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  • Functional classification o...
    Kirk, Jessime M; Kim, Susan O; Inoue, Kaoru; Smola, Matthew J; Lee, David M; Schertzer, Megan D; Wooten, Joshua S; Baker, Allison R; Sprague, Daniel; Collins, David W; Horning, Christopher R; Wang, Shuo; Chen, Qidi; Weeks, Kevin M; Mucha, Peter J; Calabrese, J Mauro

    Nature genetics, 10/2018, Letnik: 50, Številka: 10
    Journal Article

    The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.