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Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato

(2018) PLANT PHYSIOLOGY. 178(1). p.488-499
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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 Genesi 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
TRANSCRIPTION COACTIVATOR NPR1, PLANT IMMUNITY, ARABIDOPSIS-THALIANA, BIOLOGICAL NETWORKS, GENE-EXPRESSION, DEFENSE, RESPONSES, ACID, VISUALIZATION, RESISTANCE

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MLA
Ramsak, Ziva, Anna Coll, Tjasa Stare, et al. “Network Modeling Unravels Mechanisms of Crosstalk Between Ethylene and Salicylate Signaling in Potato.” PLANT PHYSIOLOGY 178.1 (2018): 488–499. Print.
APA
Ramsak, Z., Coll, A., Stare, T., Tzfadia, O., Baebler, S., Van de Peer, Y., & Gruden, K. (2018). Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato. PLANT PHYSIOLOGY, 178(1), 488–499.
Chicago author-date
Ramsak, Ziva, Anna Coll, Tjasa Stare, Oren Tzfadia, Spela Baebler, Yves Van de Peer, and Kristina Gruden. 2018. “Network Modeling Unravels Mechanisms of Crosstalk Between Ethylene and Salicylate Signaling in Potato.” Plant Physiology 178 (1): 488–499.
Chicago author-date (all authors)
Ramsak, Ziva, Anna Coll, Tjasa Stare, Oren Tzfadia, Spela Baebler, Yves Van de Peer, and Kristina Gruden. 2018. “Network Modeling Unravels Mechanisms of Crosstalk Between Ethylene and Salicylate Signaling in Potato.” Plant Physiology 178 (1): 488–499.
Vancouver
1.
Ramsak Z, Coll A, Stare T, Tzfadia O, Baebler S, Van de Peer Y, et al. Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato. PLANT PHYSIOLOGY. 2018;178(1):488–99.
IEEE
[1]
Z. Ramsak et al., “Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato,” PLANT PHYSIOLOGY, vol. 178, no. 1, pp. 488–499, 2018.
@article{8575750,
  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 Genesi 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.},
  author       = {Ramsak, Ziva and Coll, Anna and Stare, Tjasa and Tzfadia, Oren and Baebler, Spela and Van de Peer, Yves and Gruden, Kristina},
  issn         = {0032-0889},
  journal      = {PLANT PHYSIOLOGY},
  keywords     = {TRANSCRIPTION COACTIVATOR NPR1,PLANT IMMUNITY,ARABIDOPSIS-THALIANA,BIOLOGICAL NETWORKS,GENE-EXPRESSION,DEFENSE,RESPONSES,ACID,VISUALIZATION,RESISTANCE},
  language     = {eng},
  number       = {1},
  pages        = {488--499},
  title        = {Network modeling unravels mechanisms of crosstalk between ethylene and salicylate signaling in potato},
  url          = {http://dx.doi.org/10.1104/pp.18.00450},
  volume       = {178},
  year         = {2018},
}

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