Computational identification of piRNA targets on mouse mRNAs

Abstract

Motivation: PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are highly abundant in the germline. One important role of piRNAs is to defend genome integrity by guiding PIWI proteins to silence transposable elements (TEs), which have a high potential to cause deleterious effects on their host. The mechanism of piRNA-mediated post-transcriptional silencing was also observed to affect mRNAs, suggesting that piRNAs might play a broad role in gene expression regulation. However, there has been no systematic report with regard to how many protein-coding genes might be targeted and regulated by piRNAs. Results: We trained a support vector machine classifier based on a combination of Miwi CLIP-Seq-derived features and position-derived features to predict the potential targets of piRNAs on mRNAs in the mouse. Reanalysis of a published microarray dataset suggested that the expression level of the 2587 protein-coding genes predicted as piRNA targets showed significant upregulation as a whole after abolishing the slicer activity of Miwi, supporting the conclusion that they are subject to piRNA-mediated regulation.