Dataset Information

Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq.

ABSTRACT: 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 approximately 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.

SUBMITTER: Lu T

PROVIDER: S-EPMC2928502 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq.

Lu Tingting T Lu Guojun G Fan Danlin D Zhu Chuanrang C Li Wei W Zhao Qiang Q Feng Qi Q Zhao Yan Y Guo Yunli Y Li Wenjun W Huang Xuehui X Han Bin B

Genome research 20100713 9

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 1 ...[more]

PMID: 20627892

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Project description:Actinobacillus pleuropneumoniae is the pathogen of porcine contagious pleuropneumoniae, a highly contagious respiratory disease of swine. Although the genome of A. pleuropneumoniae was sequenced several years ago, limited information is available on the genome-wide transcriptional analysis to accurately annotate the gene structures and regulatory elements. High-throughput RNA sequencing (RNA-seq) has been applied to study the transcriptional landscape of bacteria, which can efficiently and accurately identify gene expression regions and unknown transcriptional units, especially small non-coding RNAs (sRNAs), UTRs and regulatory regions. The aim of this study is to comprehensively analyze the transcriptome of A. pleuropneumoniae by RNA-seq in order to improve the existing genome annotation and promote our understanding of A. pleuropneumoniae gene structures and RNA-based regulation. In this study, we utilized RNA-seq to construct a single nucleotide resolution transcriptome map of A. pleuropneumoniae. More than 3.8 million high-quality reads (average length ~90 bp) from a cDNA library were generated and aligned to the reference genome. We identified 32 open reading frames encoding novel proteins that were mis-annotated in the previous genome annotations. The start sites for 35 genes based on the current genome annotation were corrected. Furthermore, 51 sRNAs in the A. pleuropneumoniae genome were discovered, of which 40 sRNAs were never reported in previous studies. The transcriptome map also enabled visualization of 5'- and 3'-UTR regions, in which contained 11 sRNAs. In addition, 351 operons covering 1230 genes throughout the whole genome were identified. The RNA-Seq based transcriptome map validated annotated genes and corrected annotations of open reading frames in the genome, and led to the identification of many functional elements (e.g. regions encoding novel proteins, non-coding sRNAs and operon structures). The transcriptional units described in this study provide a foundation for future studies concerning the gene functions and the transcriptional regulatory architectures of this pathogen.

Project description:BACKGROUND: Clostridium beijerinckii is a prominent solvent-producing microbe that has great potential for biofuel and chemical industries. Although transcriptional analysis is essential to understand gene functions and regulation and thus elucidate proper strategies for further strain improvement, limited information is available on the genome-wide transcriptional analysis for C. beijerinckii. RESULTS: The genome-wide transcriptional dynamics of C. beijerinckii NCIMB 8052 over a batch fermentation process was investigated using high-throughput RNA-Seq technology. The gene expression profiles indicated that the glycolysis genes were highly expressed throughout the fermentation, with comparatively more active expression during acidogenesis phase. The expression of acid formation genes was down-regulated at the onset of solvent formation, in accordance with the metabolic pathway shift from acidogenesis to solventogenesis. The acetone formation gene (adc), as a part of the sol operon, exhibited highly-coordinated expression with the other sol genes. Out of the > 20 genes encoding alcohol dehydrogenase in C. beijerinckii, Cbei_1722 and Cbei_2181 were highly up-regulated at the onset of solventogenesis, corresponding to their key roles in primary alcohol production. Most sporulation genes in C. beijerinckii 8052 demonstrated similar temporal expression patterns to those observed in B. subtilis and C. acetobutylicum, while sporulation sigma factor genes sigE and sigG exhibited accelerated and stronger expression in C. beijerinckii 8052, which is consistent with the more rapid forespore and endspore development in this strain. Global expression patterns for specific gene functional classes were examined using self-organizing map analysis. The genes associated with specific functional classes demonstrated global expression profiles corresponding to the cell physiological variation and metabolic pathway switch. CONCLUSIONS: The results from this work provided insights for further C. beijerinckii strain improvement employing system biology-based strategies and metabolic engineering approaches.

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Dataset Information

Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq.

Publications

Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq.

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