ForestTreeDB: a database dedicated to the mining of tree transcriptomes

ForestTreeDB is intended as a resource that centralizes large-scale expressed sequence tag (EST) sequencing results from several tree species (). It currently encompasses 344 878 quality sequences from 68 libraries, from diverse organs of conifer and hybrid poplar trees. It utilizes the Nimbus data model to provide a hosting system for multiple projects, and uses object-relational mapping APIs in Java and Perl for data accesses within an Oracle database designed to be scalable, maintainable and extendable. Transcriptome builds or unigene sets occupy the focal point of the system. Several of the five current species-specific unigenes were used to design microarrays and SNP resources. The ForestTreeDB web application provides the means for multiple combination database queries. It presents the user with a list of discrete queries to retrieve and download large EST datasets or sequences from precompiled unigene assemblies. Functional annotation assignment is not trivial in conifers which are distantly related to angiosperm model plants. Optimal annotations are achieved through database queries that integrate results from several procedures based open-source tools. ForestTreeDB aims to facilitate sequence mining of coherent annotations in multiple species to support comparative genomic approaches. We plan to continuously enrich ForestTreeDB with other resources through collaborations with other genomic projects

Databases and Information Integration for the Medicago truncatula Genome and Transcriptome

An international consortium is sequencing the euchromatic genespace of Medicago truncatula. Extensive bioinformatic and database resources support the marker-anchored bacterial artificial chromosome (BAC) sequencing strategy. Existing physical and genetic maps and deep BAC-end sequencing help to guide the sequencing effort, while EST databases provide essential resources for genome annotation as well as transcriptome characterization and microarray design. Finished BAC sequences are joined into overlapping sequence assemblies and undergo an automated annotation process that integrates ab initio predictions with EST, protein, and other recognizable features. Because of the sequencing project's international and collaborative nature, data production, storage, and visualization tools are broadly distributed. This paper describes databases and Web resources for the project, which provide support for physical and genetic maps, genome sequence assembly, gene prediction, and integration of EST data. A central project Web site at medicago.org/genome provides access to genome viewers and other resources project-wide, including an Ensembl implementation at medicago.org, physical map and marker resources at mtgenome.ucdavis.edu, and genome viewers at the University of Oklahoma (www.genome.ou.edu), the Institute for Genomic Research (www.tigr.org), and Munich Information for Protein Sequences Center (mips.gsf.de)