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Updated: Jan 18, 2026

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen
Published on: May 24, 2017
Structural probing of RNA hairpins quantifies protein occupancy on RNA and links it to function in human cells
Abby R Thurm1, Tanya H Nguyen2, Jesus Damian Torres Campos2
1Biophysics Program, Stanford University School of Medicine, Stanford, CA 94305.
Abstract:
RNA structures that form inside living cells influence processes ranging from translation to RNA decay, many of which are controlled by RNA-binding proteins (RBPs). Because RBP specificity depends on both local RNA structure and sequence motifs, traditional pulldown-based methods often obscure the structural context of bound RNAs. Here, a quantitative framework based on dimethyl sulfate mutational profiling and sequencing (DMS-MaPseq) is introduced that jointly measures RNA structure and protein binding at single-nucleotide resolution in human cells, enabling estimation of effective RNA-protein affinities and fractional occupancy directly in cells. Application of this approach to a 1,600-member library of MS2 hairpin mutants reveals that RNA folding is the strongest determinant of MS2 coat protein (MCP) recognition, and that stable MS2 structures must form for MCP to bind its target sequence. MCP also shows strong preference for its consensus loop sequence while displaying minimal dependence on stem length beyond ten base pairs or on stem GC content. Incorporation of an inducible degron fused to MCP allows precise tuning of intracellular protein concentrations analogous to those of many endogenous RBPs and show that DMS reactivity changes can be used to infer binding specificities across a subsaturating regime. A quantitative occupancy framework further shows that inferred fraction-bound values accurately predict how efficiently MCP fused to a downregulatory-domain drives RNA degradation. Together, these results establish a generalizable approach for measuring RBP-RNA affinities with structural resolution in living cells, dissecting how sequence and structure contribute to RBP recognition, and quantitatively linking occupancy to functional output.
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