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TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes
BIOBASE GmbH Halchtersche Strasse 33, D-38304 Wolfenbüttel, Germany
*To whom correspondence should be addressed. Tel: +49 5331 8584 28; Fax: +49 5331 8584 70; Email: vma{at}biobase.de
Received September 15, 2005. Revised October 27, 2005. Accepted October 27, 2005.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONAVAILABILITYREFERENCES |
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The TRANSFAC® database on transcription factors, their binding sites, nucleotide distribution matrices and regulated genes as well as the complementing database TRANSCompel® on composite elements have been further enhanced on various levels. A new web interface with different search options and integrated versions of MatchTM and PatchTM provides increased functionality for TRANSFAC®. The list of databases which are linked to the common GENE table of TRANSFAC® and TRANSCompel® has been extended by: Ensembl, UniGene, EntrezGene, HumanPSDTM and TRANSPROTM. Standard gene names from HGNC, MGI and RGD, are included for human, mouse and rat genes, respectively. With the help of InterProScan, Pfam, SMART and PROSITE domains are assigned automatically to the protein sequences of the transcription factors. TRANSCompel® contains now, in addition to the COMPEL table, a separate table for detailed information on the experimental EVIDENCE on which the composite elements are based. Finally, for TRANSFAC®, in respect of data growth, in particular the gain of Drosophila transcription factor binding sites (by courtesy of the Drosophila DNase I footprint database) and of Arabidopsis factors (by courtesy of DATF, Database of Arabidopsis Transcription Factors) has to be stressed. The here described public releases, TRANSFAC® 7.0 and TRANSCompel® 7.0, are accessible under http://www.gene-regulation.com/pub/databases.html.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONAVAILABILITYREFERENCES |
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For a better understanding of almost all life processes, a deeper knowledge of gene regulation seems indispensable. TRANSFAC® (1–3) and TRANSCompel® (3,4) are among those databases which have been contributing for years to sight and order the published data on eukaryotic gene transcription regulation and, by doing so, to make the available data applicable for analysis and predictions. The primary data in the two databases (e.g. DNA-binding sites in TRANSFAC®, composite elements in TRANSCompel®) are based on experimental evidence. These data are extracted by curators from peer-reviewed papers. The curators search the scientific literature for suitable data, which are then entered via an input client, making use of controlled vocabulary and various automated functions, into a relational database, from which flatfile releases are generated from time to time. Collection of these data in a structured form allows us to deduce—via comparison and classification—secondary or so-called meta-data (e.g. nucleotide distribution matrices, factor classification). Both types of data, the primary as well as the secondary data, can then serve for (sequence-based) predictions by certain programs, e.g. MatchTM (5) (for matrix-based transcription factor binding site searches), PatchTM (for pattern-based transcription factor binding site searches) and P-MatchTM (6) (for a mixture of matrix- and pattern-based binding site searches). (These programs are all available on the same server as the herein described databases.)
Content of TRANSFAC® and TRANSCompel®
The primary data of TRANSFAC® are stored in the three tables FACTOR, SITE and GENE for information on transcription factors, their binding sites and regulated genes, respectively. Besides genomic binding sites, the SITE table contains also so-called artificial binding sites, which are mostly sites from random oligonucleotide selection assays, and IUPAC consensus sequences. Nucleotide distribution matrices, which are derived from a collection of binding sites for a particular factor are stored in the MATRIX table, while the CLASS table groups the transcription factors according to their DNA-binding domains. In addition to this CLASS table, the factor entries are linked to the respective nodes in a classification hierarchy (7). In a sixth table (CELL), cell lines and other kinds of factor sources, which were used for detection of a binding site/binding activity, are stored (Table 1).
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While TRANSFAC® deals essentially with single factor–site interactions, the focus of TRANSCompel® is on so-called composite elements, consisting of two (or more) neighboring binding sites, characterized by synergistic or antagonistic effects between the two transcription factors binding to them. They are, thus, the smallest units of combinatorial transcriptional regulation (Table 1).
Recent changes in the database structure
In the TRANSFAC® GENE table a new field has been introduced for the inclusion of information on the regulation of gene expression, especially when this information cannot be assigned (yet) to a particular binding site. The CELL table, which contains entries of cell lines or other factor sources, lists now all SITE entries, for which binding activity was shown under the given conditions. The factor CLASS entries have been linked to the respective nodes in the hierarchical factor classification. The links from GENE entries (TRANSFAC®) to composite elements (in TRANSCompel®) are no longer listed among other database links, but are given now subsequent to the listed binding sites, and, as for those, the positions of the composite elements within the gene (usually relative to the transcription start site, TSS) are given. The structure of TRANScompel® has been fundamentally changed. The database consists now of two tables. The COMPEL table contains general information about the composite elements including sequence, positions, gene, names of cooperating transcription factors as well as a brief list of the experimental evidence, while detailed information about the experimental evidence, confirming physical and functional interactions between the corresponding transcription factors, can be found in the EVIDENCE table.
Linking to other databases
Linking to other databases has been extended. The FACTOR and GENE entries of TRANSFAC® have been linked to the respective protein reports in HumanPSDTM (8). GENE entries from human, mouse and rat have been linked to the promoter database TRANSPROTM [see the paper about TiProD (9)], and the corresponding SITE entries were also mapped to the promoter sequences in TRANSPROTM, where absolute genomic positions are given for the promoter sequences. These sequences in TRANSPROTM reach from 10 000 nt upstream to 1000 nt downstream relative to the accepted ‘virtual TSSs’, which are derived by weighting documented TSSs from different resources (9). FACTOR–SITE–GENE links are mirrored as ‘trans-regulations’ (FACTOR
GENE) in TRANSPATH® (10,11), where these are incorporated into the overall regulation network of the cell. For yeast (Saccharomyces cerevisiae) genes, now standard open reading frame names are given under synonyms. For human, mouse and rat genes (and factors) HGNC (12), MGI (13) and RGD (14) gene symbols are given, respectively. (The HGNC, MGI and RGD gene symbols appear in the GENE table under external database links and in the FACTOR table alongside the GENE link.) Further, new links to Ensembl (15) and UniGene (16), as well as Affymetrix probe set IDs were added to the GENE table, and the links to LocusLink were changed into EntrezGene (17) links and expanded from human to mouse and rat, as well as—to a smaller extend—other organisms.
Automatic factor domain assignment
For each release protein sequences are analyzed with InterProScan (18). From the databases integrated by InterPro, Pfam (19) and SMART (20), as well as PROSITE (21) models corresponding to low-complexity regions are selected. The automatically assigned domains, which are linked to the corresponding Pfam, SMART and PROSITE entries, are meant to complement the manually annotated domains, many of which are based on functional studies reported in the original literature.
From Arabidopsis to Drosophila
Besides a general data increase, with major focus on human, mouse, rat and other vertebrate organisms, especially the amount of Arabidopsis thaliana and Drosophila melanogaster data has been increased for TRANSFAC® 7.0. This was accomplished in particular by import of 1440 factor entries from DATF, Database of Arabidopsis transcription factors [http://datf.cbi.pku.edu.cn/ (22)], and 899 genomic site entries from the Drosophila DNase I footprint database [http://www.flyreg.org/ (23)]. The imported data are referenced accordingly and are linked to the respective databases, from which they were derived. In addition, the Drosophila gene entries linked to the newly imported sites contain pointers to FlyBase (24) and EntrezGene (17). Identifiers used by Ensembl which are synonyms in FlyBase and EntrezGene (e.g. CG3481) were introduced as synonyms of the gene name and were used for mapping during the import procedure.
New web interface
TRANSFAC® and the programs MatchTM and PatchTM, for transcription factor binding site searches, are now combined under a common web interface. In addition to the ‘one table search’ the new search engine has a search mode for simultaneous search in all tables. The ‘one table search’ contains now the possibility to combine searches in up to three fields at the same time or to make batch search and further options. The user can also choose the output fields, which are to be displayed in the result list. Each search can be stored and refined later on or the stored search result (list of accession numbers) can serve as input for a batch search in another table. Finally, on the basis of the result from a search in the SITE or MATRIX table, ‘profiles’ (sets of sites or matrices) can be created, which can be used by the integrated version of PatchTM or MatchTM, respectively, for sequence analyses.
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AVAILABILITY |
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TOPABSTRACTINTRODUCTIONAVAILABILITYREFERENCES |
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The described TRANSFAC® 7.0 and TRANSCompel® 7.0 releases as well as the programs MatchTM, PatchTM and P-MatchTM are all freely available for online use by users from non-profit organizations at http://www.gene-regulation.com/pub/databases.html#transfac, http://www.gene-regulation.com/pub/databases.html#transcompel and http://www.gene-regulation.com/pub/programs.html, respectively.
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ACKNOWLEDGEMENTS |
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We like to thank Prof Jingchu Luo, Dr Anyuan Guo and colleagues from Peking University, Center for Bioinformatics, for providing the DATF data and Dr Casey Bergman and colleagues from FlyReg, Universiy of Manchester, U.K. for the Drosophila footprint data, as well as Prof. Dr. Reinhard Hehl and Claudia Galuschka from the Technical University Braunschweig, Germany for their collaboration on plant data curation. Further, we like to thank all people who have been contributing over the years to the development and curation of the described databases and connected tools. Parts of the work were funded by grants of the German Ministry of Education and Research (BMBF) ‘Intergenomics’ (031U210B), collectively by BioRegioN GmbH and BMBF ‘BioProfil’ (0313092), by the European Commission under FP6-‘Life sciences, genomics and biotechnology for health’, contract LSHG-CT-2004-503568 ‘COMBIO’, and by the European Commission under ‘Marie Curie research training networks’, contract MRTN-CT-2004-512285 ‘TRANSISTOR’. Funding to pay the Open Access publication charges for this article was provided by BIOBASE GmbH.
Conflict of interest statement. None declared.
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S. Hannenhalli Eukaryotic transcription factor binding sites--modeling and integrative search methods Bioinformatics, June 1, 2008; 24(11): 1325 - 1331. [Abstract] [Full Text] [PDF]
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M. Hackenberg and R. Matthiesen Annotation-Modules: a tool for finding significant combinations of multisource annotations for gene lists Bioinformatics, June 1, 2008; 24(11): 1386 - 1393. [Abstract] [Full Text] [PDF]
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E. Hoffmann, J. Ashouri, S. Wolter, A. Doerrie, O. Dittrich-Breiholz, H. Schneider, E. F. Wagner, J. Troppmair, N. Mackman, and M. Kracht Transcriptional Regulation of EGR-1 by the Interleukin-1-JNK-MKK7-c-Jun Pathway J. Biol. Chem., May 2, 2008; 283(18): 12120 - 12128. [Abstract] [Full Text] [PDF]
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J. Eddy and N. Maizels Conserved elements with potential to form polymorphic G-quadruplex structures in the first intron of human genes Nucleic Acids Res., March 27, 2008; 36(4): 1321 - 1333. [Abstract] [Full Text] [PDF]
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V. Bourdeau, J. Deschenes, D. Laperriere, M. Aid, J. H. White, and S. Mader Mechanisms of primary and secondary estrogen target gene regulation in breast cancer cells Nucleic Acids Res., January 17, 2008; 36(1): 76 - 93. [Abstract] [Full Text] [PDF]
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R. Harada, C. Vadnais, L. Sansregret, L. Leduy, G. Berube, F. Robert, and A. Nepveu Genome-wide location analysis and expression studies reveal a role for p110 CUX1 in the activation of DNA replication genes Nucleic Acids Res., January 17, 2008; 36(1): 189 - 202. [Abstract] [Full Text] [PDF]
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H. Wakaguri, R. Yamashita, Y. Suzuki, S. Sugano, and K. Nakai DBTSS: database of transcription start sites, progress report 2008 Nucleic Acids Res., January 11, 2008; 36(suppl_1): D97 - D101. [Abstract] [Full Text] [PDF]
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J. Fang, Y. Dong, N. Salamat-Miller, and C. Russell Middaugh DB-PABP: a database of polyanion-binding proteins Nucleic Acids Res., January 11, 2008; 36(suppl_1): D303 - D306. [Abstract] [Full Text] [PDF]
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A.-Y. Guo, X. Chen, G. Gao, H. Zhang, Q.-H. Zhu, X.-C. Liu, Y.-F. Zhong, X. Gu, K. He, and J. Luo PlantTFDB: a comprehensive plant transcription factor database Nucleic Acids Res., January 11, 2008; 36(suppl_1): D966 - D969. [Abstract] [Full Text] [PDF]
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Y. Y. Yamamoto and J. Obokata ppdb: a plant promoter database Nucleic Acids Res., January 11, 2008; 36(suppl_1): D977 - D981. [Abstract] [Full Text] [PDF]
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B. C. Foat, R. G. Tepper, and H. J. Bussemaker TransfactomeDB: a resource for exploring the nucleotide sequence specificity and condition-specific regulatory activity of trans-acting factors Nucleic Acids Res., January 11, 2008; 36(suppl_1): D125 - D131. [Abstract] [Full Text] [PDF]
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O. L. Griffith, S. B. Montgomery, B. Bernier, B. Chu, K. Kasaian, S. Aerts, S. Mahony, M. C. Sleumer, M. Bilenky, M. Haeussler, et al. ORegAnno: an open-access community-driven resource for regulatory annotation Nucleic Acids Res., January 11, 2008; 36(suppl_1): D107 - D113. [Abstract] [Full Text] [PDF]
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J. Donitz, B. Goemann, M. Lize, H. Michael, N. Sasse, E. Wingender, and A. P. Potapov EndoNet: an information resource about regulatory networks of cell-to-cell communication Nucleic Acids Res., January 11, 2008; 36(suppl_1): D689 - D694. [Abstract] [Full Text] [PDF]
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L. O. Barrera, Z. Li, A. D. Smith, K. C. Arden, W. K. Cavenee, M. Q. Zhang, R. D. Green, and B. Ren Genome-wide mapping and analysis of active promoters in mouse embryonic stem cells and adult organs Genome Res., January 1, 2008; 18(1): 46 - 59. [Abstract] [Full Text] [PDF]
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L. N. Singh, L.-S. Wang, and S. Hannenhalli TREMOR a tool for retrieving transcriptional modules by incorporating motif covariance Nucleic Acids Res., December 18, 2007; 35(21): 7360 - 7371. [Abstract] [Full Text] [PDF]
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Z. Qian, L. Lu, X. Liu, Y.-D. Cai, and Y. Li An approach to predict transcription factor DNA binding site specificity based upon gene and transcription factor functional categorization Bioinformatics, September 15, 2007; 23(18): 2449 - 2454. [Abstract] [Full Text] [PDF]
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J. W. Tullai, M. E. Schaffer, S. Mullenbrock, G. Sholder, S. Kasif, and G. M. Cooper Immediate-Early and Delayed Primary Response Genes Are Distinct in Function and Genomic Architecture J. Biol. Chem., August 17, 2007; 282(33): 23981 - 23995. [Abstract] [Full Text] [PDF]
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A. Kerhornou and R. Guigo BioMoby web services to support clustering of co-regulated genes based on similarity of promoter configurations Bioinformatics, July 15, 2007; 23(14): 1831 - 1833. [Abstract] [Full Text] [PDF]
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J. Reimand, M. Kull, H. Peterson, J. Hansen, and J. Vilo g:Profiler--a web-based toolset for functional profiling of gene lists from large-scale experiments Nucleic Acids Res., July 13, 2007; 35(suppl_2): W193 - W200. [Abstract] [Full Text] [PDF]
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M. Brudno, A. Poliakov, S. Minovitsky, I. Ratnere, and I. Dubchak Multiple whole genome alignments and novel biomedical applications at the VISTA portal Nucleic Acids Res., July 13, 2007; 35(suppl_2): W669 - W674. [Abstract] [Full Text] [PDF]
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C. Backes, A. Keller, J. Kuentzer, B. Kneissl, N. Comtesse, Y. A. Elnakady, R. Muller, E. Meese, and H.-P. Lenhof GeneTrail--advanced gene set enrichment analysis Nucleic Acids Res., July 13, 2007; 35(suppl_2): W186 - W192. [Abstract] [Full Text] [PDF]
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N. A. Kolchanov, T. I. Merkulova, E. V. Ignatieva, E. A. Ananko, D. Yu. Oshchepkov, V. G. Levitsky, G. V. Vasiliev, N. V. Klimova, V. M. Merkulov, and T. C. Hodgman Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes Brief Bioinform, July 12, 2007; (2007) bbm027v1. [Abstract] [Full Text] [PDF]
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K. Tsuritani, T. Irie, R. Yamashita, Y. Sakakibara, H. Wakaguri, A. Kanai, J. Mizushima-Sugano, S. Sugano, K. Nakai, and Y. Suzuki Distinct class of putative "non-conserved" promoters in humans: Comparative studies of alternative promoters of human and mouse genes Genome Res., July 1, 2007; 17(7): 1005 - 1014. [Abstract] [Full Text] [PDF]
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J. A. Greenbaum, B. Pang, and T. D. Tullius Construction of a genome-scale structural map at single-nucleotide resolution Genome Res., June 1, 2007; 17(6): 947 - 953. [Abstract] [Full Text] [PDF]
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L. Li, Y. Liang, and R. L. Bass GAPWM: a genetic algorithm method for optimizing a position weight matrix Bioinformatics, May 15, 2007; 23(10): 1188 - 1194. [Abstract] [Full Text] [PDF]
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Q.-H. Zhu, A.-Y. Guo, G. Gao, Y.-F. Zhong, M. Xu, M. Huang, and J. Luo DPTF: a database of poplar transcription factors Bioinformatics, May 15, 2007; 23(10): 1307 - 1308. [Abstract] [Full Text] [PDF]
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B. J. Jenkins, A. W. Roberts, C. J. Greenhill, M. Najdovska, T. Lundgren-May, L. Robb, D. Grail, and M. Ernst Pathologic consequences of STAT3 hyperactivation by IL-6 and IL-11 during hematopoiesis and lymphopoiesis Blood, March 15, 2007; 109(6): 2380 - 2388. [Abstract] [Full Text] [PDF]
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L. Zhang, S. Kasif, and a. C. R. Cantor Quantifying DNA-protein binding specificities by using oligonucleotide mass tags and mass spectroscopy PNAS, February 27, 2007; 104(9): 3061 - 3066. [Abstract] [Full Text] [PDF]
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S. Nagel, M. Scherr, A. Kel, K. Hornischer, G. E. Crawford, M. Kaufmann, C. Meyer, H. G. Drexler, and R. A.F. MacLeod Activation of TLX3 and NKX2-5 in t(5;14)(q35;q32) T-Cell Acute Lymphoblastic Leukemia by Remote 3'-BCL11B Enhancers and Coregulation by PU.1 and HMGA1 Cancer Res., February 15, 2007; 67(4): 1461 - 1471. [Abstract] [Full Text] [PDF]
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T. Sandmann, C. Girardot, M. Brehme, W. Tongprasit, V. Stolc, and E. E.M. Furlong A core transcriptional network for early mesoderm development in Drosophila melanogaster Genes & Dev., February 15, 2007; 21(4): 436 - 449. [Abstract] [Full Text] [PDF]
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