RBPamp: Quantitative Modeling of Protein-RNA Interactions in vitro Predicts in vivo Binding

Abstract

RNA-binding proteins (RBPs) control the processing and function of cellular transcripts to effect post-transcriptional gene regulation. Sequence-specific binding of RBPs to millions of synthetic RNAs has been probed in vitro by RNA Bind-n-Seq (RBNS). Here we describe RBPamp, a bio-physically-based model of protein-RNA interactions and associated algorithm that inferred affinity spectra of 79 diverse human RBPs from RBNS data. RBPamp supports multiple motifs per RBP, models RBP concentration and binding site saturation, and accounts for the effects of RNA secondary structure. RBPamp affinities along transcripts are predictive of in vivo binding, as measured by eCLIP density. For many RBPs, average local eCLIP density increases monotonically with predicted affinity, and the shape of this relationship can suggest free protein concentrations and potential cooperativity. Together, these analyses demonstrate a powerful integrative approach for the quantitative dissection of RBP function.