LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns
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Yongsheng Li1,*, Hong Chen1,*, Tao Pan1,*, Chunjie Jiang1, Zheng Zhao1, Zishan Wang1, Jinwen Zhang1, Juan Xu1 and Xia Li1
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
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
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.
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