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Comparative promoter region analysis powered by CORG

BACKGROUND: Promoters are key players in gene regulation. They receive signals from various sources (e.g. cell surface receptors) and control the level of transcription initiation, which largely determines gene expression. In vertebrates, transcription start sites and surrounding regulatory elements...

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Autores principales: Dieterich, Christoph, Grossmann, Steffen, Tanzer, Andrea, Röpcke, Stefan, Arndt, Peter F, Stadler, Peter F, Vingron, Martin
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC555765/
https://www.ncbi.nlm.nih.gov/pubmed/15723697
http://dx.doi.org/10.1186/1471-2164-6-24
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author Dieterich, Christoph
Grossmann, Steffen
Tanzer, Andrea
Röpcke, Stefan
Arndt, Peter F
Stadler, Peter F
Vingron, Martin
author_facet Dieterich, Christoph
Grossmann, Steffen
Tanzer, Andrea
Röpcke, Stefan
Arndt, Peter F
Stadler, Peter F
Vingron, Martin
author_sort Dieterich, Christoph
collection PubMed
description BACKGROUND: Promoters are key players in gene regulation. They receive signals from various sources (e.g. cell surface receptors) and control the level of transcription initiation, which largely determines gene expression. In vertebrates, transcription start sites and surrounding regulatory elements are often poorly defined. To support promoter analysis, we present CORG , a framework for studying upstream regions including untranslated exons (5' UTR). DESCRIPTION: The automated annotation of promoter regions integrates information of two kinds. First, statistically significant cross-species conservation within upstream regions of orthologous genes is detected. Pairwise as well as multiple sequence comparisons are computed. Second, binding site descriptions (position-weight matrices) are employed to predict conserved regulatory elements with a novel approach. Assembled EST sequences and verified transcription start sites are incorporated to distinguish exonic from other sequences. As of now, we have included 5 species in our analysis pipeline (man, mouse, rat, fugu and zebrafish). We characterized promoter regions of 16,127 groups of orthologous genes. All data are presented in an intuitive way via our web site. Users are free to export data for single genes or access larger data sets via our DAS server . The benefits of our framework are exemplarily shown in the context of phylogenetic profiling of transcription factor binding sites and detection of microRNAs close to transcription start sites of our gene set. CONCLUSION: The CORG platform is a versatile tool to support analyses of gene regulation in vertebrate promoter regions. Applications for CORG cover a broad range from studying evolution of DNA binding sites and promoter constitution to the discovery of new regulatory sequence elements (e.g. microRNAs and binding sites).
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spelling pubmed-5557652005-04-01 Comparative promoter region analysis powered by CORG Dieterich, Christoph Grossmann, Steffen Tanzer, Andrea Röpcke, Stefan Arndt, Peter F Stadler, Peter F Vingron, Martin BMC Genomics Database BACKGROUND: Promoters are key players in gene regulation. They receive signals from various sources (e.g. cell surface receptors) and control the level of transcription initiation, which largely determines gene expression. In vertebrates, transcription start sites and surrounding regulatory elements are often poorly defined. To support promoter analysis, we present CORG , a framework for studying upstream regions including untranslated exons (5' UTR). DESCRIPTION: The automated annotation of promoter regions integrates information of two kinds. First, statistically significant cross-species conservation within upstream regions of orthologous genes is detected. Pairwise as well as multiple sequence comparisons are computed. Second, binding site descriptions (position-weight matrices) are employed to predict conserved regulatory elements with a novel approach. Assembled EST sequences and verified transcription start sites are incorporated to distinguish exonic from other sequences. As of now, we have included 5 species in our analysis pipeline (man, mouse, rat, fugu and zebrafish). We characterized promoter regions of 16,127 groups of orthologous genes. All data are presented in an intuitive way via our web site. Users are free to export data for single genes or access larger data sets via our DAS server . The benefits of our framework are exemplarily shown in the context of phylogenetic profiling of transcription factor binding sites and detection of microRNAs close to transcription start sites of our gene set. CONCLUSION: The CORG platform is a versatile tool to support analyses of gene regulation in vertebrate promoter regions. Applications for CORG cover a broad range from studying evolution of DNA binding sites and promoter constitution to the discovery of new regulatory sequence elements (e.g. microRNAs and binding sites). BioMed Central 2005-02-21 /pmc/articles/PMC555765/ /pubmed/15723697 http://dx.doi.org/10.1186/1471-2164-6-24 Text en Copyright © 2005 Dieterich et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database
Dieterich, Christoph
Grossmann, Steffen
Tanzer, Andrea
Röpcke, Stefan
Arndt, Peter F
Stadler, Peter F
Vingron, Martin
Comparative promoter region analysis powered by CORG
title Comparative promoter region analysis powered by CORG
title_full Comparative promoter region analysis powered by CORG
title_fullStr Comparative promoter region analysis powered by CORG
title_full_unstemmed Comparative promoter region analysis powered by CORG
title_short Comparative promoter region analysis powered by CORG
title_sort comparative promoter region analysis powered by corg
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC555765/
https://www.ncbi.nlm.nih.gov/pubmed/15723697
http://dx.doi.org/10.1186/1471-2164-6-24
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