Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Highly Accessed Software

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

Ming Wen1, Yang Shen1, Suhua Shi123 and Tian Tang123*

Author affiliations

1 State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, Guangdong, People’s Republic of China

2 The Key Laboratory of Gene Engineering of Ministry of Education, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, Guangdong, People’s Republic of China

3 Guangdong Key Laboratory of Plant Resources, Sun Yat-sen University, Guangzhou, 510275, Guangdong, People’s Republic of China

For all author emails, please log on.

Citation and License

BMC Bioinformatics 2012, 13:140  doi:10.1186/1471-2105-13-140

Published: 21 June 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 webcite under the GNU/GPL license.