Modelling the interactions for JA signalling and response

Anthony Hampstead, Siddharth Jayaraman, Michael Kreim, Julien Lavenus, Anna Lovrics, Nathan Mellor, Daniele Muraro, Katarzyna Oles, John Ward & Alessandra Devoto

The current central dogma of jasmonate signalling is based on the evidence that when the jasmonate (JA) signal emerges, the SCFCOI1 complex mediates degradation of repressors so that transcription of down-stream regulators is activated. The main aim of this work is to model the interactions between regulators from receptor activation to the ultimate gene expression in the JA pathway and their cross-talk with other hormone-dependent pathways. In a simplified view, the approaches chosen here were aimed to model two modules separately: (A) the “JA repressor complex”, which includes the JAZ transcription factors and (B) “the downstream interactions occurring during the JA response”. To model (A), Hampstead, Lovrics, Mellor, and Ward decided to use a system of ordinary differential equations (ODEs). Kreim applied to this model stochastic simulation, to take into consideration the elements of discreteness and randomness of the system. Regulatory genes can be identified based on the knowledge gained from whole genome datasets. These regulatory genes may have the capacity to control sets of genes involved in a particular pathway. Jayaraman, Muraro and Oles tested Bayesian networks and dynamical models on gene expression data obtained from Arabidopsis microarray experiments including timecourse studies following JAs treatment (selected from publicly available datasets), to construct a transcriptional network modelling (B) “the downstream interactions occurring during the JA response”. Devoto and Lavenus, provided curated sets of genes known to be induced by JAs and involved in the JAs biosynthesis and response to be used in the modelling procedure.

Proceedings of the 4th Mathematics in the Plant Sciences Study Group