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Modelling water use efficiency in a dynamic environment: An example using Arabidopsis thaliana.

ABSTRACT: Intrinsic water use efficiency (Wi), the ratio of net CO2 assimilation (A) over stomatal conductance to water vapour (gs), is a complex trait used to assess plant performance. Improving Wi could lead in theory to higher productivity or reduced water usage by the plant, but the physiological traits for improvement and their combined effects on Wi have not been clearly identified. Under fluctuating light intensity, the temporal response of gs is an order of magnitude slower than A, which results in rapid variations in Wi. Compared to traditional approaches, our new model scales stoma behaviour at the leaf level to predict gs and A during a diurnal period, reproducing natural fluctuations of light intensity, in order to dissect Wi into traits of interest. The results confirmed the importance of stomatal density and photosynthetic capacity on Wi but also revealed the importance of incomplete stomatal closure under dark conditions as well as stomatal sensitivity to light intensity. The observed continuous decrease of A and gs over the diurnal period was successfully described by negative feedback of the accumulation of photosynthetic products. Investigation into the impact of leaf anatomy on temporal responses of A, gs and Wi revealed that a high density of stomata produces the most rapid response of gs but may result in lower Wi.

SUBMITTER: Vialet-Chabrand S

PROVIDER: S-EPMC5038844 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Modelling water use efficiency in a dynamic environment: An example using Arabidopsis thaliana.

Vialet-Chabrand S S Matthews J S A JSA Brendel O O Blatt M R MR Wang Y Y Hills A A Griffiths H H Rogers S S Lawson T T

Plant science : an international journal of experimental plant biology 20160622

Intrinsic water use efficiency (Wi), the ratio of net CO2 assimilation (A) over stomatal conductance to water vapour (gs), is a complex trait used to assess plant performance. Improving Wi could lead in theory to higher productivity or reduced water usage by the plant, but the physiological traits for improvement and their combined effects on Wi have not been clearly identified. Under fluctuating light intensity, the temporal response of gs is an order of magnitude slower than A, which results i ...[more]

PMID: 27593464

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Project description:Wheat production under rainfed conditions is restrained by water scarcity, elevated temperatures, and lower nutrient uptake due to possible drought. The complex genotype, management, and environment (G × M × E) interactions can obstruct the selection of suitable high yielding wheat cultivars and nitrogen (N) management practices prerequisite to ensure food security and environmental sustainability in arid regions. The agronomic traits, water use efficiency (WUE), and N use efficiencies were evaluated under favorable and unfavorable weather conditions to explore the impacts of G × M × E on wheat growth and productivity. The multi-N rate (0, 70, 140, 210, and 280 kg N ha-1) field experiment was conducted under two weather conditions (favorable and unfavorable) using three wheat cultivars (AUR-809, CHK-50, and FSD-2008) in the Pothowar region of Pakistan. The experiments were laid out in randomized complete block design (RCBD), with split plot arrangements having cultivars in the main plot and N levels in the subplot. The results revealed a significant decrease in aboveground biomass, grain yield, crop N-uptake, WUE, and N use efficiency (NUE) by 15%, 22%, 21%, 18%, and 8%, respectively in the unfavorable growing season (2014-2015) as compared to favorable growing season (2013-2014) as a consequence of less rainfall and heat stress during the vegetative and reproductive growth phases, respectively. FSD-2008 showed a significantly higher aboveground biomass, grain yield, crop N-uptake, WUE, and NUE as compared to other wheat cultivars in both years. Besides, N140 appeared as the most suitable dose for wheat cultivars during the favorable growing season. However, any further increase in N application rates beyond N140 showed a non-significant effect on yield and yield components. Conversely, the wheat yield increased significantly up to 74% from N0 to N70 during the unfavorable growing season, and there was no substantial difference between N70-N280. The findings provide opportunities for maximizing yield while avoiding excessive N loss by selecting suitable cultivars and N application rates for rainfed areas of Pothowar Plateau by using meteorological forecasting, amount of summer rainfall, and initial soil moisture content.

Project description:BACKGROUND: To understand transcriptional regulatory networks (TRNs), especially the coordinated dynamic regulation between transcription factors (TFs) and their corresponding target genes during development, computational approaches would represent significant advances in the genome-wide expression analysis. The major challenges for the experiments include monitoring the time-specific TFs' activities and identifying the dynamic regulatory relationships between TFs and their target genes, both of which are currently not yet available at the large scale. However, various methods have been proposed to computationally estimate those activities and regulations. During the past decade, significant progresses have been made towards understanding pollen development at each development stage under the molecular level, yet the regulatory mechanisms that control the dynamic pollen development processes remain largely unknown. Here, we adopt Networks Component Analysis (NCA) to identify TF activities over time course, and infer their regulatory relationships based on the coexpression of TFs and their target genes during pollen development. RESULTS: We carried out meta-analysis by integrating several sets of gene expression data related to Arabidopsis thaliana pollen development (stages range from UNM, BCP, TCP, HP to 0.5 hr pollen tube and 4 hr pollen tube). We constructed a regulatory network, including 19 TFs, 101 target genes and 319 regulatory interactions. The computationally estimated TF activities were well correlated to their coordinated genes' expressions during the development process. We clustered the expression of their target genes in the context of regulatory influences, and inferred new regulatory relationships between those TFs and their target genes, such as transcription factor WRKY34, which was identified that specifically expressed in pollen, and regulated several new target genes. Our finding facilitates the interpretation of the expression patterns with more biological relevancy, since the clusters corresponding to the activity of specific TF or the combination of TFs suggest the coordinated regulation of TFs to their target genes. CONCLUSIONS: Through integrating different resources, we constructed a dynamic regulatory network of Arabidopsis thaliana during pollen development with gene coexpression and NCA. The network illustrated the relationships between the TFs' activities and their target genes' expression, as well as the interactions between TFs, which provide new insight into the molecular mechanisms that control the pollen development.

Dataset Information

Modelling water use efficiency in a dynamic environment: An example using Arabidopsis thaliana.

Publications

Modelling water use efficiency in a dynamic environment: An example using Arabidopsis thaliana.

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