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Title:   Author  item
                                            DASH, SUDHANSU - Iowa State Universityitem
                                            VAN HEMERT, JOHN - Iowa State Universityitem
                                            HONG, LU - Iowa State Universityitem
                                            Wise, Rogeritem
                                            DICKERSON, JULIE - Iowa State University
  Submitted to: Nucleic Acids Research
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 10/11/2011
                                    Publication  Date: 11/13/2011
                                    Citation: Dash, S., Van Hemert, J., Hong, L., Wise, R.P., Dickerson, J.A. 2011. PLEXdb: Gene expression resources for plants and plant pathogens. Nucleic Acids Research. 40(D1):D1194-D1201.Interpretive Summary: New high-throughput sequencing technologies are transforming how scientists survey gene expression, discover new genes, and annotate genomes. However, easy-to-use tools to deploy these technologies, share data with the community following publication, or use findings to update gene annotations are limited. PLEXdb (Plant Expression Database), in partnership with community databases, is currently the only public site that supports comparisons of gene expression patterns across multiple plant species and allows individual users and/or consortia to upload their own data sets and then compare them to previously published results prior to publication, facilitating the interpretation of structure, function, and regulation of genes in economically important plants. The primary goal of the PLEXdb resource is to provide integration of data and tools that are currently accessible only from disparate resources. Without this integration, researchers, students, and teachers would have to download expression data from a repository site, check for conformity to standards that would allow cross-experiment comparisons, map the respective array (or RNA-Seq tags) to genes and those genes to genomic locations and orthologs in other species, install local software for expression data analysis, rely on disparate resources to view associated data, and develop their own methods to post-process results (e.g., obtain additional sequence data for upload into promoter motif-finding software). PLEXdb facilitates these many different tasks using a single web interface that is easily accessible to any researcher within two or three clicks from the PLEXdb front page. Most individual students, K-12 teachers, postdocs, and even faculty do not have the resources and expertise to develop their own comparative analysis pipelines, and thus rely on PLEXdb for gene expression annotation and analysis tools.
                                Technical Abstract: PLEXdb (Plant Expression Database), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function, and regulation of genes in economically important plants. A list of Gene Atlas experiments highlights datasets which give responses across different developmental stages, conditions, and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plants, including rice and Arabidopsis. MGI predicts homologies and displays gene structures and supporting information for annotated genes and full-length complementary DNAs (cDNAs). The Gene List Suite guides users through PLEXdb functions for creating, analyzing, annotating, and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher-level analyses, such Gene Ontology (GO) and pathway overrepresentation. Lastly, Gene Oscilloscope tracks gene expression signals across many different experiments. This tool is useful for identifying interesting expression patterns, such as up-regulation under diverse conditions or checking any gene’s suitability as a steady-state control.


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