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Published on: September 17, 2016
CAST-R: An application to visualize circadian and heat stress-responsive genes in plants
Titouan Bonnot1, Morgane B Gillard1, Dawn H Nagel1
1Department of Botany and Plant Sciences, University of California, Riverside, California, USA.
Abstract:
The circadian clock helps organisms to anticipate and coordinate gene regulatory responses to changes in environmental stimuli. Under stresses, both time of day and the circadian clock closely control the magnitude of plant responses. The identification of clock-regulated genes is, therefore, important when studying the influence of environmental factors. Here, we present CAST-R (Circadian And heat STress-Responsive), a "Shiny" application that allows users to identify and visualize circadian and heat stress-responsive genes in plants. More specifically, users can generate and export profiles and heatmaps representing transcript abundance of a single or of multiple Arabidopsis (Arabidopsis thaliana) genes over a 24-h time course, in response to heat stress and during recovery following the stress. The application also takes advantage of published Arabidopsis chromatin immunoprecipitation-sequencing datasets to visualize the connections between clock proteins and their targets in an interactive network. In addition, CAST-R offers the possibility to perform phase (i.e. timing of expression) enrichment analyses for rhythmic datasets from any species, within and beyond plants. This functionality combines statistical analyses and graphical representations to identify significantly over- and underrepresented phases within a subset of genes. Lastly, profiles of transcript abundance can be visualized from multiple circadian datasets generated in Arabidopsis, Brassica rapa, barley (Hordeum vulgare), and rice (Oryza sativa). In summary, CAST-R is a user-friendly interface that allows the rapid identification of circadian and stress-responsive genes through multiple modules of visualization. We anticipate that this tool will make it easier for users to obtain temporal and dynamic information on genes of interest that links plant responses to environmental signals.
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