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

Journal: Oncotarget
PMID: 26485761

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.

Authors

  • Yongsheng Li
    School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, 150081, China. liyongsheng@ems.hrbmu.edu.cn.
  • Hong Chen
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Tao Pan
    College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China.
  • Chunjie Jiang
    College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Nangang, Harbin, Heilongjiang, China.
  • Zheng Zhao
    College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Nangang, Harbin, Heilongjiang, China.
  • Zishan Wang
    College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Nangang, Harbin, Heilongjiang, China.
  • Jinwen Zhang
    College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Nangang, Harbin, Heilongjiang, China.
  • Juan Xu
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang Province, China. xujuanbiocc@ems.hrbmu.edu.cn.
  • Xia Li
    Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Tsukuba, Ibaraki, Japan.

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