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      eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses

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          Abstract

          eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de

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          ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data

          The Environment for Tree Exploration (ETE) is a computational framework that simplifies the reconstruction, analysis, and visualization of phylogenetic trees and multiple sequence alignments. Here, we present ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. The new features include (i) building gene-based and supermatrix-based phylogenies using a single command, (ii) testing and visualizing evolutionary models, (iii) calculating distances between trees of different size or including duplications, and (iv) providing seamless integration with the NCBI taxonomy database. ETE is freely available at http://etetoolkit.org
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            Evolution by gene duplication: an update

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              Distinguishing homologous from analogous proteins.

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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                12 November 2018
                12 November 2018
                : 47
                : Database issue , Database issue
                : D309-D314
                Affiliations
                [1 ]Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
                [2 ]Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) – Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
                [3 ]Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
                [4 ]Experimental and Clinical Research Center, a cooperation of Charité-Universitätsmedizin Berlin and Max Delbruck Center for Molecular Medicine, 13125 Berlin, Germany
                [5 ]The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N 2200, Denmark
                [6 ]Daniel K. Inouye Center for Microbial Oceanography: Research and Education (C-MORE), University of Hawaii, Honolulu, HI 96822, USA
                [7 ]Biobyte solutions GmbH, Bothestr 142, 69126 Heidelberg, Germany
                [8 ]CUBE-Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, University of Vienna, Vienna 1090, Austria
                [9 ]Germany Molecular Medicine Partnership Unit (MMPU), University Hospital Heidelberg and European Molecular Biology Laboratory, Heidelberg, Germany
                [10 ]Max Delbrück Centre for Molecular Medicine, Berlin, Germany
                [11 ]Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
                Author notes
                To whom correspondence should be addressed. Tel: +34 913364556; Email: j.huerta@ 123456upm.es . Correspondence may also be addressed to Peer Bork. Tel: +49 6221 387 85 26; Email: bork@ 123456embl.de

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                http://orcid.org/0000-0001-7734-9102
                Article
                gky1085
                10.1093/nar/gky1085
                6324079
                30418610
                e7c1e5d9-4d19-4ff5-a1e3-19109fef12d2
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 October 2018
                : 15 September 2018
                Page count
                Pages: 6
                Funding
                Funded by: Horizon 2020 10.13039/501100007601
                Award ID: 686070
                Funded by: Ramón y Cajal Programme 10.13039/100008054
                Award ID: RYC-2016-20621
                Funded by: Fondo Social Europeo 10.13039/501100004895
                Award ID: PEJ-2017-AI/TIC-7514
                Funded by: Novo Nordisk Foundation
                Award ID: NNF14CC0001
                Funded by: Bundesministerium für Bildung und Forschung 10.13039/501100002347
                Award ID: #031A537B
                Funded by: Swiss National Science Foundation 10.13039/501100001711
                Award ID: 31003A-160095
                Categories
                Database Issue

                Genetics
                Genetics

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