Inst. f. Informatik   
Uni Leipzig

Bioinformatics Preprint 04-017


Comparative promoter region analysis powered by CORG

Christoph Dieterich, Steffen Grossmann, Andrea Tanzer, Stefan Ropcke, Peter F Arndt, Peter F Stadler, Martin Vingron

Submitted for publication in:
BMC Genomics

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.
Methods: The automated annotation of promoter regions integrates information of two kinds. First, it detects cross-species conservation within upstream regions of orthologous genes. Pairwise as well a multiple sequence comparisons are computed. Second, binding site descriptions (position-weight matrices) are employed to predict conserved regulatory elements. Assembled EST sequences and verified transcription start sites are incorporated to distinguish exonic from other sequences. Results: 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 website or can be directly accessed 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. Conclusions: 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 sequence elements (e.g. microRNAs and binding sites).

CORG database, promoter regions, transcription factor binding sites, micro RNAs

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