Prediction of piRNAs using transposon interaction and a support vector machine

• Published in: BMC bioinformatics Vol. 15; no. 1; p. 419
• Main Authors: Wang, Kai, Liang, Chun, Liu, Jinding, Xiao, Huamei, Huang, Shuiqing, Xu, Jianhua, Li, Fei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 30.12.2014; BioMed Central
• Subjects: Algorithms; Animals; Bioinformatics; Biosynthesis; Chilo suppressalis; Classification; Colleges & universities; Communities; Computer science; Drosophila; Drosophila melanogaster - genetics; Drosophila Proteins - genetics; Gene expression; Genomes; Humans; Insects; Methodology; Methods; Mice; Moths - genetics; Moths - metabolism; Oryza - parasitology; Oryza sativa; Piano; Pianos; Rats; Ribonucleic acids; Rice; RNA; RNA, Small Interfering - genetics; Software; Support Vector Machine; Support vector machines; Transposons; User-Computer Interface
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-014-0419-6

Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNA primarily expressed in germ cells that can silence transposons at the post-transcriptional level. Accurate prediction of piRNAs remains a significant challenge. We developed a program for piRNA annotation (Piano) using piRNA-transposon interaction information. We downloaded 13,848 Drosophila piRNAs and 261,500 Drosophila transposons. The piRNAs were aligned to transposons with a maximum of three mismatches. Then, piRNA-transposon interactions were predicted by RNAplex. Triplet elements combining structure and sequence information were extracted from piRNA-transposon matching/pairing duplexes. A support vector machine (SVM) was used on these triplet elements to classify real and pseudo piRNAs, achieving 95.3 ± 0.33% accuracy and 96.0 ± 0.5% sensitivity. The SVM classifier can be used to correctly predict human, mouse and rat piRNAs, with overall accuracy of 90.6%. We used Piano to predict piRNAs for the rice stem borer, Chilo suppressalis, an important rice insect pest that causes huge yield loss. As a result, 82,639 piRNAs were predicted in C. suppressalis. Piano demonstrates excellent piRNA prediction performance by using both structure and sequence features of transposon-piRNAs interactions. Piano is freely available to the academic community at http://ento.njau.edu.cn/Piano.html .