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CicArMiSatDB: the chickpea microsatellite database.

Doddamani D, Katta MA, Khan AW, Agarwal G, Shah TM, Varshney RK - BMC Bioinformatics (2014)

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India. r.k.varshney@cgiar.org.

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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Simple SSR search result displaying chromosome co-ordinates, motif type, primers and other information.
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Figure 3: Simple SSR search result displaying chromosome co-ordinates, motif type, primers and other information.

Mentions: 4. On the basis of genic and non-genic SSRs.Advanced search is implemented by combining 2 or more options of simple search. For example, one can search the simple SSR with the motif “TA” which is reported to be present in the pseudo-molecule number 5 (Ca5). The query result is tabulated with total number of SSRs found in the database along with genomic location as well as primers which could be used for amplification (Figure 3). Validated SSRs reported previously in the literature (1300 in number) have been highlighted with yellow color. Annotation information e.g. gene co-ordinates, orientation of the gene, gene symbols, function, UniProt ID, pathway information, gene ontology ID and gene ontology was also provided. However, in case of search for non-genic SSRs, similar information is displayed along with the details of nearest gene.


CicArMiSatDB: the chickpea microsatellite database.

Doddamani D, Katta MA, Khan AW, Agarwal G, Shah TM, Varshney RK - BMC Bioinformatics (2014)

Simple SSR search result displaying chromosome co-ordinates, motif type, primers and other information.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4230034&req=5

Figure 3: Simple SSR search result displaying chromosome co-ordinates, motif type, primers and other information.
Mentions: 4. On the basis of genic and non-genic SSRs.Advanced search is implemented by combining 2 or more options of simple search. For example, one can search the simple SSR with the motif “TA” which is reported to be present in the pseudo-molecule number 5 (Ca5). The query result is tabulated with total number of SSRs found in the database along with genomic location as well as primers which could be used for amplification (Figure 3). Validated SSRs reported previously in the literature (1300 in number) have been highlighted with yellow color. Annotation information e.g. gene co-ordinates, orientation of the gene, gene symbols, function, UniProt ID, pathway information, gene ontology ID and gene ontology was also provided. However, in case of search for non-genic SSRs, similar information is displayed along with the details of nearest gene.

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India. r.k.varshney@cgiar.org.

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.

Show MeSH