In Silico Identification of Conserved MiRNAs from Physcomitrella patens ESTs and their Target Characterization
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Published:2018-12-06
Issue:1
Volume:14
Page:33-42
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ISSN:1574-8936
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Container-title:Current Bioinformatics
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language:en
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Short-container-title:CBIO
Author:
Hajieghrari Behzad1, Farrokhi Naser1, Goliaei Bahram2, Kavousi Kaveh3
Affiliation:
1. Department of Plant Sciences & Biotechnology, Faculty of Life Sciences & Biotechnology, Shahid Beheshti University G.C., Evin, Tehran, P.O. Box 19839-4716, Iran 2. Departments of Biophysics and Bioinformatics laboratories, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, P.O.Box 13145-1365, Iran 3. Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, P.O.Box 13145-1365, Iran
Abstract
Background:
MicroRNAs (miRNAs) are groups of small non-protein-coding endogenous
single stranded RNAs with approximately 18-24 nucleotides in length. High evolutionary sequence conservation
of miRNAs among plant species and availability of powerful computational tools allow identification
of new orthologs and paralogs.
Methods:
New conserved miRNAs in P. patens were found by EST-based homology search approaches.
All candidates were screened according to a series of miRNA filtering criteria. Unigene, DFCI Gene
Index (PpspGI) databases and psRNATarget algorithm were applied to identify target transcripts using
P. patens putative conserved miRNA sequences.
Results:
Nineteen conserved P. patens miRNAs were identified. The sequences were homologous to
known reference plant mature miRNA from 10 miRNA families. They could be folded into the typical
miRNA secondary structures. RepeatMasker algorithm demonstrated that ppt-miR2919e and pptmiR1533
had simple sequence repeats in their sequences. Target sites (49 genes) were identified for 7
out of 19 miRNAs. GO and KEGG analysis of targets indicated the involvement of some in important
multiple biological and metabolic processes.
Conclusion:
The majority of the registered miRNAs in databases were predicted by computational approaches
while many more have remained unknown. Due to the conserved nature of miRNAs in plant
species from closely to distantly related, homology search-based approaches between plants species
could lead to the identification of novel miRNAs in other plant species providing baseline information
for further search about the biological functions and evolution of miRNAs.
Publisher
Bentham Science Publishers Ltd.
Subject
Computational Mathematics,Genetics,Molecular Biology,Biochemistry
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