engleski

Plant Defence Signaling Network Inference Using Knowledge - Based Perturbations and Global Gene Expression Analysis

In Arabidopsis three main signaling compounds activate the plant responses to pathogen attack: salicylic acid (SA), ethylene (ET), and jasmonic acid (JA). These substances and their different combinations can modulate the activation of groups of particular and/or similar genes. In order to determine the complexity of stimuli interpretation and to reconstitute the structure of the defense signaling network in Arabidopsis, we performed global analysis of gene expression (using microarray technology) of plants submitted to exogenous treatment with SA, ET, and JA, as well as their combinations (SA+JA, SA+ET, JA+ET, SA+JA+ET). Our concept of clustering is founded on preestablished signaling/genetic knowledge coupled with a set of highly significant perturbations allowing us to group genes in regulons with a high biological connectivity. The resulting classes determine the circuits of interpretation/combinations of cell defense signals. They have been inferred as minimal logical circuits, and represented in a Boolean formalism. In order to produce a representation of these statistical circuits inside a single graphical model, and to perform qualitative digital simulation, we developed a method for bio-digital circuits concatenation. As a first interesting result, signaling network analysis suggests that virulent pathogens block part of the defense signaling network in a semi specific manner.

plant defence signalling network

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