robin M D Beck
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Jean P Boubli
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Shamil Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jinbo Xu
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| |
Collapse
|
4
|
Fiziev P, McRae J, Ulirsch JC, Dron JS, Hamp T, Yang Y, Wainschtein P, Ni Z, Schraiber JG, Gao H, Cable D, Field Y, Aguet F, Fasnacht M, Metwally A, Rogers J, Marques-Bonet T, Rehm HL, O’Donnell-Luria A, Khera AV, Kai-How Farh K. Rare penetrant mutations confer severe risk of common diseases. medRxiv 2023:2023.05.01.23289356. [PMID: 37205493 PMCID: PMC10187340 DOI: 10.1101/2023.05.01.23289356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ∼10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared to common variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction. One sentence summary Rare variant polygenic risk scores identify individuals with outlier phenotypes in common human diseases and complex traits.
Collapse
Affiliation(s)
- Petko Fiziev
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jacob C. Ulirsch
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jacqueline S. Dron
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
| | - Tobias Hamp
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Yanshen Yang
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Pierrick Wainschtein
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Zijian Ni
- Department of Statistics, UW Madison; Madison, Wisconsin 53706, USA
| | - Joshua G. Schraiber
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Hong Gao
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Dylan Cable
- Department of Electrical Engineering and Computer Science, MIT; Cambridge, Massachusetts 02142, USA
| | - Yair Field
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Francois Aguet
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Marc Fasnacht
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Ahmed Metwally
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
- Wisconsin National Primate Research Center, University of Wisconsin; Madison 53715, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC); 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA); 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona; 08193 Barcelona, Spain
| | - Heidi L. Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital; Boston, Massachusetts 02114, USA
| | - Anne O’Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital; Boston, Massachusetts 02114, USA
- Division of Genetics and Genomics, Boston Children’s Hospital; Boston, Massachusetts 02115, USA
| | - Amit V. Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Verve Therapeutics, Cambridge, Massachusetts 02215, USA
| | - Kyle Kai-How Farh
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| |
Collapse
|
5
|
Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich A, Fiziev P, Kuderna L, Sundaram L, Wu Y, Adhikari A, Field Y, Chen C, Batzoglou S, Aguet F, Lemire G, Reimers R, Balick D, Janiak MC, Kuhlwilm M, Orkin JD, Manu S, Valenzuela A, Bergman J, Rouselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath J, Hvilsom C, Juan D, Frandsen P, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, do Amaral JV, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Batallion T, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin A, Guschanski K, Schierup MH, Beck RMD, Umapathy G, Roos C, Boubli JP, Lek M, Sunyaev S, O’Donnell A, Rehm H, Xu J, Rogers J, Marques-Bonet T, Kai-How Farh K. The landscape of tolerated genetic variation in humans and primates. bioRxiv 2023:2023.05.01.538953. [PMID: 37205491 PMCID: PMC10187174 DOI: 10.1101/2023.05.01.538953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence Summary Deep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.
Collapse
Affiliation(s)
- Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Tobias Hamp
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Jeffrey Ede
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Joshua G. Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Jeremy McRae
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Moriel Singer-Berk
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
| | - Yanshen Yang
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Anastasia Dietrich
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Petko Fiziev
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Lukas Kuderna
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Laksshman Sundaram
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Yibing Wu
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Aashish Adhikari
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Yair Field
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Chen Chen
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Serafim Batzoglou
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Francois Aguet
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Rebecca Reimers
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Daniel Balick
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Mareike C. Janiak
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Martin Kuhlwilm
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna; Djerassiplatz 1, 1030, Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna; 1030, Vienna, Austria
| | - Joseph D. Orkin
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Département d’anthropologie, Université de Montréal; 3150 Jean-Brillant, Montréal, QC, H3T 1N8, Canada
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR); Ghaziabad, 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Alejandro Valenzuela
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University; Aarhus, 8000, Denmark
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University; Aarhus, 8000, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development; Estrada da Bexiga 2584, Tefé, Amazonas, CEP 69553-225, Brazil
- Faculty of Sciences, Department of Organismal Biology, Unit of Evolutionary Biology and Ecology, Université Libre de Bruxelles (ULB); Avenue Franklin D. Roosevelt 50, 1050, Brussels, Belgium
| | - Lidia Agueda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Ian Goodhead
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - R. Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University; SE-75236, Uppsala, Sweden
| | | | - Julie Horvath
- North Carolina Museum of Natural Sciences; Raleigh, North Carolina, 27601, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University; Durham, North Carolina , 27707, USA
- Department of Biological Sciences, North Carolina State University; Raleigh, North Carolina , 27695, USA
- Department of Evolutionary Anthropology, Duke University; Durham, North Carolina , 27708, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | | | - Fabricio Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah; Salt Lake City, Utah, 84102, USA
| | - Iracilda Sampaio
- Universidade Federal do Para; Guamá, Belém - PA, 66075-110, Brazil
| | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
| | - João Valsecchi do Amaral
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development; Tefé, Amazonas, 69553-225, Brazil
- Rede de Pesquisa para Estudos sobre Diversidade, Conservação e Uso da Fauna na Amazônia – RedeFauna; Manaus, Amazonas, 69080-900, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica – ComFauna; Iquitos, Loreto, 16001, Peru
| | - Mariluce Messias
- Universidade Federal de Rondonia; Porto Velho, Rondônia, 78900-000, Brazil
- PPGREN - Programa de Pós-Graduação “Conservação e Uso dos Recursos Naturais and BIONORTE - Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Rede BIONORTE, Universidade Federal de Rondonia; Porto Velho, Rondônia, 78900-000, Brazil
| | - Maria N. F. da Silva
- Instituto Nacional de Pesquisas da Amazonia; Petrópolis, Manaus - AM, 69067-375, Brazil
| | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Rogerio Rossi
- Universidade Federal do Mato Grosso; Boa Esperança, Cuiabá - MT, 78060-900, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
- Department of Biology, Trinity University; San Antonio, Texas, 78212, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | - Clément J. Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | | | | | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center; Houston, Texas, 77030, USA
| | | | - Joe H. Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center; Houston, Texas, 77030, USA
| | - Eduardo Fernandez-Duque
- Yale University; New Haven, Connecticut, 06520, USA
- Universidad Nacional de Formosa, Argentina Fundacion ECO, Formosa, Argentina
| | | | | | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences; Kunming, Yunnan, 650223, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences; Kunming, Yunnan, 650223, China
| | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen; Copenhagen, DK-2100, Denmark
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center; 1369 West Wenyi Road, Hangzhou, 311121, China
- Women’s Hospital, School of Medicine, Zhejiang University; 1 Xueshi Road, Shangcheng District, Hangzhou, 310006, China
| | - Julius D. Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Head Office; P.O.Box 661, Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health; 17493 Greifswald - Isle of Riems, Germany
| | - Minh D. Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University; Hanoi, 100000, Vietnam
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain; Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart; 70191 Stuttgart, Germany
| | - Arcadi Navarro
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology; Av. Doctor Aiguader, N88, Barcelona, 08003, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation; C. Wellington 30, Barcelona, 08005, Spain
| | - Thomas Batallion
- Bioinformatics Research Centre, Aarhus University; Aarhus, 8000, Denmark
| | - Tilo Nadler
- Cuc Phuong Commune; Nho Quan District, Ninh Binh Province, 430000, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
| | - Jessica Lee
- Mandai Nature; 80 Mandai Lake Road, Singapore 729826, Republic of Singapore
| | - Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM); Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School; Singapore 168582, Republic of Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM); Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School; Singapore 168582, Republic of Singapore
- SingHealth Duke-NUS Genomic Medicine Centre; Singapore 168582, Republic of Singapore
| | - Andrew C. Kitchener
- Department of Natural Sciences, National Museums Scotland; Chambers Street, Edinburgh, EH1 1JF, UK
- School of Geosciences, University of Edinburgh; Drummond Street, Edinburgh, EH8 9XP, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research; 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen; 37077 Göttingen, Germany
| | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
- Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
| | - Amanda Melin
- Leibniz Science Campus Primate Cognition; 37077 Göttingen, Germany
- Department of Anthropology & Archaeology and Department of Medical Genetics
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University; SE-75236, Uppsala, Sweden
- Alberta Children’s Hospital Research Institute; University of Calgary; 2500 University Dr NW T2N 1N4, Calgary, Alberta, Canada
| | | | - Robin M. D. Beck
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR); Ghaziabad, 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Christian Roos
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh; Edinburgh, EH8 9XP, UK
| | - Jean P. Boubli
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Monkol Lek
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research; Kellnerweg 4, 37077 Göttingen, Germany
| | - Shamil Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
- Department of Genetics, Yale School of Medicine; New Haven, Connecticut, 06520, USA
| | - Anne O’Donnell
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Heidi Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Jinbo Xu
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
- Toyota Technological Institute at Chicago; Chicago, Illinois, 60637, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain; Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| |
Collapse
|
6
|
Hamp T, Baron-Stefaniak J, Krammel M, Reiter B, Langauer A, Stimpfl T, Plöchl W. Effect of intravenous S-ketamine on the MAC of sevoflurane: a randomised, placebo-controlled, double-blinded clinical trial. Br J Anaesth 2018; 121:1242-1248. [DOI: 10.1016/j.bja.2018.08.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Revised: 08/02/2018] [Accepted: 08/28/2018] [Indexed: 11/24/2022] Open
|
7
|
Abstract
MOTIVATION Protein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods. RESULTS We extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, recent methods explicitly ignored such a network-structure and rely either on domain knowledge or sequence-only methods. Our approach is independent of domain-knowledge and leverages evolutionary information. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/. The data can also be downloaded from https://figshare.com/collections/ProfPPI-DB/4141784.
Collapse
Affiliation(s)
- Linh Tran
- Imperial College London (ICL), Department of Computing, United Kingdom
- Technical University of Munich (TUM), Department of Informatics, Bioinformatics & Computational Biology - i12, Boltzmannstr, Germany
- * E-mail:
| | - Tobias Hamp
- Technical University of Munich (TUM), Department of Informatics, Bioinformatics & Computational Biology - i12, Boltzmannstr, Germany
| | - Burkhard Rost
- Technical University of Munich (TUM), Department of Informatics, Bioinformatics & Computational Biology - i12, Boltzmannstr, Germany
- Technical University of Munich (TUM), Institute for Advanced Study (TUM-IAS), Lichtenbergstr, Germany
| |
Collapse
|
8
|
Jiang Y, Oron TR, Clark WT, Bankapur AR, D'Andrea D, Lepore R, Funk CS, Kahanda I, Verspoor KM, Ben-Hur A, Koo DCE, Penfold-Brown D, Shasha D, Youngs N, Bonneau R, Lin A, Sahraeian SME, Martelli PL, Profiti G, Casadio R, Cao R, Zhong Z, Cheng J, Altenhoff A, Skunca N, Dessimoz C, Dogan T, Hakala K, Kaewphan S, Mehryary F, Salakoski T, Ginter F, Fang H, Smithers B, Oates M, Gough J, Törönen P, Koskinen P, Holm L, Chen CT, Hsu WL, Bryson K, Cozzetto D, Minneci F, Jones DT, Chapman S, Bkc D, Khan IK, Kihara D, Ofer D, Rappoport N, Stern A, Cibrian-Uhalte E, Denny P, Foulger RE, Hieta R, Legge D, Lovering RC, Magrane M, Melidoni AN, Mutowo-Meullenet P, Pichler K, Shypitsyna A, Li B, Zakeri P, ElShal S, Tranchevent LC, Das S, Dawson NL, Lee D, Lees JG, Sillitoe I, Bhat P, Nepusz T, Romero AE, Sasidharan R, Yang H, Paccanaro A, Gillis J, Sedeño-Cortés AE, Pavlidis P, Feng S, Cejuela JM, Goldberg T, Hamp T, Richter L, Salamov A, Gabaldon T, Marcet-Houben M, Supek F, Gong Q, Ning W, Zhou Y, Tian W, Falda M, Fontana P, Lavezzo E, Toppo S, Ferrari C, Giollo M, Piovesan D, Tosatto SCE, Del Pozo A, Fernández JM, Maietta P, Valencia A, Tress ML, Benso A, Di Carlo S, Politano G, Savino A, Rehman HU, Re M, Mesiti M, Valentini G, Bargsten JW, van Dijk ADJ, Gemovic B, Glisic S, Perovic V, Veljkovic V, Veljkovic N, Almeida-E-Silva DC, Vencio RZN, Sharan M, Vogel J, Kansakar L, Zhang S, Vucetic S, Wang Z, Sternberg MJE, Wass MN, Huntley RP, Martin MJ, O'Donovan C, Robinson PN, Moreau Y, Tramontano A, Babbitt PC, Brenner SE, Linial M, Orengo CA, Rost B, Greene CS, Mooney SD, Friedberg I, Radivojac P. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biol 2016; 17:184. [PMID: 27604469 PMCID: PMC5015320 DOI: 10.1186/s13059-016-1037-6] [Citation(s) in RCA: 252] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 08/04/2016] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. RESULTS We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. CONCLUSIONS The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
Collapse
Affiliation(s)
- Yuxiang Jiang
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA
| | | | - Wyatt T Clark
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Asma R Bankapur
- Department of Microbiology, Miami University, Oxford, OH, USA
| | | | | | - Christopher S Funk
- Computational Bioscience Program, University of Colorado School of Medicine, Aurora, CO, USA
| | - Indika Kahanda
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - Karin M Verspoor
- Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria, Australia
- Health and Biomedical Informatics Centre, University of Melbourne, Parkville, Victoria, Australia
| | - Asa Ben-Hur
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | | | - Duncan Penfold-Brown
- Social Media and Political Participation Lab, New York University, New York, NY, USA
- CY Data Science, New York, NY, USA
| | - Dennis Shasha
- Department of Computer Science, New York University, New York, NY, USA
| | - Noah Youngs
- CY Data Science, New York, NY, USA
- Department of Computer Science, New York University, New York, NY, USA
- Simons Center for Data Analysis, New York, NY, USA
| | - Richard Bonneau
- Department of Computer Science, New York University, New York, NY, USA
- Simons Center for Data Analysis, New York, NY, USA
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, USA
| | - Alexandra Lin
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA
| | - Sayed M E Sahraeian
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | | | - Giuseppe Profiti
- Biocomputing Group, BiGeA, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, BiGeA, University of Bologna, Bologna, Italy
| | - Renzhi Cao
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Zhaolong Zhong
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Jianlin Cheng
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Adrian Altenhoff
- ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Nives Skunca
- ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Christophe Dessimoz
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
- University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tunca Dogan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Kai Hakala
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
| | - Suwisa Kaewphan
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
- Turku Centre for Computer Science, Turku, Finland
| | - Farrokh Mehryary
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
| | - Tapio Salakoski
- Department of Information Technology, University of Turku, Turku, Finland
- Turku Centre for Computer Science, Turku, Finland
| | - Filip Ginter
- Department of Information Technology, University of Turku, Turku, Finland
| | - Hai Fang
- University of Bristol, Bristol, UK
| | | | | | | | - Petri Törönen
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Patrik Koskinen
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Liisa Holm
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
- Department of Biological and Environmental Sciences, Universitity of Helsinki, Helsinki, Finland
| | - Ching-Tai Chen
- Institute of Information Science, Academia Sinica, Taipei, Taiwan
| | - Wen-Lian Hsu
- Institute of Information Science, Academia Sinica, Taipei, Taiwan
| | - Kevin Bryson
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Domenico Cozzetto
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Federico Minneci
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - David T Jones
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Samuel Chapman
- Department of Computational Science and Engineering, North Carolina A&T State University, Greensboro, NC, USA
| | - Dukka Bkc
- Department of Computational Science and Engineering, North Carolina A&T State University, Greensboro, NC, USA
| | - Ishita K Khan
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Dan Ofer
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nadav Rappoport
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amos Stern
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Elena Cibrian-Uhalte
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Paul Denny
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca E Foulger
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Reija Hieta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Duncan Legge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Ruth C Lovering
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Michele Magrane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Anna N Melidoni
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | | | - Klemens Pichler
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Aleksandra Shypitsyna
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Biao Li
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Pooya Zakeri
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- iMinds Department Medical Information Technologies, Leuven, Belgium
| | - Sarah ElShal
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- iMinds Department Medical Information Technologies, Leuven, Belgium
| | - Léon-Charles Tranchevent
- Inserm UMR-S1052, CNRS UMR5286, Cancer Research Centre of Lyon, Lyon, France
- Université de Lyon 1, Villeurbanne, France
- Centre Léon Bérard, Lyon, France
| | - Sayoni Das
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Natalie L Dawson
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - David Lee
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Jonathan G Lees
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London, UK
| | | | | | - Alfonso E Romero
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Rajkumar Sasidharan
- Department of Molecular, Cell and Developmental Biology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Haixuan Yang
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland
| | - Alberto Paccanaro
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory, New York, NY, USA
| | | | - Paul Pavlidis
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Shou Feng
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA
| | - Juan M Cejuela
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Tatyana Goldberg
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Tobias Hamp
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Lothar Richter
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Asaf Salamov
- DOE Joint Genome Institute, Walnut Creek, CA, USA
| | - Toni Gabaldon
- Bioinformatics and Genomics, Centre for Genomic Regulation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - Marina Marcet-Houben
- Bioinformatics and Genomics, Centre for Genomic Regulation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Fran Supek
- Universitat Pompeu Fabra, Barcelona, Spain
- Division of Electronics, Rudjer Boskovic Institute, Zagreb, Croatia
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation, Barcelona, Spain
| | - Qingtian Gong
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Wei Ning
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Yuanpeng Zhou
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Marco Falda
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Paolo Fontana
- Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Carlo Ferrari
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Manuel Giollo
- Department of Information Engineering, University of Padua, Padova, Italy
- Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Damiano Piovesan
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Silvio C E Tosatto
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Angela Del Pozo
- Instituto De Genetica Medica y Molecular, Hospital Universitario de La Paz, Madrid, Spain
| | - José M Fernández
- Spanish National Bioinformatics Institute, Spanish National Cancer Research Institute, Madrid, Spain
| | - Paolo Maietta
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Alfonso Valencia
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Michael L Tress
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Alfredo Benso
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Stefano Di Carlo
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Gianfranco Politano
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Alessandro Savino
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Hafeez Ur Rehman
- National University of Computer & Emerging Sciences, Islamabad, Pakistan
| | - Matteo Re
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Marco Mesiti
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Giorgio Valentini
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Joachim W Bargsten
- Applied Bioinformatics, Bioscience, Wageningen University and Research Centre, Wageningen, Netherlands
| | - Aalt D J van Dijk
- Applied Bioinformatics, Bioscience, Wageningen University and Research Centre, Wageningen, Netherlands
- Biometris, Wageningen University, Wageningen, Netherlands
| | - Branislava Gemovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Sanja Glisic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Vladmir Perovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Veljko Veljkovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Nevena Veljkovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | | | - Ricardo Z N Vencio
- Department of Computing and Mathematics FFCLRP-USP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - Malvika Sharan
- Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany
| | - Jörg Vogel
- Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany
| | - Lakesh Kansakar
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Shanshan Zhang
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Slobodan Vucetic
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Zheng Wang
- University of Southern Mississippi, Hattiesburg, MS, USA
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK
| | - Mark N Wass
- School of Biosciences, University of Kent, Canterbury, Kent, UK
| | - Rachael P Huntley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Maria J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Peter N Robinson
- Institut für Medizinische Genetik und Humangenetik, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Yves Moreau
- Department of Electrical Engineering ESAT-SCD and IBBT-KU Leuven Future Health Department, Katholieke Universiteit Leuven, Leuven, Belgium
| | | | - Patricia C Babbitt
- California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, CA, USA
| | - Steven E Brenner
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Michal Linial
- Department of Chemical Biology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Christine A Orengo
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Burkhard Rost
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Casey S Greene
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean D Mooney
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Iddo Friedberg
- Department of Microbiology, Miami University, Oxford, OH, USA.
- Department of Computer Science, Miami University, Oxford, OH, USA.
| | - Predrag Radivojac
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA.
| |
Collapse
|
9
|
Hamp T, Mairweck M, Schiefer J, Krammel M, Pablik E, Wolzt M, Plöchl W. Feasibility of a 'reversed' isolated forearm technique by regional antagonization of rocuronium-induced neuromuscular block: a pilot study. Br J Anaesth 2016; 116:797-803. [PMID: 26934944 DOI: 10.1093/bja/aew018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/09/2015] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The isolated forearm technique is used to monitor intraoperative awareness. However, this technique cannot be applied to patients who must be kept deeply paralysed for >1h, because the tourniquet preventing the neuromuscular blocking agent from paralysing the forearm must be deflated from time to time. To overcome this problem, we tested the feasibility of a 'reversed' isolated forearm technique. METHODS Patients received rocuronium 0.6 mg kg(-1) i.v. to achieve muscle paralysis. A tourniquet was then inflated around one upper arm to prevent further blood supply to the forearm. Sugammadex was injected into a vein of this isolated forearm to antagonize muscle paralysis regionally. A dose titration of sugammadex to antagonize muscle paralysis in the isolated forearm was performed in 10 patients, and the effects of the selected dose were observed in 10 additional patients. RESULTS The sugammadex dose required to antagonize muscle paralysis in the isolated forearm was 0.03 mg kg(-1) in 30 ml of 0.9% saline. Muscle paralysis was antagonized in the isolated forearm within 3.2 min in nine of 10 patients; the rest of the patients' bodies remained paralysed. Releasing the tourniquet 15 min later did not affect the train-of-four count in the isolated forearm but significantly increased the train-of-four count in the other arm by 7%. CONCLUSIONS Regional antagonization of rocuronium-induced muscle paralysis using a sugammadex dose of 0.03 mg kg(-1) injected into an isolated forearm was feasible and did not have relevant systemic effects. CLINICAL TRIAL REGISTRATION The trial was registered at EudraCT (ref. no. 2013-002164-53) before patient enrolment began.
Collapse
Affiliation(s)
- T Hamp
- Department of General Anaesthesia and Intensive Care Medicine
| | - M Mairweck
- Department of General Anaesthesia and Intensive Care Medicine
| | - J Schiefer
- Department of General Anaesthesia and Intensive Care Medicine
| | - M Krammel
- Department of General Anaesthesia and Intensive Care Medicine
| | - E Pablik
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Section for Medical Statistics
| | - M Wolzt
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - W Plöchl
- Department of General Anaesthesia and Intensive Care Medicine
| |
Collapse
|
10
|
Hamp T, Rost B. Evolutionary profiles improve protein–protein interaction prediction from sequence. Bioinformatics 2015; 31:1945-50. [DOI: 10.1093/bioinformatics/btv077] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 02/02/2015] [Indexed: 11/14/2022] Open
|
11
|
Abstract
MOTIVATION Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard cross-validation protocols usually fail in biology. Park and Marcotte found that even refined protocols fail for protein-protein interactions (PPIs). RESULTS Here, we sketch additional problems for the prediction of PPIs from sequence alone. First, it not only matters whether proteins A or B of a target interaction A-B are similar to proteins of training interactions (positives), but also whether A or B are similar to proteins of non-interactions (negatives). Second, training on multiple interaction partners per protein did not improve performance for new proteins (not used to train). In contrary, a strictly non-redundant training that ignored good data slightly improved the prediction of difficult cases. Third, which prediction method appears to be best crucially depends on the sequence similarity between the test and the training set, how many true interactions should be found and the expected ratio of negatives to positives. The correct assessment of performance is the most complicated task in the development of prediction methods. Our analyses suggest that PPIs square the challenge for this task.
Collapse
Affiliation(s)
- Tobias Hamp
- Department of Informatics, Bioinformatics and Computational Biology I12, Technische Universität München, 85748 Garching/Munich, Germany
| | - Burkhard Rost
- Department of Informatics, Bioinformatics and Computational Biology I12, Technische Universität München, 85748 Garching/Munich, Germany
| |
Collapse
|
12
|
Goldberg T, Hecht M, Hamp T, Karl T, Yachdav G, Ahmed N, Altermann U, Angerer P, Ansorge S, Balasz K, Bernhofer M, Betz A, Cizmadija L, Do KT, Gerke J, Greil R, Joerdens V, Hastreiter M, Hembach K, Herzog M, Kalemanov M, Kluge M, Meier A, Nasir H, Neumaier U, Prade V, Reeb J, Sorokoumov A, Troshani I, Vorberg S, Waldraff S, Zierer J, Nielsen H, Rost B. LocTree3 prediction of localization. Nucleic Acids Res 2014; 42:W350-5. [PMID: 24848019 PMCID: PMC4086075 DOI: 10.1093/nar/gku396] [Citation(s) in RCA: 189] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria and in three for archaea. The method outputs a score that reflects the reliability of each prediction. LocTree2 has performed on par with or better than any other state-of-the-art method. Here, we report the availability of LocTree3 as a public web server. The server includes the machine learning-based LocTree2 and improves over it through the addition of homology-based inference. Assessed on sequence-unique data, LocTree3 reached an 18-state accuracy Q18 = 80 ± 3% for eukaryotes and a six-state accuracy Q6 = 89 ± 4% for bacteria. The server accepts submissions ranging from single protein sequences to entire proteomes. Response time of the unloaded server is about 90 s for a 300-residue eukaryotic protein and a few hours for an entire eukaryotic proteome not considering the generation of the alignments. For over 1000 entirely sequenced organisms, the predictions are directly available as downloads. The web server is available at http://www.rostlab.org/services/loctree3.
Collapse
Affiliation(s)
- Tatyana Goldberg
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany TUM Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), 85748 Garching, Germany
| | - Maximilian Hecht
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Tobias Hamp
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Timothy Karl
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Guy Yachdav
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany Biosof LLC, New York, NY 10001, USA
| | - Nadeem Ahmed
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Uwe Altermann
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Philipp Angerer
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Sonja Ansorge
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Kinga Balasz
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Michael Bernhofer
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Alexander Betz
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Laura Cizmadija
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Kieu Trinh Do
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Julia Gerke
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Robert Greil
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Vadim Joerdens
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | | | - Katharina Hembach
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Max Herzog
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Maria Kalemanov
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Michael Kluge
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Alice Meier
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Hassan Nasir
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Ulrich Neumaier
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Verena Prade
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Jonas Reeb
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | | | - Ilira Troshani
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Susann Vorberg
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Sonja Waldraff
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Jonas Zierer
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany
| | - Henrik Nielsen
- Center for Biological Sequence Analysis, Department of Systems Biology, DTU, 2800 Lyngby, Denmark
| | - Burkhard Rost
- Department of Informatics, Bioinformatics-I12, TUM, 85748 Garching, Germany Biosof LLC, New York, NY 10001, USA Institute for Advanced Study (TUM-IAS), 85748 Garching, Germany New York Consortium on Membrane Protein Structure (NYCOMPS) & Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA Institute for Food and Plant Sciences WZW - Weihenstephan, 85350 Freising, Germany
| |
Collapse
|
13
|
Yachdav G, Kloppmann E, Kajan L, Hecht M, Goldberg T, Hamp T, Hönigschmid P, Schafferhans A, Roos M, Bernhofer M, Richter L, Ashkenazy H, Punta M, Schlessinger A, Bromberg Y, Schneider R, Vriend G, Sander C, Ben-Tal N, Rost B. PredictProtein--an open resource for online prediction of protein structural and functional features. Nucleic Acids Res 2014; 42:W337-43. [PMID: 24799431 PMCID: PMC4086098 DOI: 10.1093/nar/gku366] [Citation(s) in RCA: 435] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
PredictProtein is a meta-service for sequence analysis that has been predicting
structural and functional features of proteins since 1992. Queried with a
protein sequence it returns: multiple sequence alignments, predicted aspects of
structure (secondary structure, solvent accessibility, transmembrane helices
(TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered
regions) and function. The service incorporates analysis methods for the
identification of functional regions (ConSurf), homology-based inference of Gene
Ontology terms (metastudent), comprehensive subcellular localization prediction
(LocTree3), protein–protein binding sites (ISIS2),
protein–polynucleotide binding sites (SomeNA) and predictions of the
effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our
goal has always been to develop a system optimized to meet the demands of
experimentalists not highly experienced in bioinformatics. To this end, the
PredictProtein results are presented as both text and a series of intuitive,
interactive and visually appealing figures. The web server and sources are
available at http://ppopen.rostlab.org.
Collapse
Affiliation(s)
- Guy Yachdav
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany Biosof LLC, New York, NY 10001, USA TUM Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Edda Kloppmann
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany New York Consortium on Membrane Protein Structure (NYCOMPS), Columbia University, New York, NY 10032, USA
| | - Laszlo Kajan
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Maximilian Hecht
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany TUM Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Tatyana Goldberg
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany TUM Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Tobias Hamp
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Peter Hönigschmid
- Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, Freising 85354, Germany
| | - Andrea Schafferhans
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Manfred Roos
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Michael Bernhofer
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Lothar Richter
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany
| | - Haim Ashkenazy
- The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, 69978 Tel Aviv, Israel
| | - Marco Punta
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK Institute for Food and Plant Sciences WZW-Weihenstephan, Alte Akademie 8, Freising 85350, Germany
| | - Avner Schlessinger
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Yana Bromberg
- Biosof LLC, New York, NY 10001, USA Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Reinhard Schneider
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ 08901, USA
| | - Gerrit Vriend
- Luxembourg University & Luxembourg Centre for Systems Biomedicine, 4362 Belval, Luxembourg
| | - Chris Sander
- CMBI, NCMLS, Radboudumc Nijmegen Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Nir Ben-Tal
- Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, 10065 NY, USA
| | - Burkhard Rost
- Department of Informatics, Bioinformatics & Computational Biology i12, TUM (Technische Universität München), Garching/Munich 85748, Germany Biosof LLC, New York, NY 10001, USA New York Consortium on Membrane Protein Structure (NYCOMPS), Columbia University, New York, NY 10032, USA The Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, 69978 Tel Aviv, Israel Department of Biochemistry and Molecular Biophysics & New York Consortium on Membrane Protein Structure (NYCOMPS), Columbia University, New York, NY 10032, USA Institute for Advanced Study (TUM-IAS), Garching/Munich 85748, Germany
| |
Collapse
|
14
|
Abstract
One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.
Collapse
Affiliation(s)
- Tobias Hamp
- Bioinformatics & Computational Biology - I12, Department of Informatics, Technical University of Munich, Garching/Munich, Germany
| | - Tatyana Goldberg
- Bioinformatics & Computational Biology - I12, Department of Informatics, Technical University of Munich, Garching/Munich, Germany
- Center of Doctoral Studies in Informatics and Its Applications (CeDoSIA), Technical University of Munich Graduate School, Garching/Munich, Germany
| | - Burkhard Rost
- Bioinformatics & Computational Biology - I12, Department of Informatics, Technical University of Munich, Garching/Munich, Germany
- Institute of Advanced Study (TUM-IAS), Garching/Munich, Germany
- New York Consortium on Membrane Protein Structure (NYCOMPS) and Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America
- * E-mail:
| |
Collapse
|
15
|
Abstract
Motivation: Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled. Results: In this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data. Availability: Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2. Contact:localization@rostlab.org Supplementary Information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Tatyana Goldberg
- TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany.
| | | | | |
Collapse
|
16
|
Hamp T, Kassner R, Seemayer S, Vicedo E, Schaefer C, Achten D, Auer F, Boehm A, Braun T, Hecht M, Heron M, Hönigschmid P, Hopf TA, Kaufmann S, Kiening M, Krompass D, Landerer C, Mahlich Y, Roos M, Rost B. Homology-based inference sets the bar high for protein function prediction. BMC Bioinformatics 2013; 14 Suppl 3:S7. [PMID: 23514582 PMCID: PMC3584931 DOI: 10.1186/1471-2105-14-s3-s7] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference. METHODS Here, we describe a few methods that predict protein function exclusively through homology. Together, they set the bar or lower limit for future improvements. RESULTS AND CONCLUSIONS During the development of these methods, we faced two surprises. Firstly, our most successful implementation for the baseline ranked very high at CAFA1. In fact, our best combination of homology-based methods fared only slightly worse than the top-of-the-line prediction method from the Jones group. Secondly, although the concept of homology-based inference is simple, this work revealed that the precise details of the implementation are crucial: not only did the methods span from top to bottom performers at CAFA, but also the reasons for these differences were unexpected. In this work, we also propose a new rigorous measure to compare predicted and experimental annotations. It puts more emphasis on the details of protein function than the other measures employed by CAFA and may best reflect the expectations of users. Clearly, the definition of proper goals remains one major objective for CAFA.
Collapse
Affiliation(s)
- Tobias Hamp
- TUM, Department of Informatics, Bioinformatics & Computational Biology - I12 Boltzmannstr, 3, 85748 Garching/Munich, Germany
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
17
|
Radivojac P, Clark WT, Oron TR, Schnoes AM, Wittkop T, Sokolov A, Graim K, Funk C, Verspoor K, Ben-Hur A, Pandey G, Yunes JM, Talwalkar AS, Repo S, Souza ML, Piovesan D, Casadio R, Wang Z, Cheng J, Fang H, Gough J, Koskinen P, Törönen P, Nokso-Koivisto J, Holm L, Cozzetto D, Buchan DWA, Bryson K, Jones DT, Limaye B, Inamdar H, Datta A, Manjari SK, Joshi R, Chitale M, Kihara D, Lisewski AM, Erdin S, Venner E, Lichtarge O, Rentzsch R, Yang H, Romero AE, Bhat P, Paccanaro A, Hamp T, Kaßner R, Seemayer S, Vicedo E, Schaefer C, Achten D, Auer F, Boehm A, Braun T, Hecht M, Heron M, Hönigschmid P, Hopf TA, Kaufmann S, Kiening M, Krompass D, Landerer C, Mahlich Y, Roos M, Björne J, Salakoski T, Wong A, Shatkay H, Gatzmann F, Sommer I, Wass MN, Sternberg MJE, Škunca N, Supek F, Bošnjak M, Panov P, Džeroski S, Šmuc T, Kourmpetis YAI, van Dijk ADJ, ter Braak CJF, Zhou Y, Gong Q, Dong X, Tian W, Falda M, Fontana P, Lavezzo E, Di Camillo B, Toppo S, Lan L, Djuric N, Guo Y, Vucetic S, Bairoch A, Linial M, Babbitt PC, Brenner SE, Orengo C, Rost B, Mooney SD, Friedberg I. A large-scale evaluation of computational protein function prediction. Nat Methods 2013; 10:221-7. [PMID: 23353650 PMCID: PMC3584181 DOI: 10.1038/nmeth.2340] [Citation(s) in RCA: 564] [Impact Index Per Article: 51.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2012] [Accepted: 12/10/2012] [Indexed: 01/03/2023]
Abstract
A report on the results of the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.
Collapse
Affiliation(s)
- Predrag Radivojac
- School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
18
|
Abstract
The intricate molecular details of protein-protein interactions (PPIs) are crucial for function. Therefore, measuring the same interacting protein pair again, we expect the same result. This work measured the similarity in the molecular details of interaction for the same and for homologous protein pairs between different experiments. All scores analyzed suggested that different experiments often find exceptions in the interfaces of similar PPIs: up to 22% of all comparisons revealed some differences even for sequence-identical pairs of proteins. The corresponding number for pairs of close homologs reached 68%. Conversely, the interfaces differed entirely for 12-29% of all comparisons. All these estimates were calculated after redundancy reduction. The magnitude of interface differences ranged from subtle to the extreme, as illustrated by a few examples. An extreme case was a change of the interacting domains between two observations of the same biological interaction. One reason for different interfaces was the number of copies of an interaction in the same complex: the probability of observing alternative binding modes increases with the number of copies. Even after removing the special cases with alternative hetero-interfaces to the same homomer, a substantial variability remained. Our results strongly support the surprising notion that there are many alternative solutions to make the intricate molecular details of PPIs crucial for function.
Collapse
Affiliation(s)
- Tobias Hamp
- TUM, Bioinformatik - I12, Informatik, Garching, Germany
| | - Burkhard Rost
- TUM, Bioinformatik - I12, Informatik, Garching, Germany
- Institute of Advanced Study (IAS), TUM, Garching, Germany
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America
- * E-mail:
| |
Collapse
|
19
|
Abstract
MOTIVATION The slow growth of expert-curated databases compared to experimental databases makes it necessary to build upon highly accurate automated processing pipelines to make the most of the data until curation becomes available. We address this problem in the context of protein structures and their classification into structural and functional classes, more specifically, the structural classification of proteins (SCOP). Structural alignment methods like Vorolign already provide good classification results, but effectively work in a 1-Nearest Neighbor mode. Model-based (in contrast to instance-based) approaches so far have been shown to be of limited values due to small classes arising in such classification schemes. RESULTS In this article, we describe how kernels defined in terms of Vorolign scores can be used in SVM learning, and explore variants of combined instance-based and model-based learning, up to exclusively model-based learning. Our results suggest that kernels based on Vorolign scores are effective and that model-based learning can yield highly competitive classification results for the prediction of SCOP families. AVAILABILITY The code is made available at: http://wwwkramer.in.tum.de/research/applications/vorolign-kernel.
Collapse
Affiliation(s)
- Tobias Hamp
- Institut für Informatik/I12, Technische Universität München, München, Germany
| | | | | | | |
Collapse
|