Project description:Interactions between RNAs and RNA binding proteins (RBPs) regulate gene expression in eukaryotic cells. RNA-RBP affinities measured in vitro reveal diverse binding specificities, yet approaches to directly compare specificities across RBPs are lacking. Here, we introduce two quantitative metrics: inherent specificity, which measures how selectively an RBP distinguishes its strongest binding motif from all possible motifs, and mutational sensitivity, which assesses tolerance to single nucleotide variations within preferred motifs. Analyzing high-throughput sequencing datasets, we compared these metrics across 100 RBPs in vitro and 27 RBPs in cells, finding strong correlation between in vitro and cellular measurements for RBPs that bind RNA independently of a local structural context. Through CLIP experiments with swapped RNA recognition motifs between a low-specificity RBP (RBM25) and a high-specificity RBP (HNRNPC), we demonstrated that sequence specificity can be transferred between protein contexts. Using these insights, we developed mathematical models showing how RBPs with different specificity profiles compete for binding sites, revealing how variations in inherent specificity and mutational sensitivity influence target selection. Together, our results provide a quantitative framework for modeling RNA-RBP interactions and designing RBPs with targeted specificity.
