Volume 16, Issue 4 (12-2021)                   MGj 2021, 16(4): 349-361 | Back to browse issues page

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Abstract:   (295 Views)
The structures from which mature microRNA molecules can be derived (i.e., pri-microRNA and pre-microRNA) have special properties distinguishing them from similar molecules and make them identifiable for enzymes and processors. These properties are mostly influenced by the characteristics of the secondary structure of the RNA molecule. Therefore, several algorithms have been designed to predict the secondary structure of polynucleotide sequences. CTAnalyzer is an algorithm aimed to digitalize the characteristics of RNA secondary structures and categorize these structures using key properties in identifying microRNA molecules. In the current research, CTAnalyzer, by defining adequate filters and rulesets, was used to examine and categorize the derived secondary structures from the genome sequence of Azadirachta indica. The aim of this study was to investigate the efficiency of CTAnalyzer in identifying the structural details of double-stranded RNA and categorizing them based on their structural properties. For this purpose, a similarity alignment was conducted between known viridiplantae mature microRNAs and the whole genome sequence of A. indica using BLASTn algorithm. Following the bidirectional elongation for 80217 identified regions across A. indica genome with adequate homology and also the exclusion of coding sequences, the secondary structure prediction procedure was carried out for the remaining 38067 sequences. The agreed values of criteria for microRNA secondary structures was defined in the software and could to identify candidate microRNA sequences. According to the results obtained from CTAnalyzer, out of all the 566754 evaluated secondary structures, 482 (~%0.08) structures with all properties accepted for microRNAs were identified.
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Type of Study: Applicable | Subject: Subject 01
Received: 2021/04/13 | Accepted: 2021/11/14 | Published: 2022/01/1

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