LncTar: a tool for predicting the RNA targets of long noncoding RNAs

TLDR

Long noncoding RNAs are abundant and regulate diverse biological processes, notably through RNA–RNA interactions. Given the large number of lncRNAs, predicting their RNA targets at scale is urgently needed for comprehensive functional understanding. LncTar predicts RNA targets of lncRNAs at large scale by computationally identifying RNA–RNA interactions, and its accuracy was evaluated on ten experimentally supported lncRNA–mRNA pairs. LncTar correctly predicted 80 % of the tested lncRNA–mRNA pairs, demonstrating reliable accuracy and efficiency for rapid target identification. LncTar is freely available at http://www.cuilab.cn/lnctar.

Abstract

Long noncoding RNAs (lncRNAs) represent a big category of noncoding RNA molecules, and increasing studies have shown that they play important roles in various critical biological processes. They show a diversity of functions through diverse mechanisms, among which regulating RNA molecules is one of the most popular ones. Given the big number of lncRNAs, it becomes urgent and important to predict the RNA targets of lncRNAs in a large scale for the comprehensive understanding of lncRNA functions and action mechanisms. Although several methods have been developed to predict RNA–RNA interactions, none of them can be used to predict the RNA targets of lncRNAs in a large scale. Here we presented a tool, LncTar, which shows the ability to efficiently predict the RNA targets of lncRNAs in a large scale. To test the accuracy of LncTar, we applied it to 10 experimentally supported lncRNA–mRNA interactions. As a result, LncTar successfully predicted 8 (80%) of the 10 lncRNA–mRNA pairs, suggesting that LncTar has a reliable accuracy. Finally, we believe that LncTar could be an efficient tool for the fast identification of the RNA targets of lncRNAs. LncTar is freely available at http://www.cuilab.cn/lnctar.