The functional complexity of the rice transcriptome is not yet fully elucidated despite many studies having reported the use of DNA microarrays. Next-generation DNA sequencing technologies provide a powerful approach for mapping and quantifying the transcriptome, termed RNA sequencing (RNA-seq). In this study, we applied RNA-seq to globally sample transcripts of the cultivated rice Oryza sativa indica and japonica subspecies for resolving the whole-genome transcription profiles. We identified 15,708 novel transcriptional active regions (nTARs), of which 51.7% have no homolog to public protein data and more than 63% are putative single exon transcripts, which are highly different from protein-coding genes (<20%). We found that ~48% rice genes show alternative splicing patterns, a percentage considerably higher than previous estimations. On the basis of the available rice gene models, 83.1% (46,472 genes) of the current rice gene models were validated by RNA-seq, and 6,228 genes were identified to be extended at the 5′ and/or 3′ ends by at least 50 bp. Comparative transcriptome analysis demonstrated that 3,464 genes exhibited differential expression patterns. The ratio of SNPs with nonsynonymous/synonymous mutations was nearly 1:1.06. In total, we interrogated and compared transcriptomes of the two rice subspecies to reveal the overall transcriptional landscape at maximal resolution.
Lu T, Lu G, Fan D, Zhu C, Li W, Zhao Q, Feng Q, Zhao Y, Guo Y, Li W, Huang X, Han B. (2010) Function annotation of rice transcriptome at single nucleotide resolution by RNA-seq. Genome Res [Epub ahead of print]. [article]