MoccaDB - an integrative database for functional, comparative and diversity studies in the Rubiaceae family.

Full Abstract

BACKGROUND: In the past few years, functional genomics information has been rapidly accumulating on Rubiaceae species and especially on those belonging to the Coffea genus (coffee trees). An increasing number of expressed sequence tag (EST) data and EST- or genomic-derived microsatellite markers have been generated, together with Conserved Ortholog Set (COS) markers. This considerably facilitates comparative genomics or map-based genetic studies through the common use of orthologous loci across different species. Similar genomic information is available for e.g. tomato or potato, members of the Solanaceae family. Since both Rubiaceae and Solanaceae belong to the Euasterids I (lamiids) integration of information on genetic markers would be possible and lead to more efficient analyses and discovery of key loci involved in important traits such as fruit development, quality, and maturation, or adaptation. Our goal was to develop a comprehensive web data source for integrated information on validated orthologous markers in Rubiaceae. DESCRIPTION: MoccaDB is an online MySQL-PHP driven relational database that houses annotated and/or mapped microsatellite markers in Rubiaceae. In its current release, the database stores 638 markers that have been defined on 259 ESTs and 379 genomic sequences. Marker information was retrieved from 11 published works, and completed with original data on 132 microsatellite markers validated in our laboratory. DNA sequences were derived from three Coffea species/hybrids. Microsatellite markers were checked for similarity, in vitro tested for cross-amplification and diversity/polymorphism status in up to 38 Rubiaceae species belonging to the Cinchonoideae and Rubioideae subfamilies. Functional annotation was provided and some markers associated with described metabolic pathways were also integrated. Users can search the database for marker, sequence, map or diversity information through multi-option query forms. The retrieved data can be browsed and downloaded, along with protocols used, using a standard web browser. MoccaDB also integrates bioinformatics tools (CMap viewer and local BLAST) and hyperlinks to related external data sources (NCBI GenBank and PubMed, SOL Genomic Network database). CONCLUSION: We believe that MoccaDB will be extremely useful for all researchers working in the areas of comparative and functional genomics and molecular evolution, in general, and population analysis and association mapping of Rubiaceae and Solanaceae species, in particular.

Author information

Author/s: Plechakova, Olga (O); Tranchant-Dubreuil, Christine (C); Benedet, Fabrice (F); Couderc, Marie (M); Tinaut, Alexandra (A); Viader, Véronique (V); De Block, Petra (P); Hamon, Perla (P); Campa, Claudine (C); de Kochko, Alexandre (A); Hamon, Serge (S); Poncet, Valérie (V);

Affiliation: UMR DIAPC, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. olga.plechakova(-atsign-)ird.fr

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: BMC plant biology (BMC Plant Biol), published in England. (Language: eng)

Reference: 2009-; vol 9 (issue ) : pp 123

Dates: Created 2009/10/13; Completed 2009/11/04;

PMID: 19788737, status: MEDLINE (last retrieval date: 11/4/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.