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. 2014 Jun 21:15:212.
doi: 10.1186/1471-2105-15-212.

CicArMiSatDB: the chickpea microsatellite database

Dadakhalandar Doddamani, Mohan A V S K Katta, Aamir W Khan, Gaurav Agarwal, Trushar M Shah, Rajeev K Varshney  1
Affiliations

CicArMiSatDB: the chickpea microsatellite database

Dadakhalandar Doddamani et al. BMC Bioinformatics. .

Abstract

Background: Chickpea (Cicer arietinum) is a widely grown legume crop in tropical, sub-tropical and temperate regions. Molecular breeding approaches seem to be essential for enhancing crop productivity in chickpea. Until recently, limited numbers of molecular markers were available in the case of chickpea for use in molecular breeding. However, the recent advances in genomics facilitated the development of large scale markers especially SSRs (simple sequence repeats), the markers of choice in any breeding program. Availability of genome sequence very recently opens new avenues for accelerating molecular breeding approaches for chickpea improvement.

Description: In order to assist genetic studies and breeding applications, we have developed a user friendly relational database named the Chickpea Microsatellite Database (CicArMiSatDB http://cicarmisatdb.icrisat.org). This database provides detailed information on SSRs along with their features in the genome. SSRs have been classified and made accessible through an easy-to-use web interface.

Conclusions: This database is expected to help chickpea community in particular and legume community in general, to select SSRs of particular type or from a specific region in the genome to advance both basic genomics research as well as applied aspects of crop improvement.

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Figures

Figure 1
Figure 1
Database schema of CicArMiSatDB.
Figure 2
Figure 2
Distribution and classification of SSRs in CicArMiSatDB. A) Distribution of SSRs classified according to the motif repeats show the abundance of di and tri-nucleotide motifs. B) SSRs classified into simple and compound SSRs, simple SSRs constitute the majority of SSRs in chickpea genome. C) SSRs classified by their occurrence in genic and non-genic features show predominance of SSRs in non-genic regions.
Figure 3
Figure 3
Simple SSR search result displaying chromosome co-ordinates, motif type, primers and other information.
Figure 4
Figure 4
A GBrowse view displaying genomic features.
See this image and copyright information in PMC

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