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      A curated list of genes that affect the plant ionome

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          Abstract

          Understanding the mechanisms underlying plants’ adaptation to their environment will require knowledge of the genes and alleles underlying elemental composition. Modern genetics is capable of quickly, and cheaply indicating which regions of DNA are associated with particular phenotypes in question, but most genes remain poorly annotated, hindering the identification of candidate genes. To help identify candidate genes underlying elemental accumulations, we have created the known ionome gene (KIG) list: a curated collection of genes experimentally shown to change uptake, accumulation, and distribution of elements. We have also created an automated computational pipeline to generate lists of KIG orthologs in other plant species using the PhytoMine database. The current version of KIG consists of 176 known genes covering 5 species, 23 elements, and their 1588 orthologs in 10 species. Analysis of the known genes demonstrated that most were identified in the model plant Arabidopsis thaliana, and that transporter coding genes and genes altering the accumulation of iron and zinc are overrepresented in the current list.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Automatic clustering of orthologs and in-paralogs from pairwise species comparisons.

            Orthologs are genes in different species that originate from a single gene in the last common ancestor of these species. Such genes have often retained identical biological roles in the present-day organisms. It is hence important to identify orthologs for transferring functional information between genes in different organisms with a high degree of reliability. For example, orthologs of human proteins are often functionally characterized in model organisms. Unfortunately, orthology analysis between human and e.g. invertebrates is often complex because of large numbers of paralogs within protein families. Paralogs that predate the species split, which we call out-paralogs, can easily be confused with true orthologs. Paralogs that arose after the species split, which we call in-paralogs, however, are bona fide orthologs by definition. Orthologs and in-paralogs are typically detected with phylogenetic methods, but these are slow and difficult to automate. Automatic clustering methods based on two-way best genome-wide matches on the other hand, have so far not separated in-paralogs from out-paralogs effectively. We present a fully automatic method for finding orthologs and in-paralogs from two species. Ortholog clusters are seeded with a two-way best pairwise match, after which an algorithm for adding in-paralogs is applied. The method bypasses multiple alignments and phylogenetic trees, which can be slow and error-prone steps in classical ortholog detection. Still, it robustly detects complex orthologous relationships and assigns confidence values for both orthologs and in-paralogs. The program, called INPARANOID, was tested on all completely sequenced eukaryotic genomes. To assess the quality of INPARANOID results, ortholog clusters were generated from a dataset of worm and mammalian transmembrane proteins, and were compared to clusters derived by manual tree-based ortholog detection methods. This study led to the identification with a high degree of confidence of over a dozen novel worm-mammalian ortholog assignments that were previously undetected because of shortcomings of phylogenetic methods.A WWW server that allows searching for orthologs between human and several fully sequenced genomes is installed at http://www.cgb.ki.se/inparanoid/. This is the first comprehensive resource with orthologs of all fully sequenced eukaryotic genomes. Programs and tables of orthology assignments are available from the same location. Copyright 2001 Academic Press.
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              The Gene Ontology (GO) database and informatics resource.

              The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.
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                Author and article information

                Contributors
                ibaxter@danforthcenter.org
                Journal
                Plant Direct
                Plant Direct
                10.1002/(ISSN)2475-4455
                PLD3
                Plant Direct
                John Wiley and Sons Inc. (Hoboken )
                2475-4455
                21 October 2020
                October 2020
                : 4
                : 10 ( doiID: 10.1002/pld3.v4.10 )
                : e00272
                Affiliations
                [ 1 ] Donald Danforth Plant Science Center Saint Louis MO USA
                [ 2 ] Departamento de Botânica Programa de Pós‐Graduação em Biologia Celular e Molecular Universidade Federal do Rio Grande do Sul Porto Alegre Brazil
                [ 3 ] University of Bayreuth Bayreuth Germany
                [ 4 ] University of Massachusetts Amherst Amherst MA USA
                [ 5 ] University of York York United Kingdom
                [ 6 ] Cornell University Ithaca NY USA
                Author notes
                [*] [* ] Correspondence

                Ivan Baxter, Donald Danforth Plant Science Center, Saint Louis, Missouri 63132, USA.

                Email: ibaxter@ 123456danforthcenter.org

                Author information
                https://orcid.org/0000-0002-2970-2175
                https://orcid.org/0000-0001-5429-3759
                https://orcid.org/0000-0001-6455-7148
                https://orcid.org/0000-0003-0570-1060
                https://orcid.org/0000-0003-4237-9920
                https://orcid.org/0000-0001-6033-6428
                https://orcid.org/0000-0002-4488-6013
                https://orcid.org/0000-0001-6680-1722
                Article
                PLD3272
                10.1002/pld3.272
                7576880
                33103043
                09a23b20-2a23-4221-8459-50362a7328f9
                © 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 April 2020
                : 26 August 2020
                : 28 August 2020
                Page count
                Figures: 4, Tables: 2, Pages: 15, Words: 13396
                Funding
                Funded by: Donald Danforth Plant Science Center
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for granting a fellowship to FKR
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                October 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.3 mode:remove_FC converted:21.10.2020

                curated,ionomics,mineral nutrition
                curated, ionomics, mineral nutrition

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