Expressed sequence tag-based prediction of putative genes responsive to drought tolerance in rice (Oryza sativa) using in silico approach

Abstract

In present genomic era, rapid genetic gains can be achieved by exploitation of novel genes associated with the trait of interest employing molecular breeding and genetic engineering. In the present study genes responsible for drought stress in rice 10746 expressed sequence tags (ESTs), expressed under drought stress condition were retrieved from the NCBI. The downloaded ESTs were clustered and assembled into 1120 contigs and 5559 singletones using CAP3 programme. The contigs were further subjected to identification of transcription factor, a total of 62 putative transcription factors were identified and sorted into 17 putative TF families. The contigs were subjected to BLASTX in NCBI to identify unique sequence which were further aligned to Oryza sativa Indica Group (ASM465v1) in gramene database using BLAT to retrieve the upstream and downstream sequences for putative gene identification. The retrieved sequences were analysed for transcription start site, PolyA tails and coding sequences which are essential features of gene using online tool fsgene. The present study found that, 46 contigs out of 1120 contigs has key gene structure and was considered as putative novel genes which may contribute to the drought tolerance in indica rice. These genes may be useful in development of drought tolerant varieties through smart breeding