Dataset Information

PRESTA: associating promoter sequences with information on gene expression.

ABSTRACT: BACKGROUND:Large sets of well-characterized promoter sequences are required to facilitate the understanding of promoter architecture. The major sequence databases are a prospective source of upstream regulatory regions, but suffer from inaccurate annotation. The software tool PRESTA (PRomoter EST Association) presented in this study is designed for efficient recovery of characterized and partially verified promoters from GenBank and EMBL libraries. RESULTS:The PRESTA algorithm examines the putative GenBank/EMBL promoters and automatically removes most of the poorly annotated entries. The remaining records are connected to expressed sequence tags (ESTs) through a high-stringency BLAST search. The frequency and source of recovered ESTs provide an estimate of the activity and expression pattern of the promoter, and the ESTs' 5' ends assist in transcription start-site verification. The PRESTA database provides easy access to non-redundant upstream regulatory regions recently extracted by the PRESTA algorithm. The current size of this resource is 552 human and 241 mouse promoters. Surprisingly, no overlap between the PRESTA database and the Eukaryotic Promoter Database (EPD) was detected by sequence comparison. CONCLUSIONS:The PRESTA algorithm demonstrates the principle of promoter verification by mapping EST 5' ends. The publicly available PRESTA database collects hundreds of characterized and partially verified promoter sequences and is complementary to other promoter databases.

SUBMITTER: Mach V

PROVIDER: S-EPMC126875 | biostudies-literature | 2002 Aug

REPOSITORIES: biostudies-literature

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PRESTA: associating promoter sequences with information on gene expression.

Mach Václav V

Genome biology 20020821 9

<h4>Background</h4>Large sets of well-characterized promoter sequences are required to facilitate the understanding of promoter architecture. The major sequence databases are a prospective source of upstream regulatory regions, but suffer from inaccurate annotation. The software tool PRESTA (PRomoter EST Association) presented in this study is designed for efficient recovery of characterized and partially verified promoters from GenBank and EMBL libraries.<h4>Results</h4>The PRESTA algorithm exa ...[more]

PMID: 12225589

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Project description:BackgroundUncovering the key sequence elements in gene promoters that regulate the expression of plant genomes is a huge task that will require a series of complementary methods for prediction, substantial innovations in experimental validation and a much greater understanding of the role of combinatorial control in the regulation of plant gene expression.ResultsTo add to this larger process and to provide alternatives to existing prediction methods, we have developed several tools in the statistical package R. ModuleFinder identifies sets of genes and treatments that we have found to form valuable sets for analysis of the mechanisms underlying gene co-expression. CoReg then links the hierarchical clustering of these co-expressed sets with frequency tables of promoter elements. These promoter elements can be drawn from known elements or all possible combinations of nucleotides in an element of various lengths. These sets of promoter elements represent putative cis-acting regulatory elements common to sets of co-expressed genes and can be prioritised for experimental testing. We have used these new tools to analyze the response of transcripts for nuclear genes encoding mitochondrial proteins in Arabidopsis to a range of chemical stresses. ModuleFinder provided a subset of co-expressed gene modules that are more logically related to biological functions than did subsets derived from traditional hierarchical clustering techniques. Importantly ModuleFinder linked responses in transcripts for electron transport chain components, carbon metabolism enzymes and solute transporter proteins. CoReg identified several promoter motifs that helped to explain the patterns of expression observed.ConclusionModuleFinder identifies sets of genes and treatments that form useful sets for analysis of the mechanisms behind co-expression. CoReg links the clustering tree of expression-based relationships in these sets with frequency tables of promoter elements. These sets of promoter elements represent putative cis-acting regulatory elements for sets of genes, and can then be tested experimentally. We consider these tools, both built on an open source software product to provide valuable, alternative tools for the prioritisation of promoter elements for experimental analysis.

Dataset Information

PRESTA: associating promoter sequences with information on gene expression.

Publications

PRESTA: associating promoter sequences with information on gene expression.

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