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Genome-Wide Analysis of 24-nt siRNAs Dynamic Variations during Rice Superior and Inferior Grain Filling

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Title
Genome-Wide Analysis of 24-nt siRNAs Dynamic Variations during Rice Superior and Inferior Grain Filling
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0061029
Pubmed ID
Authors

Ting Peng, Yanxiu Du, Jing Zhang, Junzhou Li, Yanxia Liu, Yafan Zhao, Hongzheng Sun, Quanzhi Zhao

Abstract

24 nt-siRNAs are the most abundant small interfering RNAs in rice grains aside from microRNAs. To investigate the roles that 24 nt-siRNAs played in the poor grain filling of rice inferior grains, dynamic variations of 24 nt-siRNAs in inferior grains were compared with those of superior grains by using small RNA deep sequencing technology. The results showed that 24 nt-siRNAs derived from multiple regions of rice genome, and the maintenance of the two strands of 24 nt-siRNA duplex was a non-random process. The amounts of 24 nt-siRNAs declined with the process of grain filling in both superior and inferior grains, but 24 nt-siRNAs in inferior grains was much higher than that of superior grains in each period we sampled. Bioinformatics prediction indicated that 24 nt-siRNAs targeted on more genes involved in most of the known KEGG rice pathways, such as the starch and sucrose biosynthesis pathway. Combined with digital gene expression profiling of target genes, 24 nt-siRNAs mapped on the antisense strands of exons were specifically investigated, but the abundance of 24 nt-siRNAs did not show negative correlations with their corresponding target genes. The results indicated that 24 nt-siRNAs were not involved in down-regulation of target genes. The potential biological meanings for this inconsistency were probably the results of methylation directed gene expression activation, or competition for small RNA stability methylation.

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The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 5%
China 1 5%
Unknown 18 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 40%
Student > Ph. D. Student 3 15%
Professor > Associate Professor 2 10%
Student > Master 2 10%
Student > Bachelor 1 5%
Other 0 0%
Unknown 4 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 55%
Biochemistry, Genetics and Molecular Biology 4 20%
Unknown 5 25%