Hindawi Publishing Corporation International Journal of Plant Genomics Volume 2008, Article ID 412875, 7 pages doi:10.1155/2008/412875 Research Article TreeGenes: A Forest Tree Genome Database Jill L. Wegrzyn,1 Jennifer M. Lee,2 Brandon R. Tearse,1 and David B. Neale1 1 Department of Plant Sciences, University of California, Davis, CA 95616, USA 2 Department of Evolution and Ecology, University of California, Davis, CA 95616, USA Correspondence should be addressed to David B. Neale, dbneale@ucdavis.edu Received 17 December 2007; Revised 13 June 2008; Accepted 11 July 2008 Recommended by Shizhong Xu The Dendrome Project and associated TreeGenes database serve the forest genetics research community through a curated and integrated web-based relational database. The research community is composed of approximately 2 000 members representing over 730 organizations worldwide. The database itself is composed of a wide range of genetic data from many forest trees with focused eﬀorts on commercially important members of the Pinaceae family. The primary data types curated include species, publications, tree and DNA extraction information, genetic maps, molecular markers, ESTs, genotypic, and phenotypic data. There are currently ten main search modules or user access points within this PostgreSQL database. These access points allow users to navigate logically through the related data types. The goals of the Dendrome Project are to (1) provide a comprehensive resource for forest tree genomics data to facilitate gene discovery in related species, (2) develop interfaces that encourage the submission and integration of all genomic data, and to (3) centralize and distribute existing and novel online tools for the research community that both support and ease analysis. Recent developments have focused on increasing data content, functional annotations, data retrieval, and visualization tools. TreeGenes was developed to provide a centralized web resource with analysis and visualization tools to support data storage and exchange. Copyright © 2008 Jill L. Wegrzyn et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. INTRODUCTION The TreeGenes database is a resource for all forest trees, however work to date has focused on speciﬁc members of the Pinaceae family. Pinaceae is one of eight families of the order Coniferales (conifer) and includes 10 genera and approximately 220 species. Species of Pinaceae are commercially important to the forest industry and are used for building, packaging, and paper products worldwide. Because of the very large size and complexity of the conifer genomes (10–40 Gb) [1], greater emphasis has been placed on the expressed portion of the genome. This has been achieved through EST and large-scale resequencing projects. The principal species represented include six members of the genus Pinus (taeda, elliottii, radiata, pinaster, sylvestris and lambertiana), two species from other genera of the Pinaceae (Picea abies and Pseudotsuga menzeisii), and one member of another family of conifer (Cryptomeria japonica Cupressaceae). Recent work has also focused on integrating resources for members of Populus and Eucalyptus. Devel- oping genetic resources for these organisms improve the genetic understanding individual member species within the same families or genera. The rapid rate in which genetic data is being generated from large-scale EST and resequencing projects has required corresponding growth in relational databases and associated computational tools. The ability to combine data from diﬀerent sources facilitates interpretation and potentially allows stronger inferences to be made. When information from several diﬀerent databases is required, the assembly of data into a format suitable for querying is a challenge. The development of systems for the integration and combined analysis of diverse data remains a priority in bioinformatics. The TreeGenes database helps researchers eﬃciently analyze, access, integrate, and apply the data. This paper will navigate through the Dendrome (http://dendrome.ucdavis.edu/) and TreeGenes (http://dendrome.ucdavis.edu/treegenes/) interfaces as well as the types of data that can be accessed through these resources.