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

Biology Direct

Michiaki Hamada¹  Junichi Iwakiri²  Goro Terai³ 

[1] Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University;Graduate School of Frontier Sciences, University of Tokyo;INTEC Inc;

关键词: RNA-RNA interaction;    Long non-coding RNA;    Tissue specificity;    RNA-seq;    Computational prediction;   

DOI  :  10.1186/s13062-017-0183-4

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown