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Title:Network modelling unravels mechanisms of crosstalk between ethylene and salicylate signalling in potato
Authors:ID Ramšak, Živa (Author)
ID Coll Rius, Anna (Author)
ID Stare, Tjaša (Author)
ID Tzfadia, Oren (Author)
ID Baebler, Špela (Author)
ID Van de Peer, Yves (Author)
ID Gruden, Kristina (Author)
Files:URL URL - Source URL, visit http://dx.doi.org/10.1104/pp.18.00450
 
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MD5: FDB9519CC225B5FEEFF37359AA65C00D
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo NIB - National Institute of Biology
Abstract:To develop novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modeling represents a powerful tool that can unravel properties of complex biological systems. In this study, we aimed to use network modeling to better understand immune signaling in potato (Solanum tuberosum). For this, we first built on a reliable Arabidopsis (Arabidopsis thaliana) immune signaling model, extending it with the information from diverse publicly available resources. Next, we translated the resulting prior knowledge network (20,012 nodes and 70,091 connections) to potato and superimposed it with an ensemble network inferred from time-resolved transcriptomics data for potato. We used different network modeling approaches to generate specific hypotheses of potato immune signaling mechanisms. An interesting finding was the identification of a string of molecular events illuminating the ethylene pathway modulation of the salicylic acid pathway through Nonexpressor of PR Genes1 gene expression. Functional validations confirmed this modulation, thus supporting the potential of our integrative network modeling approach for unraveling molecular mechanisms in complex systems. In addition, this approach can ultimately result in improved breeding strategies for potato and other sensitive crops.
Keywords:network modelling, potato, molecular biology
Publication status:Published
Publication version:Version of Record
Publication date:01.09.2018
Year of publishing:2018
Number of pages:str. 488-499
Numbering:Vol. 178
PID:20.500.12556/DiRROS-19986 New window
UDC:577
ISSN on article:0032-0889
DOI:10.1104/pp.18.00450 New window
COBISS.SI-ID:4778575 New window
Publication date in DiRROS:01.08.2024
Views:477
Downloads:351
Metadata:XML DC-XML DC-RDF
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RAMŠAK, Živa, COLL RIUS, Anna, STARE, Tjaša, TZFADIA, Oren, BAEBLER, Špela, VAN DE PEER, Yves and GRUDEN, Kristina, 2018, Network modelling unravels mechanisms of crosstalk between ethylene and salicylate signalling in potato. Plant physiology [online]. 2018. Vol. 178, p. 488–499. [Accessed 8 April 2025]. DOI 10.1104/pp.18.00450. Retrieved from: https://dirros.openscience.si/IzpisGradiva.php?lang=eng&id=19986
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Record is a part of a journal

Title:Plant physiology
Shortened title:Plant physiol.
Publisher:American Society of Plant Physiologists
ISSN:0032-0889
COBISS.SI-ID:5661703 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P4-0165-2015
Name:Biotehnologija in sistemska biologija rastlin
Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J4-7636-2016
Name:Prostorsko časovna analiza hipersenzitivnega odziva krompirja na krompirjev virus Y
Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J7-7303-2016
Name:Analiza heterogenih informacijskih omrežij za odkrivanje zakonitosti v znanostih o življenju
Funder:ARIS - Slovenian Research and Innovation Agency
Project number:N4-0026-2014
Name:Priprava molekularnih postopkov za sistemsko analizo imunskega odgovora krompirja

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License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

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