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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.

Show MeSH
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.
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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.

Mentions: Identified SSRs have been further classified in the database into simple and compound SSRs based on the complexity of the motif. Simple SSRs were found to be abundant in the genome constituting to 89.6% (43,273) of the total SSRs. In contrast, compound SSRs amount to only 10.4% (5,025) of the SSRs (Figure 2B). The most abundant simple SSR is di-SSRs (26,477) followed by the tri-SSRs (13,729), tetra-SSRs (2,368), penta-SSRs (421) and finally hexa-SSRs (278) (Figure 2A). The longest simple SSR was found to be hexa SSR with 49 repeating CAATTT motifs. The highest number of repeats was observed to be 132 in AT motif, (AT)132. Of the simple SSRs, the most frequently occurring motifs were AT (10,935, 41%) in di-SSRs, and AAT (1,820, 13.25%) in tri-SSRs.The SSRs classified based on genomic features (genic or non-genic) show that they occur predominantly in the non-genic regions (46,088, 95.42%) (Figure 2 C). On the other hand, the SSRs in genic regions were low (2,210, 4.57%) in number.


CicArMiSatDB: the chickpea microsatellite database.

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

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.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

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.
Mentions: Identified SSRs have been further classified in the database into simple and compound SSRs based on the complexity of the motif. Simple SSRs were found to be abundant in the genome constituting to 89.6% (43,273) of the total SSRs. In contrast, compound SSRs amount to only 10.4% (5,025) of the SSRs (Figure 2B). The most abundant simple SSR is di-SSRs (26,477) followed by the tri-SSRs (13,729), tetra-SSRs (2,368), penta-SSRs (421) and finally hexa-SSRs (278) (Figure 2A). The longest simple SSR was found to be hexa SSR with 49 repeating CAATTT motifs. The highest number of repeats was observed to be 132 in AT motif, (AT)132. Of the simple SSRs, the most frequently occurring motifs were AT (10,935, 41%) in di-SSRs, and AAT (1,820, 13.25%) in tri-SSRs.The SSRs classified based on genomic features (genic or non-genic) show that they occur predominantly in the non-genic regions (46,088, 95.42%) (Figure 2 C). On the other hand, the SSRs in genic regions were low (2,210, 4.57%) in number.

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