title: Predicting the functions of long noncoding RNAs using RNA-seq based on Bayesian network.
abstract: Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent 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 our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We 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, our method can provide comparable predicted functions of lncRNAs. Overall, our 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.
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China ; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang 150086, China.
authors: Yun
authors: Y
authors: Xiao
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Yanling
authors: Y
authors: Lv
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Hongying
authors: H
authors: Zhao
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Yonghui
authors: Y
authors: Gong
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Jing
authors: J
authors: Hu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Feng
authors: F
authors: Li
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Jinyuan
authors: J
authors: Xu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Jing
authors: J
authors: Bai
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Fulong
authors: F
authors: Yu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
authors: Xia
authors: X
authors: Li
mesh_terms: D001483:Base Sequence / Q000235:genetics*; D001499:Bayes Theorem; D020869:Gene Expression Profiling; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D016366:Open Reading Frames / Q000235:genetics; D060066:Protein Interaction Maps / Q000235:genetics*; D012313:RNA / Q000235:genetics; D062085:RNA, Long Noncoding / Q000737:chemistry / Q000235:genetics*; D059467:Transcriptome / Q000235:genetics
chemical_list: D062085:RNA, Long Noncoding; D012313:RNA