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Open Access item Fine-tuning tomato agronomic properties by computational genome redesign
Elena, Santiago F.
|Keywords:||Transcriptional control, Arabidopsis-Thaliana, Fruit-Development, Line population, Networks, Model, Optimization, Metabolism, Selection, Behavior|
|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|
|Appears in Collections:||(IBMCP) Artículos|
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