title: Computational analysis of flowering in pea (Pisum sativum).
abstract: During plant development, the transition from a vegetative to reproductive state is a critical event. For decades, pea (Pisum sativum) has been used as a model species to study this transition. These studies have led to a conceptual, qualitative model for the control of flower initiation, referred to as the 'classical' model. This model involves many inputs, namely photoperiod, genetic states and two mobile signals which interact to determine the first node of flowering. Here, we developed a computational model based on the hypotheses of the classical model. Accordingly, we converted qualitative hypotheses into quantitative rules. We found that new hypotheses, in addition to those already described for the classical model, were required that explicitly described the signals. In particular, we hypothesized that the key flowering gene HR interacts with the photoperiod pathway to control flowering. The computational model was tested against a wide range of biological data, including pre-existing and new experimental results presented here, and was found to be accurate. This computational model, together with ongoing experimental advances, will assist future modelling efforts to increase our understanding of flowering in pea.
authors.affiliation: INRA, Institut JP Bourgin, UR 254 Station de Génétique et d'Amélioration des Plantes, 78026 Versailles, France.
authors.forename: Bénédicte
authors.initials: B
authors.lastname: Wenden
authors.affiliation: The University of Queensland, Australian Research Council Centre of Excellence for Integrative Legume Research, St. Lucia, Qld 4072, Australia.|The University of Queensland, School of Biological Sciences, St. Lucia, Qld 4072, Australia.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Dun
authors.affiliation: The University of Queensland, Australian Research Council Centre of Excellence for Integrative Legume Research, St. Lucia, Qld 4072, Australia.|The University of Queensland, Centre for Biological Information Technology, St. Lucia, Qld 4072, Australia.
authors.forename: Jim
authors.initials: J
authors.lastname: Hanan
authors.affiliation: INRA, UMR 1091 Environnement et Grandes Cultures, 78850 Thiverval-Grignon, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Andrieu
authors.affiliation: School of Plant Science, University of Tasmania, Hobart, Tas. 7001, Australia.
authors.forename: James L
authors.initials: JL
authors.lastname: Weller
authors.affiliation: The University of Queensland, Australian Research Council Centre of Excellence for Integrative Legume Research, St. Lucia, Qld 4072, Australia.|The University of Queensland, School of Biological Sciences, St. Lucia, Qld 4072, Australia.
authors.forename: Christine A
authors.initials: CA
authors.lastname: Beveridge
authors.affiliation: INRA, Institut JP Bourgin, UR 254 Station de Génétique et d'Amélioration des Plantes, 78026 Versailles, France.
authors.forename: Catherine
authors.initials: C
authors.lastname: Rameau
mesh_terms: D000483:Alleles; D019295:Computational Biology; D035264:Flowers / Q000502:physiology*; D005838:Genotype; D008957:Models, Genetic; D018532:Pisum sativum / Q000235:genetics* / Q000502:physiology*; D017440:Photoperiod; D012639:Seeds / Q000502:physiology; D015398:Signal Transduction
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