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Potent induction of Arabidopsis thaliana flowering by elevated growth temperature.

ABSTRACT: The transition to flowering is an important event in the plant life cycle and is modulated by several environmental factors including photoperiod, light quality, vernalization, and growth temperature, as well as biotic and abiotic stresses. In contrast to light and vernalization, little is known about the pathways that mediate the responses to other environmental variables. A mild increase in growth temperature, from 23 degrees C to 27 degrees C, is equally efficient in inducing flowering of Arabidopsis plants grown in 8-h short days as is transfer to 16-h long days. There is extensive natural variation in this response, and we identify strains with contrasting thermal reaction norms. Exploiting this natural variation, we show that FLOWERING LOCUS C potently suppresses thermal induction, and that the closely related floral repressor FLOWERING LOCUS M is a major-effect quantitative trait locus modulating thermosensitivity. Thermal induction does not require the photoperiod effector CONSTANS, acts upstream of the floral integrator FLOWERING LOCUS T, and depends on the hormone gibberellin. Analysis of mutants defective in salicylic acid biosynthesis suggests that thermal induction is independent of previously identified stress-signaling pathways. Microarray analyses confirm that the genomic responses to floral induction by photoperiod and temperature differ. Furthermore, we report that gene products that participate in RNA splicing are specifically affected by thermal induction. Above a critical threshold, even small changes in temperature can act as cues for the induction of flowering. This response has a genetic basis that is distinct from the known genetic pathways of floral transition, and appears to correlate with changes in RNA processing.

SUBMITTER: Balasubramanian S

PROVIDER: S-EPMC1487179 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe transition from vegetative to reproductive stages marks a major milestone in plant development. It is clear that global change factors (e.g., increasing [CO(2)] and temperature) have already had and will continue to have a large impact on plant flowering times in the future. Increasing atmospheric [CO(2)] has recently been shown to affect flowering time, and may produce even greater responses than increasing temperature. Much is known about the genes influencing flowering time, although their relevance to changing [CO(2)] is not well understood. Thus, we present the first study to identify QTL (Quantitative Trait Loci) that affect flowering time at elevated [CO(2)] in Arabidopsis thaliana.Methodology/principal findingsWe developed our mapping population by crossing a genotype previously selected for high fitness at elevated [CO(2)] (SG, Selection Genotype) to a Cape Verde genotype (Cvi-0). SG exhibits delayed flowering at elevated [CO(2)], whereas Cvi-0 is non-responsive to elevated [CO(2)] for flowering time. We mapped one major QTL to the upper portion of chromosome 1 that explains 1/3 of the difference in flowering time between current and elevated [CO(2)] between the SG and Cvi-0 parents. This QTL also alters the stage at which flowering occurs, as determined from higher rosette leaf number at flowering in RILs (Recombinant Inbred Lines) harboring the SG allele. A follow-up study using Arabidopsis mutants for flowering time genes within the significant QTL suggests MOTHER OF FT AND TFL1 (MFT) as a potential candidate gene for altered flowering time at elevated [CO(2)].Conclusion/significanceThis work sheds light on the underlying genetic architecture that controls flowering time at elevated [CO(2)]. Prior to this work, very little to nothing was known about these mechanisms at the genomic level. Such a broader understanding will be key for better predicting shifts in plant phenology and for developing successful crops for future environments.

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.

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Potent induction of Arabidopsis thaliana flowering by elevated growth temperature.

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