scRBP infers cell-specific RNA-binding protein regulons from single-cell transcriptomes at gene and isoform resolution

Abstract

Single-cell regulatory network inference remains dominated by transcription factors, despite RNA-binding proteins (RBPs) orchestrating major aspects of transcriptional regulation. We present scRBP, a framework that infers motif-supported RBP regulons from short- and long-read single-cell transcriptomes at gene and isoform resolution, resolves targets by transcript region (5'UTR, CDS, intron, 3'UTR), scores regulon activity in individual cells, and tests common- and rare-variant association against matched empirical nulls. From 20,746 motifs for 616 RBPs, scRBP recovered experimentally defined targets across 223 ENCODE eCLIP datasets at gene and isoform level. Across 30 tissues, transcript-region preferences separated 3'UTR-associated stability factors from intron-dominant splicing regulators. In published genome-scale CRISPRi Perturb-seq data, scRBP-inferred targets were over-represented among genes responding to RBP knockdown (1.4-2.5-fold across 161 RBPs; FDR<2x10-4). Across 6.2 million cells and 50 traits, scRBP prioritized cell-specific post-transcriptional programs linking human genetic risk to development and disease.