Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Temporal analysis of physiological, metabolite and transcriptome responses during drought identifies distinct early and late phases in Arabidopsis

ABSTRACT: Water availability is the biggest single limitation on plant productivity worldwide. In Arabidopsis, adjustments to drought stress, involving changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that integrate these complex responses we hypothesised that we needed to identify genes that govern early responses to drought. To this end, we produced a high-resolution time series transcriptomics dataset, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to the onset of drought conditions. 1825 differentially expressed genes (DEGs) were identified which showed no significant enrichment in gene ontology terms associated with dehydration responses and abscisic acid (ABA) regulation, confirming that the gene expression time series had targeted events prior to severe drought stress. Initial changes in gene expression coincided with a drop in carbon assimilation, not the later increase in foliar ABA content. Thus the early physiological and gene expression responses to drought were not driven by changes in leaf ABA content. In order to identify gene regulatory networks (GRNs) linked to early events, we used Bayesian network modelling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE 22 as key hub gene in a TF GRN. AGL22 is involved in the transition from vegetative state to flowering. Loss of AGL22 expression affected flowering time and drying rate providing a link between early changes in metabolism and the subsequent initiation of developmental responses to stress that govern plant productivity. A novel experimental design strategy (A Mead et al, in preparation), based on the principle of the âloop designâ, was developed to enable efficient extraction of information about key sample comparisons using a two-color hybridization experimental system. With 108 distinct samples (four biological replicates, at each of 13 time points in control and droughted conditions, plus a shared time zero set) to be compared, the experimental design included 216 two-color microarray slides, allowing four technical replicates of each sample to be observed. One third of the slides were devoted to assessment of changes in gene expression between time points, using a simple loop design to link samples from time points across the sampled times, directly comparing samples collected on adjacent sampling times (i.e. day 1 with day 2, day 2 with day 3, etc.). With the remaining slides, four separate loops were constructed comparing treatments, biological replicates and sampling times. All of the samples in the microarray experiment were Col-0.

ORGANISM(S): Arabidopsis thaliana

SUBMITTER: Jonathan Moore

PROVIDER: E-GEOD-65046 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Detailed information: Rice (*Oryza sativa* L. cv. Nipponbare) is a drought-susceptible species which is well suited for studies of abiotic stress response because of the comprehensive bioinformatics resource available. By withholding water from the entire root system of young rice plants, or half the root system only, it was possible to infer the relative impact of signals arriving from roots growing in wet and dry soil on the shoot proteome. The global proteome of shoots had 685 proteins in common to all three drought treatments but there were major shifts in abundance of individual proteins within 16 functional categories. The dominant changes were analyzed more deeply. First, we investigated transport and cell component organization, where some proteins were up-regulated by drought but many more down-regulated. Proteins involved in protein metabolism were up-regulated in general by drought when they were responsible for protein degradation but those involved in protein synthesis were down-regulated when water was withheld. Stress-related proteins behaved very consistently by increasing in droughted plants but notably some proteins were most abundant when roots of the same plant were growing in both wet and dry soil. This suggests that drought signals are complex interactions and not simply the additive effect of water supply to the roots. Changes in carbohydrate-processing proteins were consistent with the passive accumulation of soluble sugars in shoots under drought, with hydrolysis of sucrose and starch synthesis both enhanced. Data analysis information: The result raw files were converted to mzXML format and processed through the global proteome machine (GPM) software (version 2.1.1) of the X!Tandem algorithm (freely available at http://www.thegpm.org). The 16 gel fractions were processed serially for each experiment and the output files were generated as non-redundant, merged files with protein identifications with log (e) values less than -1, for each individual gel fraction. A protein database compiled from NCBI *O*. *sativa* with 26938 protein sequences (August 2011) was used in GPM to search the tandem mass spectra; the database also included common trypsin and human peptide contaminants. False discovery rates (FDR) were evaluated by searching against a reversed sequence database. Search parameters included MS and MS/MS tolerances of +2 Da and +0.2 Da, carbamidomethylation of cysteine as fixed modifications, oxidation of methionine as variable modifications and tolerance of two missed tryptic cleavages and K/R-P cleavages.

Project description:Genome-wide transcriptional profiling of Arabidopsis thaliana to a combination of heatwave and drought under ambient and elevated CO2. Goal of this study was elucidate the transcriptional responses to a combination of heat wave and drought, and to see how these responses are modifed under future climate (high) CO2. Climate changes increasingly threaten plant growth and productivity. Such changes are complex and involve multiple environmental factors, including rising CO2 levels and climate extreme events. As the molecular and physiological mechanisms underlying plant responses to realistic future climate extreme conditions are still poorly understood, a multiple organizational level-analysis (i.e. eco-physiological, biochemical and transcriptional) was performed, using Arabidopsis exposed to incremental heat wave and water deficit under elevated CO2.The climate extreme resulted in biomass reduction, photosynthesis inhibition, and considerable increases in stress parameters. Photosynthesis was a major target as demonstrated at the physiological and transcriptional levels. In contrast, the climate extreme treatment induced a protective effect on oxidative membrane damage, most likely as a result of strongly increased lipophilic antioxidants and membrane-protecting enzymes. Elevated CO2 significantly mitigated the negative impact of a combined heat and drought, as apparent in biomass reduction, photosynthesis inhibition, chlorophyll fluorescence decline, H2O2 production and protein oxidation. Analysis of enzymatic and molecular antioxidants revealed that the stress-mitigating CO2 effect operates through up-regulation of antioxidant defense metabolism, as well as by reduced photorespiration resulting in lowered oxidative pressure. Therefore, exposure to future climate extreme episodes will negatively impact plant growth and production, but elevated CO2 is likely to mitigate this effect. Transcriptome analysis was performed by Agilent Arabidopsis (V4) 4x44K platform which represented all known genes in the Arabidopsisgenome. Experiments were performed using a modified loop design (Knapen et al., 2009). This design consisted of total 8 arrays; sample from each treatment was labelled once and has 4 biological replicates, two of which were labelled in red and two in green

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Temporal analysis of physiological, metabolite and transcriptome responses during drought identifies distinct early and late phases in Arabidopsis

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