RT Journal Article
SR Electronic
T1 Network modelling unravels mechanisms of crosstalk between ethylene and salicylate signalling in potato
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 214940
DO 10.1101/214940
A1 Živa Ramšak
A1 Anna Coll
A1 Tjaša Stare
A1 Oren Tzfadia
A1 Špela Baebler
A1 Špela Baebler
A1 Yves Van de Peer
A1 Kristina Gruden
YR 2017
UL http://biorxiv.org/content/early/2017/11/06/214940.abstract
AB To provide means for novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modelling represents a powerful tool that can unravel properties of complex biological systems. Here, we build on a reliable Arabidopsis (Arabidopsis thaliana L.) immune signalling model, extending it with the information from diverse publically available resources. The resulting prior knowledge network (20,012 nodes, 70,091 connections) was then translated to potato (Solanum tuberosum L.) and superimposed with an ensemble network inferred from potato time-resolved transcriptomics data. We used different network modelling approaches to generate specific hypotheses of potato immune signalling mechanisms. An interesting finding was the identification of a string of molecular events, illuminating the ethylene pathway modulation of the salicylic acid pathway through NPR1 gene expression. Functional validations confirmed this modulation, thus confirming the potential of our integrative network modelling approach for unravelling molecular mechanisms in complex systems.One-sentence summary Analysis of integrated prior knowledge and ensemble networks highlights a novel connection between ethylene and salicylic acid signalling modules in potato.