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Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/59206
Title: Fine-tuning tomato agronomic properties by computational genome redesign
Authors: Carrera, Javier; Fernández-del-Carmen, Asun; Fernández-Muñoz, Rafael; Rambla, JoséLuis; Pons, Clara; Jaramillo, Alfonso; Elena, Santiago F.; Granell, Antonio
Keywords: Transcriptional control
Line population
Issue Date: Jun-2012
Publisher: Public Library of Science
Citation: Plos Computational Biology 8(6): e1002528 (2012)
Abstract: Considering 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.
Description: This 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
URI: http://hdl.handle.net/10261/59206
DOI: 10.1371/journal.pcbi.1002528
ISSN: 1553-7358
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