11. Prediction of drought related transcripts in cotton (Gossypium hirsutum): an in-silico approach
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Abstract
Prediction of candidate transcripts using bioinformatics tools is an exciting domain which saves the time of a researcher. Drought responsive genes were identified using homology method. The known genes from sequenced organisms (like Arabidopsis, rice, etc.) were compared with ESTs of different crops from various databases. Total 177 genes of Arabidopsis and rice with known functions were retrieved from different databases. The genes were classified and their role in drought was characterized on the basis of already available literature. After classification, 110 genes were selected for further studies. mRNA sequences and accession numbers of the 110 drought tolerant genes were retrieved which were analyzed using BLAST tool against ESTs on “NCBI” databases. ESTs in different crops (like cotton, wheat, potato, maize, sorghum, etc.) were found and data regarding ESTs from cotton were retrieved. Total 9096 ESTs were analyzed from NCBI. The 26 short listed genes were analyzed for “Multiple Sequence Alignment” and aligned with ESTs which were identified earlier. They showed considerable homology with ESTs. All the genes were thoroughly searched for their novelty and finally 8 genes were reported as candidate genes responsible for drought stress tolerance.
Keyword: Bioinformatics; Cotton; Drought; ESTs; Transcripts