Dataset Information

Over-Expression of GmGIa-Regulated Soybean miR172a Confers Early Flowering in Transgenic Arabidopsis thaliana.

ABSTRACT: Flowering is a pivotal event in the life cycle of plants. miR172 has been widely confirmed to play critical roles in flowering time control by regulating its target gene expression in Arabidopsis. However, the role of its counterpart in soybean remains largely unclear. In the present study, we found that the gma-miR172a was regulated by a GIGANTEA ortholog, GmGIa, in soybean through miRNA metabolism. The expression analysis revealed that gma-miR172a has a pattern of diurnal rhythm expression and its abundance increased rapidly as plants grew until the initiation of flowering phase in soybean. One target gene of gma-miR172a, Glyma03g33470, was predicted and verified using a modified RLM 5'-RACE (RNA ligase-mediated rapid amplification of 5' cDNA ends) assay. Overexpression of gma-miR172a exhibited an early flowering phenotype and the expression of FT, AP1 and LFY were simultaneously increased in gma-miR172a-transgenic Arabidopsis plants, suggesting that the early flowering phenotype was associated with up-regulation of these genes. The overexpression of the gma-miR172a-resistant version of Glyma03g33470 weakened early flowering phenotype in the toe1 mutant of Arabidopsis. Taken together, our results suggested that gma-miR172a played an important role in GmGIa-mediated flowering by repressing Glyma03g33470, which in turn increased the expression of FT, AP1 and LFY to promote flowering in soybean.

SUBMITTER: Wang T

PROVIDER: S-EPMC4881471 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Over-Expression of GmGIa-Regulated Soybean miR172a Confers Early Flowering in Transgenic Arabidopsis thaliana.

Wang Tao T Sun Ming-Yang MY Wang Xue-Song XS Li Wen-Bin WB Li Yong-Guang YG

International journal of molecular sciences 20160429 5

Flowering is a pivotal event in the life cycle of plants. miR172 has been widely confirmed to play critical roles in flowering time control by regulating its target gene expression in Arabidopsis. However, the role of its counterpart in soybean remains largely unclear. In the present study, we found that the gma-miR172a was regulated by a GIGANTEA ortholog, GmGIa, in soybean through miRNA metabolism. The expression analysis revealed that gma-miR172a has a pattern of diurnal rhythm expression and ...[more]

PMID: 27136537

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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

Over-Expression of GmGIa-Regulated Soybean miR172a Confers Early Flowering in Transgenic Arabidopsis thaliana.

Publications

Over-Expression of GmGIa-Regulated Soybean miR172a Confers Early Flowering in Transgenic Arabidopsis thaliana.

Similar Datasets

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