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Open Access Research article

The prediction of the porcine pre-microRNAs in genome-wide based on support vector machine (SVM) and homology searching

Zhen Wang12, Kan He123, Qishan Wang12, Yumei Yang12 and Yuchun Pan12*

Author Affiliations

1 School of Agriculture and Biology, Department of Animal Science, Shanghai Jiao Tong University, Shanghai, 200240, PR China

2 Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai, 200240, PR China

3 Department of Biology, Faculty of Science, Hong Kong Baptist University, Hong Kong, China

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BMC Genomics 2012, 13:729  doi:10.1186/1471-2164-13-729

Published: 27 December 2012

Abstract

Background

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by targeting mRNAs for translation repression or mRNA degradation. Although many miRNAs have been discovered and studied in human and mouse, few studies focused on porcine miRNAs, especially in genome wide.

Results

Here, we adopted computational approaches including support vector machine (SVM) and homology searching to make a global scanning on the pre-miRNAs of pigs. In our study, we built the SVM-based porcine pre-miRNAs classifier with a sensitivity of 100%, a specificity of 91.2% and a total prediction accuracy of 95.6%, respectively. Moreover, 2204 novel porcine pre-miRNA candidates were found by using SVM-based pre-miRNAs classifier. Besides, 116 porcine pre-miRNA candidates were detected by homology searching.

Conclusions

We identified the porcine pre-miRNA in genome-wide through computational approaches by utilizing the data sets of pigs and set up the porcine pre-miRNAs library which may provide us a global scanning on the pre-miRNAs of pigs in genome level and would benefit subsequent experimental research on porcine miRNA functional and expression analysis.

Keywords:
Porcine; Pre-miRNA; SVM; Homology searching