Co-profiling of in situ RNA-protein interactions and transcriptome in single cells and tissues [bulk RNA-seq]

RNA-binding proteins (RBPs) are essential regulators of RNA fate and function. A long-standing challenge in studying RBP regulation has been mapping RNA interactomes within the dynamic transcriptomic landscape, especially in single-cell contexts and primary tissues. Here we introduce MAPIT-seq (modification added to RBP interacting transcript-sequencing), which uses an antibody-directed editing strategy to map genome-wide in situ RBP–RNA interactions and gene expression concurrently. We demonstrate MAPIT-seq's robustness across multiple RBPs and systematically analyze RNA substrates associated with core polycomb repressive complex 2 (PRC2) components. MAPIT-seq is also applicable to frozen tissue sections, enabling the mapping of RBP roles during brain development. Importantly, we develop high-throughput single-cell MAPIT-seq (scMAPIT-seq) to reveal cell stage-specific RBP regulation. In summary, MAPIT-seq expands multi-omics profiling, providing an effective framework to study post-transcriptional regulation in dynamic biological processes and clinically relevant scenarios. Overall design: We developed Modification Adjacent to RNA-binding Protein Interaction Targets Sequencing (MAPIT-seq), a versatile method for in situ RNA-protein interaction profiling. Initial validation was performed in YTHDF2-FLAG-overexpressing HeLa cells, followed by optimization for target detection of endogenous protein G3BP1 in HEK293T cells. We refined formaldehyde crosslinking conditions and pAG-deaminase constructs to enhance specificity and sensitivity. Then, we evaluated its general applicability by extending to additional canonical RBPs and further selected RBFOX2 and PUM1, two RBPs with well-defined recognition sequences, for an in-depth evaluation of MAPIT-seq resolution. Demonstrating remarkable sensitivity, we scaled MAPIT-seq down to 500 cells, a 1000-fold reduction from the initial 500,000-cell protocol. We further advanced the technique to a high-throughput single-cell format, uncovering cell cycle-specific G3BP1 targets and revealing heterogeneity in RNA-protein interactions at single-cell resolution.