Original Research ARTICLE
Dynamical Modeling of the Core Gene Network Controlling Flowering Suggests Cumulative Activation from the FLOWERING LOCUS T Gene Homologs in Chickpea
- 1Ioffe Institute (RAS), Russia
- 2Saint Petersburg State Polytechnic University, Russia
- 3University of Southern California, United States
Initiation of flowering moves plants from vegetative to reproductive development. The time when this transition happens (flowering time), an important indicator of productivity, depends on both endogenous and environmental factors. The core genetic regulatory network canalizing the flowering signals to the decision to flower has been studied extensively in the model plant Arabidopsis thaliana and has been shown to preserve its main regulatory blocks in other species. It integrates activation from the FLOWERING LOCUS T (FT) gene or its homologs to the flowering decision expressed as high expression of the meristem identity genes, including AP1. We elaborated a dynamical model of this flowering gene regulatory network and applied it to the previously published expression data from two cultivars of domesticated chickpea (Cicer arietinum), obtained for two photoperiod durations. Due to a large number of free parameters in the model, we used an ensemble approach analyzing the model solutions at many parameter sets that provide equally good fit to data. Testing several alternative hypotheses about regulatory roles of the five FT homologs present in chickpea revealed no preference in segregating individual FT copies as singled-out activators with their own regulatory parameters, thus favoring the hypothesis that the five genes possess similar regulatory properties and provide cumulative activation in the network. The analysis reveals that different levels of activation from AP1 can explain a small difference observed in the expression of the two homologs of the repressor gene TFL1. Finally, the model predicts highly reduced activation between LFY and AP1, thus suggesting that this regulatory block is not conserved in chickpea and needs other mechanisms. Overall, this study provides the first attempt to quantitatively test the flowering time gene network in chickpea based on data-driven modeling.
Keywords: chickpea, flowering time, FT genes, ICCV 96029, CDC Frontier, Dynamical model
Received: 25 Aug 2018;
Accepted: 26 Oct 2018.
Edited by:Yuriy L. Orlov, Institute of Cytology and Genetics, Russian Academy of Sciences, Russia
Reviewed by:Inna N. Lavrik, Medizinische Fakultät, Universitätsklinikum Magdeburg, Germany
Filippo Geraci, Italian National Research Council, Italy
Copyright: © 2018 Gursky, Kozlov, Nuzhdin and Samsonova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Maria G. Samsonova, Saint Petersburg State Polytechnic University, Saint Petersburg, 195251, Saint Petersburg, Russia, firstname.lastname@example.org