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MiREvo: an integrative microRNA evolutionary analysis platform for next-generation sequencing experiments.

Authors :
Ming Wen
Yang Shen
Suhua Shi
Tian Tang
Source :
BMC Bioinformatics. 2012, Vol. 13 Issue 1, p140-149. 10p. 4 Diagrams, 1 Chart, 1 Graph.
Publication Year :
2012

Abstract

Background: MicroRNAs (miRNAs) are small (~19-24nt) non-coding RNAs that play important roles in various biological processes. To date, the next-generation sequencing (NGS) technology has been widely used to discover miRNAs in plants and animals. Although evolutionary analysis is important to reveal the functional dynamics of miRNAs, few computational tools have been developed to analyze the evolution of miRNA sequence and expression across species, especially the newly emerged ones, Results: We developed miREvo, an integrated software platform with a graphical user interface (GUI), to process deep-sequencing data of small RNAs and to analyze miRNA sequence and expression evolution based on the multiple-species whole genome alignments (WGAs). Three major features are provided by miREvo: (i) to identify novel miRNAs in both plants and animals, based on a modified miRDeep algorithm, (ii) to detect miRNA homologs and measure their pairwise evolutionary distances among multiple species based on a WGA, and (iii) to profile miRNA expression abundances and analyze expression divergence across multiple species (small RNA libraries). Moreover, we demonstrated the utility of miREvo with Illumina data sets from Drosophila melanogaster and Arabidopsis, respectively. Conclusion: This work presents an integrated pipline, miREvo, for exploring the expressional and evolutionary dynamics of miRNAs across multiple species. MiREvo is standalone, modular, and freely available at http://evolution. sysu.edu.cn/software/mirevo.htm under the GNU/GPL license. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*MICRORNA
*COMPUTER software

Details

Language :
English
ISSN :
14712105
Volume :
13
Issue :
1
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
79827150
Full Text :
https://doi.org/10.1186/1471-2105-13-140