The Eukaryotic Promoter Database (EPD): recent developments

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes description of the initiation site mapping data, cross-references to other databases, and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Recent efforts have focused on exhaustive crossreferencing to the EMBL nucleotide sequence database, and on the improvement of the WWW-based user interfaces and data retrieval mechanisms. EPD can be accessed at http://www.epd.isb-sib.c

The Eukaryotic Promoter Database (EPD): recent developments

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes description of the initiation site mapping data, cross-references to other databases, and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Recent efforts have focused on exhaustive cross-referencing to the EMBL nucleotide sequence database, and on the improvement of the WWW-based user interfaces and data retrieval mechanisms. EPD can be accessed at http://www.epd.isb-sib.c

EPD in its twentieth year: towards complete promoter coverage of selected model organisms

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). Access to promoter sequences is provided by pointers to positions in the corresponding genomes. Promoter evidence comes from conventional TSS mapping experiments for individual genes, or, starting from release 73, from mass genome annotation projects. Subsets of promoter sequences with customized 5′ and 3′ extensions can be downloaded from the EPD website. The focus of current development efforts is to reach complete promoter coverage for important model organisms as soon as possible. To speed up this process, a new class of preliminary promoter entries has been introduced as of release 83, which requires less stringent admission criteria. As part of a continuous integration process, new web-based interfaces have been developed, which allow joint analysis of promoter sequences with other bioinformatics resources developed by our group, in particular programs offered by the Signal Search Analysis Server, and gene expression data stored in the CleanEx database. EPD can be accessed at

Genetic networks of antibacterial responses of eukaryotic cells. Bioinformatics analysis and modeling

This work describes the development of new methods to construction of promoter models as one of necessary steps of regulatory networks construction. Identification of characteristic promoter features shows the role of specific transcription factors (TFs) in triggering the response, which in turn sheds light on the signaling pathways activating these TFs. Treating reported results of microarray analyses together with other available information about the genes expressed in different cellular systems under consideration, we search for distinguishing features of the promoters of coexpressed genes. The application of such promoter models enables to identify additional candidate genes belonging to the same regulatory network. Four novel approaches are presented in this work: (i) subtractive approach to matrix generation; (ii) distance distribution approach; (iii) "seed" sets approach; (iv) complementary pairs approach. These approaches help to solve serious problems in promoter model construction such as the doubtful reliability of positive training sets ("seed" sets approach) and lack of knowledge about the exact signaling pathways triggering the gene expression (complementary pairs approach); the subtractive approach to matrix generation allows to refine positional weight matrices (PWM) for heterogeneous sets of binding sites, thus to improve the PWM search for single TFBS. A significant improvement of the specificity of promoter analysis has been achieved by applying statistical methods for characterizing TFBS combinations at over-represented distances rather than the mere identification of single potential TFBS (distance distributions approach). The newly developed methods were applied to the description of four defensive eukaryotic systems in terms of transcription regulation. The obtained models enabled us to gain better insights into the pathways of the corresponding signaling networks.Diese Arbeit beschreibt die Entwicklung mehrerer neuer Methoden zur Konstruktion von Promotormodellen als einen der notwendigen Schritte zur Konstruktion regulatorischer Netzwerke. Die Identifizierung charakteristischer Eigenschaften von Promotoren zeigt die Rolle bestimmter Transkriptionsfaktoren (TF) beim Auslösen spezifischer Antworten auf, was wiederum Aufschluss über die Signalwege zur Aktivierung dieser TF gibt. Durch Verarbeitung von Ergebnissen aus Microarray-Analysen zusammen mit weiteren verfügbaren Informationen über die in den betrachteten zellulären Systemen exprimierten Gene suchen wir nach kennzeichnenden Eigenschaften koregulierter Promotoren. Die Applikation solcher Promotermodelle ermöglicht die Identifizierung zusätzlicher Kandidatengene, die demselben regulatorischen Netzwerk angehören. Vier neue Ansätze werden in dieser Arbeit präsentiert: (i) der subtraktive Ansatz zur Matrixerzeugung; (ii) der Distanzverteilungsansatz; (iii) der "seed"-Set-Ansatz; (iv) der Ansatz komplementärer Paare. Diese Ansätze helfen, beträchtliche Probleme der Promotormodellkonstruktion zu lösen, wie die zweifelhafte Zuverlässigkeit positiver Trainingsets ("seed"-Set-Ansatz) und der Mangel an Wissen über die präzisen Signalwege, die bestimmte Genexpressionsereignisse auslösen (Ansatz komplementärer Paare). Der subtraktive Ansatz zur Matrixerzeugung erlaubt, Positionsgewichtungsmatrizen (PWM) für heterogene Sets von Bindungsstellen zu verfeinern und dadurch die PWM-Suche für einzelne TFBSs zur verbessern. Eine signifikante Verbesserung der Spezifität der Promotoranalyse wurde durch die Anwendung statistischer Methoden zur Charakterisierung von TFBS-Kombinationen in überrepräsentierten Distanzen anstelle der bloßen Identifizierung einzelner potentieller TFBSs erreicht. Die neuentwickelten Methoden wurden zur Beschreibung von vier eukaryotischen Abwehrsystemen verwendet. Die erhaltenen Modelle eröffneten tiefergehende Einsichten in die Pfade der zugehörigen Signalnetzwerke

Stress-inducible protein 1: a bioinformatic analysis of the human, mouse and yeast STI1 gene structure

Stress-inducible protein 1 (Sti1) is a 60 kDa eukaryotic protein that is important under stress and non-stress conditions. Human Sti1 is also known as the Hsp70/Hsp90 organising protein (Hop) that coordinates the functional cooperation of heat shock protein 70 (Hsp70) and heat shock protein 90 (Hsp90) during the folding of various transcription factors and kinases, including certain oncogenic proteins and prion proteins. Limited studies have been conducted on the STI1 gene structure. Thus, the aim of this study was to develop a comprehensive description of human STI1 (hSTI1), mouse STI1 (mSTI1), and yeast STI1 (ySTI1) genes, using a bioinformatic approach. Genes encoded near the STI1 loci were identified for the three organisms using National Centre for Biotechnology Information (NCBI) MapViewer and the Saccharomyces Genome Database. Exon/intron boundaries were predicted using Hidden Markov model gene prediction software (HMMGene) and Genscan, and by alignment of the mRNA sequence with the genomic DNA sequence. Transcription factor binding sites (TFBS) were predicted by scanning the region 1000 base pairs (bp) upstream of the STI1 orthologues’ transcription start site (TSS) with Alibaba, Transcription element search software (TESS) and Transcription factor search (TFSearch). The promoter region was defined by comparing the number, type and position of TFBS across the orthologous STI1 genes. Additional putative TFBS were identified for ySTI1 by searching with software that aligns nucleic acid conserved elements (AlignACE) for over-represented motifs in the region upstream of the TSS of genes thought to be co-regulated with ySTI1. This study showed that hSTI1 and mSTI1 occur in a region of synteny with a number of genes of related function. Both hSTI1 and mSTI1 comprised 14 putative exons, while ySTI1 was encoded on a single exon. Human and mouse STI1 shared a perfectly conserved 55 bp region spanning their predicted TSS, although their TATA boxes were not conserved. A putative CpG island was identified in the region from -500 to +100 bp relative to the hSTI1 and mSTI1 TSS. This region overlapped with a region of high TFBS density, suggesting that the core promoter region was located in the region approximately 100 to 200 bp upstream of the TSS. Several conserved clusters of TFBS were also identified upstream of this promoter region, including binding sites for stimulatory protein 1 (Sp1), heat shock factor (HSF), nuclear factor kappa B (NF-kappaB), and the cAMP/enhancer binding protein (C/EBP). Microarray data suggested that ySTI1 was co-regulated with several heat shock proteins and substrates of the Hsp70/Hsp90 heterocomplex, and several putative regulatory elements were identified in the upstream region of these co-regulated genes, including a motif for HSF binding. The results of this research suggest several avenues of future experimental work, including the confirmation of the proposed core promoter, upstream regulatory elements, and CpG island, and the investigation into the co-regulation of mammalian STI1 with its surrounding genes. These results could also be used to inform STI1 gene knockout experiments in mice, to assess the biological importance of mammalian STI1

The Eukaryotic Promoter Database (EPD): recent developments.

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes description of the initiation site mapping data, cross-references to other databases, and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Recent efforts have focused on exhaustive cross-referencing to the EMBL nucleotide sequence database, and on the improvement of the WWW-based user interfaces and data retrieval mechanisms. EPD can be accessed at http://www.epd.isb-sib.c