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Identification of Novel Oryza sativa miRNAs in Deep Sequencing-Based Small RNA Libraries of Rice Infected with Rice Stripe Virus

Overview of attention for article published in PLOS ONE, October 2012
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Title
Identification of Novel Oryza sativa miRNAs in Deep Sequencing-Based Small RNA Libraries of Rice Infected with Rice Stripe Virus
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0046443
Pubmed ID
Authors

Weixia Guo, Gentu Wu, Fei Yan, Yuwen Lu, Hongying Zheng, Lin Lin, Hairu Chen, Jianping Chen

Abstract

MicroRNAs (miRNAs) play essential regulatory roles in the development of eukaryotes. Methods based on deep-sequencing have provided a powerful high-throughput strategy for identifying novel miRNAs and have previously been used to identify over 100 novel miRNAs from rice. Most of these reports are related to studies of rice development, tissue differentiation, or abiotic stress, but novel rice miRNAs related to viral infection have rarely been identified. In previous work, we constructed and pyrosequenced the small RNA (sRNA) libraries of rice infected with Rice stripe virus and described the character of the small interfering RNAs (siRNA) derived from the RSV RNA genome. We now report the identification of novel miRNAs from the abundant sRNAs (with a minimum of 100 sequencing reads) in the sRNA library of RSV-infected rice. 7 putative novel miRNAs (pn-miRNAs) whose precursor sequences have not previously been described were identified and could be detected by Northern blot or RT-PCR, and were recognized as novel miRNAs (n-miRNAs). Further analysis showed that 5 of the 7 n-miRNAs were up-expressed while the other 2 n-miRNAs were down-expressed in RSV-infected rice. In addition, 23 pn-miRNAs that were newly produced from 19 known miRNA precursors were also identified. This is first report of novel rice miRNAs produced from new precursors related to RSV infection.

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Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 2%
France 1 2%
Unknown 56 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 24%
Researcher 13 22%
Student > Master 7 12%
Student > Doctoral Student 5 9%
Professor > Associate Professor 3 5%
Other 7 12%
Unknown 9 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 60%
Biochemistry, Genetics and Molecular Biology 6 10%
Environmental Science 1 2%
Physics and Astronomy 1 2%
Medicine and Dentistry 1 2%
Other 1 2%
Unknown 13 22%