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dc.contributor.authorCarrera, Javier-
dc.contributor.authorFernández-del-Carmen, Asun-
dc.contributor.authorFernández-Muñoz, Rafael-
dc.contributor.authorRambla, José Luis-
dc.contributor.authorPons, Clara-
dc.contributor.authorJaramillo, Alfonso-
dc.contributor.authorElena, Santiago F.-
dc.contributor.authorGranell, Antonio-
dc.date.accessioned2012-10-30T12:15:29Z-
dc.date.available2012-10-30T12:15:29Z-
dc.date.issued2012-06-
dc.identifier.citationPlos Computational Biology 8(6): e1002528 (2012)es_ES
dc.identifier.issn1553-7358-
dc.identifier.urihttp://hdl.handle.net/10261/59206-
dc.descriptionThis is an open-access article distributed under the terms of the Creative Commons Attribution License.-
dc.description.abstractConsidering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites.es_ES
dc.description.sponsorshipThis work was supported by grant TIN2006-12860 from the Spanish Ministerio de Ciencia e Innovación, the Strutctural Funds of the European Regional Development Fund (ERDF) FP7-ICT-043338 (BACTOCOM), the FP7-ICT-265505 (CADMAD), the ATIGE-Genopole, and the Fondation por la Recherche Medicale grants to AJ, and by grant BFU2009-06993 from the Spanish Ministerio de Ciencia e Innovación to SFE and EPSOL, Fundación Genoma España and EUSOL european Comission Contract number: FOOD-CT-2006-016214, to A.G.es_ES
dc.language.isoenges_ES
dc.publisherPublic Library of Sciencees_ES
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/265505-
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/043338-
dc.relation.isversionofPublisher's version-
dc.rightsopenAccesses_ES
dc.subjectTranscriptional controles_ES
dc.subjectArabidopsis thalianaes_ES
dc.subjectFruit-Developmentes_ES
dc.subjectLine populationes_ES
dc.subjectNetworkses_ES
dc.subjectModeles_ES
dc.subjectOptimizationes_ES
dc.subjectMetabolismes_ES
dc.subjectSelectiones_ES
dc.subjectBehavioures_ES
dc.titleFine-tuning tomato agronomic properties by computational genome redesignes_ES
dc.typeartículoes_ES
dc.identifier.doi10.1371/journal.pcbi.1002528-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1371/journal.pcbi.1002528es_ES
dc.identifier.pmid22685389-
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.openairetypeartículo-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
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