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Updated: Feb 14, 2026

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
Published on: December 1, 2023
Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor
Abdul Fatah A Samad1, Nazaruddin Nazaruddin1,2, Abdul Munir Abdul Murad1
11School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia.
Abstract:
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.
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