LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns

// Yongsheng Li 1,* , Hong Chen 1,* , Tao Pan 1,* , Chunjie Jiang 1 , Zheng Zhao 1 , Zishan Wang 1 , Jinwen Zhang 1 , Juan Xu 1 and Xia Li 1 1 College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Nangang, Harbin, Heilongjiang, China * These authors should be regarded as joint First Authors Correspondence to: Xia Li, email: // Juan Xu, email: // Keywords : long non-coding RNA, chromatin pattern, lncRNA ontology, lncRNA functions, integrated model Received : July 06, 2015 Accepted : September 05, 2015 Published : September 22, 2015 Abstract Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome profiling. We propose an integrative method for genome-wide functional predictions of lncRNAs by combining chromatin states data with gene expression patterns. We first validated the method using protein-coding genes with known function annotations. Our validation results indicated that our integrative method performs better than co-expression analysis, and is accurate across different conditions. Next, by applying the integrative model genome-wide, we predicted the probable functions for more than 97% of human lncRNAs. The putative functions inferred by our method match with previously annotated by the targets of lncRNAs. Moreover, the linkage from the cellular processes influenced by cancer-associated lncRNAs to the cancer hallmarks provided a “lncRNA point-of-view” on tumor biology. Our approach provides a functional annotation of the lncRNAs, which we developed into a web-based application, LncRNA Ontology, to provide visualization, analysis, and downloading of lncRNA putative functions.