Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor transcriptome
In current era, majority of microRNA (miRNA) are being discovered through computational approaches which are more confined towards model plants. Here, for the first time, we have described the identification and characterization of novel miRNA in a non-model plant, Persicaria minor (P. minor) using computational approach. Unannotated sequences from deep sequencing were analyzed based on previous well-established parameters. Around 24 putative novel miRNAs were identified from 6,417,780 reads of the unannotated sequence which represented 11 unique putative miRNA sequences. PsRobot target prediction tool was deployed to identify the target transcripts of putative novel miRNAs. Most of the predicted target transcripts (mRNAs) were known to be involved in plant development and stress responses. Gene ontology showed that majority of the putative novel miRNA targets involved in cellular component (69.07%), followed by molecular function (30.08%) and biological process (0.85%). Out of 11 unique putative miRNAs, 7 miRNAs were validated through semi-quantitative PCR. These novel miRNAs discoveries in P. minor may develop and update the current public miRNA database.
KeywordsDeep sequencing In silico Novel miRNA Transcriptomic library Persicaria minor
The author, Abdul Fatah A. Samad is sponsored by MyBrain 15 under MyPhD scholarship from Ministry of Higher Education (Malaysia). This research was supported by Dana Impak Perdana (DIP-2015-018).
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Conflict of interest
There are no conflicts to declare by authors.
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