The MICdb (Microsatellites database) (http://www.cdfd.org.in/micas) is a comprehensive relational database of non-redundant microsatellites extracted from fully sequenced genomes. The current version (2.0) of the database is an enhanced and upgraded version compiled from 287 viral genomes as well as 129 prokaryotic genomes belonging to different phylogenetic groups and is loaded with tools and textual information so as to provide insights into structural and functional aspects of microsatellites. This database has been linked to MICAS2.0, the Web-based Microsatellite Analysis Server. MICAS provides an user-friendly front-end to systematically extract data on microsatellite tracts from hosted genomes. The database contains the following information pertaining to the microsatellites: The regions (coding/non-coding) containing microsatellite tracts, the frequencies of their occurrences, the size and the number of repeating motifs and the sequences of the tracts. Users are facilitated to query the database for details of microsatellite locations with respect to the protein coding/non-coding regions. Protein coding regions after translation are annotated with secondary structural information and positions of microsatellite tracts are shown in order to provide an insight into the possible structural changes due to microsatellite polymorphism. In the case of microsatellites occurring in the non-coding regions graphical illustrations are provided to show relative position of the microsatellite tracts with respect to the upstream and downstream coding regions. This will help in investigations on possible regulatory roles of microsatellites occurring close to protein coding regions (upstream or downstream). Sufficient textual information has been provided to help user navigation through the database and links to GenBank and Swissprot are provided to enhance information content pertaining to microsatellites. An interface to Autoprimer, a primer design program, has been provided to every microsatellite tract to compute suitable primers for PCR.
We thank Miss Sushma for assisting in the design of the Autoprimer software. VBS greatfully acknowledges the Council of Scientific and Industrial Research (CSIR), Govt. of India, for the Junior Research Fellowship. HAN and JN gratefully acknowledge, respectively the core-grant from CDFD and an extramural grant from the Department of Biotechnology (DBT), Govt. of India.