2010
DOI: 10.1371/journal.pone.0010698
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Identification of miRNA from Porphyra yezoensis by High-Throughput Sequencing and Bioinformatics Analysis

Abstract: BackgroundmiRNAs are a class of non-coding, small RNAs that are approximately 22 nucleotides long and play important roles in the translational level regulation of gene expression by either directly binding or cleaving target mRNAs. The red alga, Porphyra yezoensis is one of the most important marine economic crops worldwide. To date, only a few miRNAs have been identified in green unicellar alga and there is no report about Porphyra miRNAs.Methodology/Principal FindingsTo identify miRNAs in Porphyra yezoensis… Show more

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Cited by 82 publications
(65 citation statements)
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“…As already mentioned, candidate miRNAs have been identified or predicted in four algal species, C. reinhardtii (41,61,102), P. yezoensis (52), P. tricornutum (22,55), and E. siliculosus (17). To address the biological role(s) of these miRNAs, computational approaches have been used to predict their putative targets in three algae (17,52,61,102). However, since the genomes of these species are not fully annotated or are not available (candidate miRNAs were matched only to expressed sequence tags for P. yezoensis) and/or many genes have no known function, it is difficult to draw a conclusion as to whether predicted miRNA targets have any functional bias.…”
Section: Biological Roles Of Rna-mediated Silencing In Algaementioning
confidence: 99%
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“…As already mentioned, candidate miRNAs have been identified or predicted in four algal species, C. reinhardtii (41,61,102), P. yezoensis (52), P. tricornutum (22,55), and E. siliculosus (17). To address the biological role(s) of these miRNAs, computational approaches have been used to predict their putative targets in three algae (17,52,61,102). However, since the genomes of these species are not fully annotated or are not available (candidate miRNAs were matched only to expressed sequence tags for P. yezoensis) and/or many genes have no known function, it is difficult to draw a conclusion as to whether predicted miRNA targets have any functional bias.…”
Section: Biological Roles Of Rna-mediated Silencing In Algaementioning
confidence: 99%
“…Likewise, endogenous noncoding sRNAs have been identified, by sRNA library sequencing, in the red alga Porphyra yezoensis (52), the diatom P. tricornutum (22), and the brown alga Ectocarpus siliculosus (17). Based on the ability of genomic sRNA loci (or of the corresponding transcripts) to fold back into hairpin secondary structures resembling miRNA precursors, miRNA candidates have been predicted in these three algal species (17,52,55). Interestingly, with the possible exception of candidate miRNAs identified in P. yezoensis (52), there appears to be little conservation of particular miRNA genes among algae or with those encoded in the genomes of land plants or animals (17,18,61,102 (16,22,24,42,43,44,76,77,79,87).…”
Section: Rnai Machinery In Algaementioning
confidence: 99%
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“…Because of its high specificity and efficiency, RNA interference has been proven to be an invaluable tool for analyzing the biological function of the target gene and adjusting the metabolism process considerably by sequence-specific knockdown (Cerutti et al, 2011;Schramke andAllshire, 2005, Waterhouse et al, 1998). A wide range of core RNAi machinery components, which promotes the transient gene silencing and stable gene repression experiments, was identified in the marine algae, red alga P. yezoensis (Liang et al, 2010), green alga D. salina (Jia et al, 2009), diatom P. tricornutum (De Riso et al, 2009, T. pseudonana (Armbrust et al, 2004), and brown alga Ectocarpus siliculosus (Cock et al, 2010). To investigate the potential of double-stranded RNA interference with gene expression in D. salina, a plasmid was constructed to express hairpin RNA containing sequences homologous to phytoene desaturase genes that were transformed into D. salina by electroporation for the transient suppression of gene expression (Sun et al, 2008).…”
Section: Rna Interference Technologymentioning
confidence: 99%