Computational prediction of lncRNA-mRNA interactionsby integrating tissue specificity in human transcriptome

Junichi Iwakiri, Goro Terai, Michiaki Hamada

Research output: Contribution to journalComment/debatepeer-review

22 Citations (Scopus)

Abstract

Long noncoding RNAs (lncRNAs) play a key role in normal tissue differentiation and cancer development through their tissue-specific expression in the human transcriptome. Recent investigations of macromolecular interactions have shown that tissue-specific lncRNAs form base-pairing interactions with various mRNAs associated with tissue-differentiation, suggesting that tissue specificity is an important factor controlling human lncRNA-mRNA interactions. Here, we report investigations of the tissue specificities of lncRNAs and mRNAs by using RNA-seq data across various human tissues as well as computational predictions of tissue-specific lncRNA-mRNA interactions inferred by integrating the tissue specificity of lncRNAs and mRNAs into our comprehensive prediction of human lncRNA-RNA interactions. Our predicted lncRNA-mRNA interactions were evaluated by comparisons with experimentally validated lncRNA-mRNA interactions (between the TINCR lncRNA and mRNAs), showing the improvement of prediction accuracy over previous prediction methods that did not account for tissue specificities of lncRNAs and mRNAs. In addition, our predictions suggest that the potential functions of TINCR lncRNA not only for epidermal differentiation but also for esophageal development through lncRNA-mRNA interactions. Reviewers: This article was reviewed by Dr. Weixiong Zhang and Dr. Bojan Zagrovic.

Original languageEnglish
Article number15
JournalBiology Direct
Volume12
Issue number1
DOIs
Publication statusPublished - 2017 Jun 8

Keywords

  • Computational prediction
  • Long non-coding RNA
  • RNA-RNA interaction
  • RNA-seq
  • Tissue specificity

ASJC Scopus subject areas

  • Immunology
  • Ecology, Evolution, Behavior and Systematics
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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