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Title

Fine-tuning tomato agronomic properties by computational genome redesign

AuthorsCarrera, Javier ; Fernández-del-Carmen, Asun ; Fernández-Muñoz, Rafael; Rambla, José Luis ; Pons, Clara ; Jaramillo, Alfonso; Elena, Santiago F. ; Granell, Antonio
KeywordsTranscriptional control
Arabidopsis-Thaliana
Fruit-Development
Line population
Networks
Model
Optimization
Metabolism
Selection
Behavior
Issue DateJun-2012
PublisherPublic Library of Science
CitationPlos Computational Biology 8(6): e1002528 (2012)
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.
DescriptionThis is an open-access article distributed under the terms of the Creative Commons Attribution License.
Publisher version (URL)http://dx.doi.org/10.1371/journal.pcbi.1002528
URIhttp://hdl.handle.net/10261/59206
DOI10.1371/journal.pcbi.1002528
ISSN1553-7358
Appears in Collections:(IBMCP) Artículos
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