REDfly v3.0: toward a comprehensive database of transcriptional regulatory elements in Drosophila.

The REDfly database of Drosophila transcriptional cis-regulatory elements provides the broadest and most comprehensive available resource for experimentally validated cis-regulatory modules and transcription factor binding sites among the metazoa. The third major release of the database extends the utility of REDfly as a powerful tool for both computational and experimental studies of transcription regulation. REDfly v3.0 includes the introduction of new data classes to expand the types of regulatory elements annotated in the database along with a roughly 40% increase in the number of records. A completely redesigned interface improves access for casual and power users alike; among other features it now automatically provides graphical views of the genome, displays images of reporter gene expression and implements improved capabilities for database searching and results filtering. REDfly is freely accessible at http://redfly.ccr.buffalo.edu.

Identification of expressed sequence tags preferentially expressed in human placentas by in silico subtraction.

OBJECTIVES: To identify expressed sequence tag (EST) clusters preferentially expressed in placentas. METHODS: The National Center for Biotechnology's online UniGene database contains 14 placenta libraries. In silico (computer-based) subtraction compared placenta libraries against the remaining libraries to identify transcripts preferentially expressed in placentas. For known genes, placental expression or their use in prenatal diagnosis was then explored online using LocusLink and PubMed. RESULTS: Placentas preferentially expressed 475 EST clusters. Of these, 18 EST clusters with no known function were expressed exclusively in placentas. Of the remaining 457 EST clusters, 90 showed preferential placental expression by >/=25 times. Of these 90, literature searches on the 45 EST clusters with known functions showed 44 linked to placental physiology or proposed as markers for prenatal diagnosis [i.e. beta-hCG, pregnancy-specific glycoproteins, human placental lactogens, pregnancy-associated plasma protein A (PAPP-A)]. Selected genes with known function in pregnancy but whose preferential placental expression fell below the factor of 25 threshold were also identified. CONCLUSION: In silico subtraction identified 44 previously studied genes involved in placental physiology as well as 63 EST clusters preferentially expressed in placental tissue, which may serve as targets for future studies seeking novel markers for prenatal diagnosis or to better understand placental genetics.