Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, researchers from Harbin Medical University present a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of this method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. The researchers found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, this method can provide comparable predicted functions of lncRNAs. Overall, this method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.
- Xiao Y, Lv Y, Zhao H, Gong Y, Hu J, Li F, Xu J, Bai J, Yu F, Li X. (2015) Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network. Biomed Res Int 2015:839590. [article]