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      Transcriptome Profiling of Citrus Fruit Response to Huanglongbing Disease

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          Abstract

          Huanglongbing (HLB) or “citrus greening” is the most destructive citrus disease worldwide. In this work, we studied host responses of citrus to infection with Candidatus Liberibacter asiaticus (CaLas) using next-generation sequencing technologies. A deep mRNA profile was obtained from peel of healthy and HLB-affected fruit. It was followed by pathway and protein-protein network analysis and quantitative real time PCR analysis of highly regulated genes. We identified differentially regulated pathways and constructed networks that provide a deep insight into the metabolism of affected fruit. Data mining revealed that HLB enhanced transcription of genes involved in the light reactions of photosynthesis and in ATP synthesis. Activation of protein degradation and misfolding processes were observed at the transcriptomic level. Transcripts for heat shock proteins were down-regulated at all disease stages, resulting in further protein misfolding. HLB strongly affected pathways involved in source-sink communication, including sucrose and starch metabolism and hormone synthesis and signaling. Transcription of several genes involved in the synthesis and signal transduction of cytokinins and gibberellins was repressed while that of genes involved in ethylene pathways was induced. CaLas infection triggered a response via both the salicylic acid and jasmonic acid pathways and increased the transcript abundance of several members of the WRKY family of transcription factors. Findings focused on the fruit provide valuable insight to understanding the mechanisms of the HLB-induced fruit disorder and eventually developing methods based on small molecule applications to mitigate its devastating effects on fruit production.

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          Most cited references77

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          GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox.

          High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.
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            Control of plant development and gene expression by sugar signaling.

            Coordination of development with the availability of nutrients, such as soluble sugars, may help ensure an adequate supply of building materials and energy with which to carry out specific developmental programs. For example, in-vivo and in-vitro experiments suggest that increasing sugar levels delay seed germination and stimulate the induction of flowering and senescence in at least some plant species. Higher sugar concentrations can also increase the number of tubers formed by potatoes and can stimulate the formation of adventitious roots by Arabidopsis. New insights into the mechanisms by which sugar-response pathways interact with other response pathways have been provided by microarray experiments examining sugar-regulated gene expression under different light and nitrogen conditions.
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              PageMan: An interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments

              Background Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Results Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs. PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis. PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at . Conclusion PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                31 May 2012
                : 7
                : 5
                : e38039
                Affiliations
                [1 ]Plant Sciences Department, University of California Davis, Davis, California, United States of America
                [2 ]U.S. Horticultural Research Laboratory, United States Department of Agriculture, Agricultural Research Service, Fort Pierce, Florida, United States of America
                [3 ]Mechanical and Aerospace Engineering Department, University of California Davis, Davis, California, United States of America
                [4 ]Center for Computational Science and Engineering, University of California Davis, Davis, California, United States of America
                [5 ]Bioinformatics Core, Genome Center, University of California Davis, Davis, California, United States of America
                [6 ]Dipartimento di Sistemi Agro-Ambientali, Università degli Studi di Palermo, Viale delle Scienze, Palermo, Italy
                Naval Research Laboratory, United States of America
                Author notes

                Conceived and designed the experiments: AMD FM KDB. Performed the experiments: FM SLU UA MLP. Analyzed the data: FM RLR MB VB JF EL WZ DL RD CED AMD. Contributed reagents/materials/analysis tools: FM SLU UA MLP KDB AMD. Wrote the paper: FM AMD. Conceived and designed the experiments: AMD FM KDB. Performed the experiments: FM SLU UA MLP. Analyzed the data: FM RLR MB VB JF EL WZ DL RD CED AMD. Contributed reagents/materials/analysis tools: FM SLU UA MLP KDB AMD. Wrote the paper: FM AMD.

                Article
                PONE-D-10-05860
                10.1371/journal.pone.0038039
                3364978
                22675433
                c67fda73-26d4-46f2-b455-3c49ff38cd41
                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
                History
                : 1 December 2010
                : 30 April 2012
                Page count
                Pages: 16
                Categories
                Research Article
                Agriculture
                Biology
                Genetics
                Gene Expression
                RNA interference
                Molecular Genetics
                Gene Identification and Analysis
                Gene Regulation
                Gene Function
                Gene Networks
                Plant Science
                Plant Pathology
                Plant Pathogens
                Plant Pests
                Plants
                Fruits
                Plant Genomics
                Plant Growth and Development

                Uncategorized
                Uncategorized

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