Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor transcriptome.

Autor: Samad AFA; 1School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia., Nazaruddin N; 1School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia.; 3Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Syiah Kuala, Darussalam, Banda Aceh, 23111 Indonesia., Murad AMA; 1School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia., Jani J; BioEasy Sdn. Bhd. and ScienceVision Sdn. Bhd., Setia Alam, Seksyen U13, 40170 Shah Alam, Selangor Malaysia., Zainal Z; 1School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia.; 2Institute of Systems Biology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia., Ismail I; 1School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia.; 2Institute of Systems Biology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor Malaysia.
Jazyk: angličtina
Zdroj: 3 Biotech [3 Biotech] 2018 Mar; Vol. 8 (3), pp. 136. Date of Electronic Publication: 2018 Feb 15.
DOI: 10.1007/s13205-018-1164-8
Abstrakt: 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.
Competing Interests: Compliance with ethical standardsThere are no conflicts to declare by authors.
Databáze: MEDLINE
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