Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato. Issue 1 (22nd June 2018)
- Record Type:
- Journal Article
- Title:
- Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato. Issue 1 (22nd June 2018)
- Main Title:
- Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato
- Authors:
- Ram¡ak, Živa
Coll, Anna
Stare, Tja¡a
Tzfadia, Oren
Baebler, Špela
Van de Peer, Yves
Gruden, Kristina - Abstract:
- Abstract : Analysis of integrated prior knowledge and ensemble networks highlights a previously unidentified connection between ethylene and salicylic acid signaling modules in potato. 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 canAbstract : Analysis of integrated prior knowledge and ensemble networks highlights a previously unidentified connection between ethylene and salicylic acid signaling modules in potato. 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. … (more)
- Is Part Of:
- Plant physiology. Volume 178:Issue 1(2018)
- Journal:
- Plant physiology
- Issue:
- Volume 178:Issue 1(2018)
- Issue Display:
- Volume 178, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 178
- Issue:
- 1
- Issue Sort Value:
- 2018-0178-0001-0000
- Page Start:
- 488
- Page End:
- 499
- Publication Date:
- 2018-06-22
- Subjects:
- Plant physiology -- Periodicals
Botany -- Periodicals
Periodicals
Electronic journals
571.2 - Journal URLs:
- https://academic.oup.com/plphys/issue ↗
http://www.plantphysiol.org/ ↗
http://www.jstor.org/journals/00320889.html ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=69 ↗
http://www-us.ebsco.com/online/direct.asp?JournalID=101725 ↗
http://www.oxfordjournals.org/ ↗ - DOI:
- 10.1104/pp.18.00450 ↗
- Languages:
- English
- ISSNs:
- 0032-0889
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22237.xml