Autoregulation of nodulation (AON) is a long-distance shoot-root signalling regulatory system that regulates nodule formation 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 – 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". The 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 nodulation. It was predicted by computational complementation that the cotyledon is part of the shoot in terms of AON and produces the SDI signal, a result that was confirmed by reciprocal epicotyls-and-hypocotyl grafting in a real-plant experiment. This application demonstrates the feasibility of computational complementation and shows its usefulness for future applications where real-plant experimentation is either difficult or impossible.

This project was supported by the ARC Centre of Excellence for Integrative Legume Research, the ARC Centre for Complex Systems and the School of Information of Information Technology and Electrical Engineering based at the University of Queensland, Australia.