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High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.
Seaver, Samuel M D; Gerdes, Svetlana; Frelin, Océane; Lerma-Ortiz, Claudia; Bradbury, Louis M T; Zallot, Rémi; Hasnain, Ghulam; Niehaus, Thomas D; El Yacoubi, Basma; Pasternak, Shiran; Olson, Robert; Pusch, Gordon; Overbeek, Ross; Stevens, Rick; de Crécy-Lagard, Valérie; Ware, Doreen; Hanson, Andrew D; Henry, Christopher S.
Afiliación
  • Seaver SM; Mathematics and Computer Science Division andComputation Institute, The University of Chicago, Chicago, IL 60637;
  • Gerdes S; Mathematics and Computer Science Division andFellowship for Interpretation of Genomes, Burr Ridge, IL 60527;
  • Frelin O; Horticultural Sciences Department and.
  • Lerma-Ortiz C; Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611;
  • Bradbury LM; Horticultural Sciences Department and.
  • Zallot R; Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611;
  • Hasnain G; Horticultural Sciences Department and.
  • Niehaus TD; Horticultural Sciences Department and.
  • El Yacoubi B; Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611;
  • Pasternak S; Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724; and.
  • Olson R; Mathematics and Computer Science Division andComputation Institute, The University of Chicago, Chicago, IL 60637;
  • Pusch G; Computation Institute, The University of Chicago, Chicago, IL 60637;Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527;Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60439;
  • Overbeek R; Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527;
  • Stevens R; Computation Institute, The University of Chicago, Chicago, IL 60637;Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60439;
  • de Crécy-Lagard V; Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611;
  • Ware D; Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724; andUS Department of Agriculture-Agricultural Research Service North Atlantic Area Plant, Soil and Nutrition Laboratory Research Unit, Cornell University, Ithaca, NY 14853.
  • Hanson AD; Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527;
  • Henry CS; Mathematics and Computer Science Division andComputation Institute, The University of Chicago, Chicago, IL 60637; chenry@mcs.anl.gov.
Proc Natl Acad Sci U S A ; 111(26): 9645-50, 2014 Jul 01.
Article en En | MEDLINE | ID: mdl-24927599
ABSTRACT
The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Plantas / Programas Informáticos / Genoma de Planta / Biología Computacional / Bases de Datos Genéticas / Secuenciación de Nucleótidos de Alto Rendimiento / Anotación de Secuencia Molecular Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2014 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Plantas / Programas Informáticos / Genoma de Planta / Biología Computacional / Bases de Datos Genéticas / Secuenciación de Nucleótidos de Alto Rendimiento / Anotación de Secuencia Molecular Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2014 Tipo del documento: Article