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Article

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Title

AmiRNA Designer - new method of artificial miRNA design

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

Year of publication

2016

Published in

Acta Biochimica Polonica

Journal year: 2016 | Journal volume: vol. 63 | Journal number: no. 1

Article type

scientific article

Publication language

english

Keywords
EN
  • artificial miRNA
  • RNAi
  • gene regulation
  • sequence specific
  • thermodynamic profiles
Abstract

EN MicroRNAs (miRNAs) are small non-coding RNAs that have been found in most of the eukaryotic organisms. They are involved in the regulation of gene expression at the post-transcriptional level in a sequence specific manner. MiRNAs are produced from their precursors by Dicer-dependent small RNA biogenesis pathway. Involvement of miRNAs in a wide range of biological processes makes them excellent candidates for studying gene function or for therapeutic applications. For this purpose, different RNA-based gene silencing techniques have been developed. Artificially transformed miRNAs (amiRNAs) targeting one or several genes of interest represent one of such techniques being a potential tool in functional genomics. Here, we present a new approach to amiRNA design, implemented as AmiRNA Designer software. Our method is based on the thermodynamic analysis of the native miRNA/miRNA* and miRNA/target duplexes. In contrast to the available automated tools, our program allows the user to perform analysis of natural miRNAs for the organism of interest and to create customized constraints for the design stage. It also provides filtering of the amiRNA candidates for the potential off-targets. AmiRNA Designer is freely available at http://www.cs.put.poznan.pl/arybarczyk/AmiRNA/.

Pages (from - to)

71 - 77

DOI

10.18388/abp.2015_989

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Full text of article

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Access level to full text

public

Ministry points / journal

15

Impact Factor

1,159

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