Quantitative predictions of protein interactions with long noncoding RNAs

Cirillo, Davide

doi:https://doi.org/10.34810/data428

Quantitative predictions of protein interactions with long noncoding RNAs

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Cirillo, D. Quantitative predictions of protein interactions with long noncoding RNAs. Universitat Pompeu Fabra; 2016. doi: 10.34810/data428

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Abstract

Long noncoding RNAs (lncRNAs, which comprise 68% of the human transcriptome with average length of 1,000 nt) interact with various RNA-binding proteins (RBPs) to mediate cellular functions. Here we introduce Global Score as a tool to predict protein interactions with lncRNAs (http://service.tartaglialab.com/new_submission/globalscore). We used enhanced CLIP (eCLIP) to test the binding of the lncRNA Xist to the RBPs HnrnpK (Global Score of 0.99), Ptbp1 (0.99), Lbr (0.79), HnrnpU (Saf-A) (0.66), Spen (Sharp) (0.59) and negative control Dkc1 (0.01). Global Score prediction correlates with the eCLIP binding profile (Pearson correlation = 0.93). As for the binding sites, Spen and HnrnpK, Ptbp1, and Lbr interact respectively with Xist A, B, and E repeats and adjacent regions, while HnrnpU binds across the whole transcript, and Dkc1 does not interact with Xist.