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

in Databases, Other Tools June 13, 2017 4,157 Views

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, University of Tokyo researchers 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 their comprehensive prediction of human lncRNA-RNA interactions. The researchers 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, these predictions suggest that the potential functions of TINCR lncRNA not only for epidermal differentiation but also for esophageal development through lncRNA-mRNA interactions.

Predictions of TINCR-mRNA interactions using skin-specific mRNAs. The skin-specific candidate mRNAs were identified from RNA-seq data derived from the Human Protein Atlas Project (Expression Atlas ID:E-MTAB-2836). A combination of two prediction (ranking) methods (MinEnergy and SumEnergy) and two candidate mRNA sets (initial and tissue specific) were used for the predictions. Experimentally validated TINCR-mRNA interactions (considered as true positives) were used for evaluating the prediction results. The horizontal axis indicates the number of predicted TINCR-mRNA interactions. The vertical axis indicates the number of experimentally validated interactions (i.e., true positives)

Availability – All predicted human lncRNA-RNA interactions are available from the database at: http://rtools.cbrc.jp/cgi-bin/RNARNA/index.pl

Iwakiri J, Terai G, Hamada M. (2017) Computational prediction of lncRNA-mRNA interactions by integrating tissue specificity in human transcriptome. Biol Direct 12(1):15. [article]