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Computational Assessment of the Cooperativity between RNA Binding Proteins and MicroRNAs in Transcript Decay

Author(s): Jiang, P; Singh, Mona; Coller, HA

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Abstract: Transcript degradation is a widespread and important mechanism for regulating protein abundance. Two major regulators of transcript degradation are RNA Binding Proteins (RBPs) and microRNAs (miRNAs). We computationally explored whether RBPs and miRNAs cooperate to promote transcript decay. We defined five RBP motifs based on the evolutionary conservation of their recognition sites in 3′UTRs as the binding motifs for Pumilio (PUM), U1A, Fox-1, Nova, and UAUUUAU. Recognition sites for some of these RBPs tended to localize at the end of long 3′UTRs. A specific group of miRNA recognition sites were enriched within 50 nts from the RBP recognition sites for PUM and UAUUUAU. The presence of both a PUM recognition site and a recognition site for preferentially co-occurring miRNAs was associated with faster decay of the associated transcripts. For PUM and its co-occurring miRNAs, binding of the RBP to its recognition sites was predicted to release nearby miRNA recognition sites from RNA secondary structures. The mammalian miRNAs that preferentially co-occur with PUM binding sites have recognition seeds that are reverse complements to the PUM recognition motif. Their binding sites have the potential to form hairpin secondary structures with proximal PUM binding sites that would normally limit RISC accessibility, but would be more accessible to miRNAs in response to the binding of PUM. In sum, our computational analyses suggest that a specific set of RBPs and miRNAs work together to affect transcript decay, with the rescue of miRNA recognition sites via RBP binding as one possible mechanism of cooperativity.
Publication Date: 30-May-2013
Electronic Publication Date: 30-May-2013
Citation: Jiang, P, Singh, M, Coller, HA. (2013). Computational Assessment of the Cooperativity between RNA Binding Proteins and MicroRNAs in Transcript Decay. PLoS Computational Biology, 9 (10.1371/journal.pcbi.1003075
DOI: doi:10.1371/journal.pcbi.1003075
Type of Material: Journal Article
Journal/Proceeding Title: PLoS Computational Biology
Version: Final published version. This is an open access article.

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