A Unified Framework for Systematic Identification of Post-Transcriptional Regulatory Modules [perturb_seq]

RNA-binding proteins (RBPs) are multifunctional regulators of gene expression with complex and context-dependent mechanisms of action, yet the regulatory grammar that underlies RBP-mediated functions remains underexplored. Here, we performed a multi-omic data integration to systematically decipher the context-specific functions of RBPs. First, we report a compendium of in vivo proximity-dependent biotinylation (BioID) datasets of 50 human RBPs, which we used to generate a large-scale map of RBP protein neighborhoods. In parallel, we took advantage of CRISPR-interference with single-cell RNA-seq read-out (Perturb-seq) to capture rich transcriptomic phenotypes downstream of each RBP knockdown. By combining these physical and functional interaction readouts, along with the ENCODE transcriptome-wide atlas of RBP binding sites from eCLIP assays, we generated an integrated map of functional RBP interactions. This map not only captures well-studied post-transcriptional processes, but also reveals numerous previously unknown RBP-mediated regulatory functions. For a number of these cases, we have validated their predicted context-specific RBP functions using biochemical and genetic approaches. By deciphering these complex modes of functional interactions between RBPs, we have taken the first step towards a more comprehensive understanding of post-transcriptional regulatory processes and their underlying molecular grammar. Overall design: We obtained transcriptome-wide gene expression measurements for 68 RBPs (representing a variety of regulatory processes) knockdowns using single-cell RNA sequencing and used the resulting high-dimensional data to systematically delineate genetic interactions between RBPs. Perturb-seq experiment was performed as previously described (Datlinger et al. 2017).