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GIGANTEA directly activates Flowering Locus T in Arabidopsis thaliana.

ABSTRACT: Plants perceive environmental signals such as day length and temperature to determine optimal timing for the transition from vegetative to floral stages. Arabidopsis flowers under long-day conditions through the CONSTANS (CO)-FLOWERING LOCUS T (FT) regulatory module. It is thought that the environmental cues for photoperiodic control of flowering are initially perceived in the leaves. We have previously shown that GIGANTEA (GI) regulates the timing of CO expression, together with FLAVIN-BINDING, KELCH REPEAT, F BOX protein 1. Normally, CO and FT are expressed exclusively in vascular bundles, whereas GI is expressed in various tissues. To better elucidate the role of tissue-specific expression of GI in the flowering pathway, we established transgenic lines in which GI is expressed exclusively in mesophyll, vascular bundles, epidermis, shoot apical meristem, or root. We found that GI expressed in either mesophyll or vascular bundles rescues the late-flowering phenotype of the gi-2 loss-of-function mutant under both short-day and long-day conditions. Interestingly, GI expressed in mesophyll or vascular tissues increases FT expression without up-regulating CO expression under short-day conditions. Furthermore, we examined the interaction between GI and FT repressors in mesophyll. We found that GI can bind to three FT repressors: SHORT VEGETATIVE PHASE (SVP), TEMPRANILLO (TEM)1, and TEM2. Finally, our chromatin immunoprecipitation experiments showed that GI binds to FT promoter regions that are near the SVP binding sites. Taken together, our data further elucidate the multiple roles of GI in the regulation of flowering time.

SUBMITTER: Sawa M

PROVIDER: S-EPMC3136272 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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GIGANTEA directly activates Flowering Locus T in Arabidopsis thaliana.

Sawa Mariko M Kay Steve A SA

Proceedings of the National Academy of Sciences of the United States of America 20110627 28

Plants perceive environmental signals such as day length and temperature to determine optimal timing for the transition from vegetative to floral stages. Arabidopsis flowers under long-day conditions through the CONSTANS (CO)-FLOWERING LOCUS T (FT) regulatory module. It is thought that the environmental cues for photoperiodic control of flowering are initially perceived in the leaves. We have previously shown that GIGANTEA (GI) regulates the timing of CO expression, together with FLAVIN-BINDING, ...[more]

PMID: 21709243

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Project description:Experimental studies of the flowering of Arabidopsis thaliana have shown that a large complex gene regulatory network (GRN) is responsible for its regulation. This process has been mathematically modelled with deterministic differential equations by considering the interactions between gene activators and inhibitors (Valentim et al. in PLoS ONE 10(2):e0116973, 2015; van Mourik et al. in BMC Syst Biol 4(1):1, 2010). However, due to complexity of the model, the properties of the network and the roles of the individual genes cannot be deducted from the numerical solution the published work offers. Here, we propose simplifications of the model, based on decoupling of the original GRN to motifs, described with three and two differential equations. A stable solution of the original model is sought by linearisation of the original model which contributes to further investigation of the role of the individual genes to the flowering. Furthermore, we study the role of noise by introducing and investigating two types of stochastic elements into the model. The deterministic and stochastic nonlinear dynamic models of Arabidopsis flowering time are considered by following the deterministic delayed model introduced in Valentim et al. (2015). Steady-state regimes and stability of the deterministic original model are investigated analytically and numerically. By decoupling some concentrations, the system was reduced to emphasise the role played by the transcription factor Suppressor of Overexpression of Constants1 ([Formula: see text]) and the important floral meristem identity genes, Leafy ([Formula: see text]) and Apetala1 ([Formula: see text]). Two-dimensional motifs, based on the dynamics of [Formula: see text] and [Formula: see text], are obtained from the reduced network and parameter ranges ensuring flowering are determined. Their stability analysis shows that [Formula: see text] and [Formula: see text] are regulating each other for flowering, matching experimental findings. New sufficient conditions of mean square stability in the stochastic model are obtained using a stochastic Lyapunov approach. Our numerical simulations demonstrate that the reduced models of Arabidopsis flowering time, describing specific motifs of the GRN, can capture the essential behaviour of the full system and also introduce the conditions of flowering initiation. Additionally, they show that stochastic effects can change the behaviour of the stability region through a stability switch. This study thus contributes to a better understanding of the role of [Formula: see text] and [Formula: see text] in Arabidopsis flowering.

Dataset Information

GIGANTEA directly activates Flowering Locus T in Arabidopsis thaliana.

Publications

GIGANTEA directly activates Flowering Locus T in Arabidopsis thaliana.

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