PRAS: Predicting functional targets of RNA binding proteins based on CLIP-seq peaks

Jianan Lin, Yuping Zhang, Wayne N. Frankel, Zhengqing Ouyang, Dina Schneidman-Duhovny
<span title="2019-08-19">2019</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="" style="color: black;">PLoS Computational Biology</a> </i> &nbsp;
RNA-protein interaction plays important roles in post-transcriptional regulation. Recent advancements in cross-linking and immunoprecipitation followed by sequencing (CLIP-seq) technologies make it possible to detect the binding peaks of a given RNA binding protein (RBP) at transcriptome scale. However, it is still challenging to predict the functional consequences of RBP binding peaks. In this study, we propose the Protein-RNA Association Strength (PRAS), which integrates the intensities and
more &raquo; ... sitions of the binding peaks of RBPs for functional mRNA targets prediction. We illustrate the superiority of PRAS over existing approaches on predicting the functional targets of two related but divergent CELF (CUGBP, ELAV-like factor) RBPs in mouse brain and muscle. We also demonstrate the potential of PRAS for wide adoption by applying it to the enhanced CLIP-seq (eCLIP) datasets of 37 RNA decay related RBPs in two human cell lines. PRAS can be utilized to investigate any RBPs with available CLIP-seq peaks. PRAS is freely available at
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1371/journal.pcbi.1007227</a> <a target="_blank" rel="external noopener" href="">pmid:31425505</a> <a target="_blank" rel="external noopener" href="">pmcid:PMC6716675</a> <a target="_blank" rel="external noopener" href="">fatcat:evvagihknvfnnfddpsvh6vf2ii</a> </span>
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