TY  - JOUR
A1  - Lu, Tingting
A1  - Lu, Guojun
A1  - Fan, Danlin
A1  - Zhu, Chuanrang
A1  - Li, Wei
A1  - Zhao, Qiang
A1  - Feng, Qi
A1  - Zhao, Yan
A1  - Guo, Yunli
A1  - Li, Wenjun
A1  - Huang, Xuehui
A1  - Han, Bin
T1  - Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq
Y1  - 2010/09/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1238 
EP  - 1249 
DO  - 10.1101/gr.106120.110 
VL  - 20 
IS  - 9 
UR  - http://genome.cshlp.org/content/20/9/1238.abstract 
N2  - 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 >63% are putative single-exon transcripts, which are highly different from protein-coding genes (<20%). We found that ∼48% of 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 6228 genes were identified to be extended at the 5′ and/or 3′ ends by at least 50 bp. Comparative transcriptome analysis demonstrated that 3464 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. 
ER  -