Comprehensive prediction of lncRNA–RNA interactions in human transcriptome. (January 2016)

• Record Type: Journal Article
• Authors: Terai, Goro; Iwakiri, Junichi; Kameda, Tomoshi; Hamada, Michiaki; Asai, Kiyoshi
• Is Part Of: BMC genomics. Volume 17:Number 1(2016)
• Page Start: 153
• Page End: 164
• Publication Date: 2016-01
• Subjects: RNA–RNA interactions -- Interaction energy -- TINCR -- 1/2-sbsRNA; Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-015-2307-5
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Motivation Recent studies have revealed that large numbers of non-coding RNAs are transcribed in humans, but only a few of them have been identified with their functions. Identification of the interaction target RNAs of the non-coding RNAs is an important step in predicting their functions. The current experimental methods to identify RNA–RNA interactions, however, are not fast enough to apply to a whole human transcriptome. Therefore, computational predictions of RNA–RNA interactions are desirable, but this is a challenging task due to the huge computational costs involved. Results Here, we report comprehensive predictions of the interaction targets of lncRNAs in a whole human transcriptome for the first time. To achieve this, we developed an integrated pipeline for predicting RNA–RNA interactions on the K computer, which is one of the fastest super-computers in the world. Comparisons with experimentally-validated lncRNA–RNA interactions support the quality of the predictions. Additionally, we have developed a database that catalogs the predicted lncRNA–RNA interactions to provide fundamental information about the targets of lncRNAs.