In silico mining of EST-SSRs from putative drought stress-responsive candidate genes and polymorphism survey in selected maize inbred lines
ShivNarayan Sharma
In silico mining of EST-SSRs from putative drought stress-responsive candidate genes and polymorphism survey in selected maize inbred lines - Mexico, DF (Mexico) CIMMYT : 2010 - p. 304-308
Maize production and productivity is severely affected worldwide by water deficit stress, particularly in countries like India where nearly 80 percent of maize is cultivated under rainfed conditions. We have undertaken in silico mining of microsatellite/SSR markers from the EST sequences of putative drought stress-responsive candidate genes in maize. The EST sequences from the NCBI database were processed and clustered to reduce redundancy to develop consensus sequences. The consensus sequences were searched for SSR motifs. In total, 930 di- to hexa-repeat motif SSR markers were identified, including 132 from EST-SSR sequences that are homologs of functionally characterized genes involved in dehydration responses. The mined data was validated using tBLASTn and tBLASTx searches of the retrieved regions against the databases at NCBI, built inside the MaizeEST project. Validated sequences were used for designing primers (through PBC Bioinformatics) for an initial set of 132 ESTSSRs. These SSRs were used for analysis of SSR polymorphisms in a set of 24 maize inbred lines with significant differences in responses to drought stress in India. The genic SSRs, identified based on putative drought-stress responsive genes in maize, can be potentially for various purposes, including genetic diversity analysis, comparative mapping and marker-assisted selection (MAS).
English
978-979-1159-41-8
Bioinformatics
Drought
EST-SSRs
functional diversity
Maize
In silico mining of EST-SSRs from putative drought stress-responsive candidate genes and polymorphism survey in selected maize inbred lines - Mexico, DF (Mexico) CIMMYT : 2010 - p. 304-308
Maize production and productivity is severely affected worldwide by water deficit stress, particularly in countries like India where nearly 80 percent of maize is cultivated under rainfed conditions. We have undertaken in silico mining of microsatellite/SSR markers from the EST sequences of putative drought stress-responsive candidate genes in maize. The EST sequences from the NCBI database were processed and clustered to reduce redundancy to develop consensus sequences. The consensus sequences were searched for SSR motifs. In total, 930 di- to hexa-repeat motif SSR markers were identified, including 132 from EST-SSR sequences that are homologs of functionally characterized genes involved in dehydration responses. The mined data was validated using tBLASTn and tBLASTx searches of the retrieved regions against the databases at NCBI, built inside the MaizeEST project. Validated sequences were used for designing primers (through PBC Bioinformatics) for an initial set of 132 ESTSSRs. These SSRs were used for analysis of SSR polymorphisms in a set of 24 maize inbred lines with significant differences in responses to drought stress in India. The genic SSRs, identified based on putative drought-stress responsive genes in maize, can be potentially for various purposes, including genetic diversity analysis, comparative mapping and marker-assisted selection (MAS).
English
978-979-1159-41-8
Bioinformatics
Drought
EST-SSRs
functional diversity
Maize