Large-scale map of RNA-binding protein interactomes across the mRNA life cycle.

mRNAs interact with RNA-binding proteins (RBPs) throughout their processing and maturation. While efforts have assigned RBPs to RNA substrates, less exploration has leveraged protein-protein interactions (PPIs) to study proteins in mRNA life-cycle stages. We generated an RNA-aware, RBP-centric PPI map across the mRNA life cycle in human cells by immunopurification-mass spectrometry (IP-MS) of ∼100 endogenous RBPs with and without RNase, augmented by size exclusion chromatography-mass spectrometry (SEC-MS). We identify 8,742 known and 20,802 unreported interactions between 1,125 proteins and determine that 73% of the IP-MS-identified interactions are RNA regulated. Our interactome links many proteins, some with unknown functions, to specific mRNA life-cycle stages, with nearly half associated with multiple stages. We demonstrate the value of this resource by characterizing the splicing and export functions of enhancer of rudimentary homolog (ERH), and by showing that small nuclear ribonucleoprotein U5 subunit 200 (SNRNP200) interacts with stress granule proteins and binds cytoplasmic RNA differently during stress.

Decoding protein-RNA interactions using CLIP-based methodologies.

Protein-RNA interactions are central to all RNA processing events, with pivotal roles in the regulation of gene expression and cellular functions. Dysregulation of these interactions has been increasingly linked to the pathogenesis of human diseases. High-throughput approaches to identify RNA-binding proteins and their binding sites on RNA - in particular, ultraviolet crosslinking followed by immunoprecipitation (CLIP) - have helped to map the RNA interactome, yielding transcriptome-wide protein-RNA atlases that have contributed to key mechanistic insights into gene expression and gene-regulatory networks. Here, we review these recent advances, explore the effects of cellular context on RNA binding, and discuss how these insights are shaping our understanding of cellular biology. We also review the potential therapeutic applications arising from new knowledge of protein-RNA interactions.

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

Protocol to process crosslinking and immunoprecipitation data into annotated binding sites.

Here, we present a protocol for using Skipper, a pipeline designed to process crosslinking and immunoprecipitation (CLIP) data into annotated binding sites. We describe steps for partitioning annotated transcript regions and fitting data to a beta-binomial model to call windows of enriched binding. From raw CLIP data, we detail how users can map reproducible RNA-binding sites to call enriched windows and perform downstream analysis. This protocol supports optional customizations for different use cases. For complete details on the use and execution of this protocol, please refer to Boyle et al.1.

A super-enhancer-regulated RNA-binding protein cascade drives pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy in need of new therapeutic options. Using unbiased analyses of super-enhancers (SEs) as sentinels of core genes involved in cell-specific function, here we uncover a druggable SE-mediated RNA-binding protein (RBP) cascade that supports PDAC growth through enhanced mRNA translation. This cascade is driven by a SE associated with the RBP heterogeneous nuclear ribonucleoprotein F, which stabilizes protein arginine methyltransferase 1 (PRMT1) to, in turn, control the translational mediator ubiquitin-associated protein 2-like. All three of these genes and the regulatory SE are essential for PDAC growth and coordinately regulated by the Myc oncogene. In line with this, modulation of the RBP network by PRMT1 inhibition reveals a unique vulnerability in Myc-high PDAC patient organoids and markedly reduces tumor growth in male mice. Our study highlights a functional link between epigenetic regulation and mRNA translation and identifies components that comprise unexpected therapeutic targets for PDAC.