Computational complementation: a modelling approach to study signalling mechanisms during legume autoregulation of nodulation

Han, Liqi, Hanan, Jim and Gresshoff, Peter M. (2010) Computational complementation: a modelling approach to study signalling mechanisms during legume autoregulation of nodulation. PloS Computational Biology, 6 2: e1000685-1-e1000685-8. doi:10.1371/journal.pcbi.1000685


Author Han, Liqi
Hanan, Jim
Gresshoff, Peter M.
Title Computational complementation: a modelling approach to study signalling mechanisms during legume autoregulation of nodulation
Journal name PloS Computational Biology   Check publisher's open access policy
ISSN 1553-7358
1553-734X
Publication date 2010-02-26
Year available 2010
Sub-type Article (original research)
DOI 10.1371/journal.pcbi.1000685
Open Access Status DOI
Volume 6
Issue 2
Start page e1000685-1
End page e1000685-8
Total pages 8
Editor Philip E.. Bourne
Place of publication San Francisco, CA
Publisher Public Library of Science
Language eng
Subject 1105 Ecology, Evolution, Behavior and Systematics
2611 Modelling and Simulation
2303 Ecology
1312 Molecular Biology
1311 Genetics
2804 Cellular and Molecular Neuroscience
1703 Computational Theory and Mathematics
Abstract Autoregulation of nodulation (AON) is a long-distance signalling regulatory system maintaining the balance of symbiotic nodulation in legume plants. However, the intricacy of internal signalling and absence of flux and biochemical data, are a bottleneck for investigation of AON. To address this, a new computational modelling approach called ‘‘Computational Complementation’’ has been developed. The main idea is to use functional-structural modelling to complement the deficiency of an empirical model of a loss-of-function (non-AON) mutant with hypothetical AON mechanisms. If computational complementation demonstrates a phenotype similar to the wild-type plant, the signalling hypothesis would be suggested as ‘‘reasonable’’. Our initial case for application of this approach was to test whether or not wild-type soybean cotyledons provide the shoot-derived inhibitor (SDI) to regulate nodule progression. We predicted by computational complementation that the cotyledon is part of the shoot in terms of AON and that it produces the SDI signal, a result that was confirmed by reciprocal epicotyl-and-hypocotyl grafting in a real-plant experiment. This application demonstrates the feasibility of computational complementation and shows its usefulness for applications where real-plant experimentation is either difficult or impossible.
Keyword In-silico Plant
Systems biology
Receptor Kinase
Glycine max
Nodule number
Root
Architecture
Auxin
Transport
Distance
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Sun, 21 Mar 2010, 10:01:18 EST