YEASTRACT: a database to search for transcription regulatory associations in Saccharomyces cerevisiae.
Miguel C. Teixeira (1), Pedro Monteiro (2), Pooja Jain (2), Sandra Tenreiro (1), Alexandra R. Fernandes (3), Nuno P. Mira (1), Marta Alenquer (1), Ana T. Freitas (2), Arlindo L. Oliveira (2), Isabel Sá-Correia (1)
(1) Biological Sciences Research Group, CEBQ, Instituto Superior Tecnico, 1049-001 Lisbon, Portugal; (2) Knowledge Discovery and Bioinformatics/ Algorithms for Optimization and Simulation group, INESC-ID, Lisbon, Portugal; (3) Biological Sciences Research Group, CEBQ, Instituto Superior Tecnico, 1049-001 Lisbon, Portugal, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande, 376, 1749-029 Lisboa, Portugal.
YEASTRACT (Yeast Search for Transcriptional Regulators And Consensus Tracking; www.yeastract.com) database is a repository of more than 11000 regulatory associations between genes and transcription factors (TF) in Saccharomyces cerevisiae, based on more than 700 bibliographic references. It also includes the description of 242 specific DNA binding sites for 102 characterized TFs. Further information about each yeast gene included in the database was extracted from Saccharomyces Genome Database (SGD). For each gene the associated Gene Ontology (GO) terms and their hierarchy in GO were obtained from the GO consortium. Currently, YEASTRACT maintains a total of 27,276 terms from GO. The nucleotide sequences of the promoter and coding regions for Yeast genes were obtained from Regulatory Sequence Analysis Tools (RSAT) and SGD. All the information in YEASTRACT will be updated regularly to match the latest data from SGD, GO consortium and recent literature on yeast regulatory networks. The database was developed to provide assistance in three major issues: i) Identification of documented and potential regulatory associations for an ORF/Gene; ii) Microarray data clustering based on regulatory associations; iii) Search for a DNA motif within known TF binding sites and promoter regions. Future releases of the database will include additional computational tools to support researchers in the process of identification of transcription regulatory associations.