Genome-wide identification of Drought-responsive Regulatory Coding and Non-coding Transcripts from Oryza sativa L. by deep RNA sequencing

Abiotic environmental stresses cause serious economic losses in agriculture. These stresses include temperature extremes, high salinity and drought. To isolate drought-responsive novel coding and noncoding genes, we used the next generation sequencing method from three rice cultivars (wild type nipponbare, nipponbare AP2 transgenic plants, wild type vandana). 36 NGS data of mRNA-seq, small RNA-seq, riboZero-seq were analyzed. For the analyses of these data we constructed a TF-TG (Transcription Factor-Target Gene) network and an ap2 rooted cascading tree. Using these networks and tress we isolated lincRNAs, differentially expressed miRNAs and their targets. We identified several drought stress-related novel/function unknown coding transcripts (transcription factors and functional genes) and non-coding transcripts (small noncoding transcripts such as microRNA and long noncoding transcripts) from these database analyses and have constructed databases of drought stress-related coding and noncoding transcripts Overall design: Identification of drought-responsive Regulatory Coding and Non-coding Transcripts from rice by deep RNA sequencing