Massive parallel sequencing of mRNA in identification of unannotated salinity stress-inducible transcripts in rice (Oryza sativa L.)

Background: Microarray technology is limited to monitoring the expression of previously annotated genes that have corresponding probes on the array. Computationally annotated genes have not fully been validated, because ESTs and full-length cDNAs cannot cover entire transcribed regions. Here, mRNA-Seq (an Illumina cDNA sequencing application) was used to monitor whole mRNAs of salinity stress-treated rice tissues. Results: Thirty-six-base-pair reads from whole mRNAs were mapped to the rice genomic sequence: 72.0% to 75.2% were mapped uniquely to the genome, and 5.0% to 5.7% bridged exons. From the piling up of short reads mapped on the genome, a series of programs (Bowtie, TopHat, and Cufflinks) comprehensively predicted 51,301 (shoot) and 54,491 (root) transcripts, including 2,795 (shoot) and 3,082 (root) currently unannotated in the Rice Annotation Project database. Of these unannotated transcripts, 995 (shoot) and 1,052 (root) had ORFs similar to those encoding the amino acid sequences of functional proteins in a BLASTX search against UniProt and RefSeq databases. Among the unannotated genes, 213 (shoot) and 436 (root) were differentially expressed in response to salinity stress. Sequence-based and array-based measurements of the expression ratios of previously annotated genes were highly correlated. Conclusion: Unannotated transcripts were identified on the basis of the piling up of mapped reads derived from mRNAs in rice. Some of these unannotated transcripts encoding putative functional proteins were expressed differentially in response to salinity stress.