Deciphering protein mutation-phenotype linkages from CRISPR-based tiling mutagenesis screens

CRISPR-based high-throughput mutagenesis screens enable systematic mapping of mutations to phenotypes, yet deciphering mutation-phenotype links remains challenging. Here, we present ProTiler-Mut, a versatile computational framework that leverages tiling mutagenesis screens, which introduce variants across entire protein sequences, to analyze mutation effects at the levels of residues, substructures, and protein-protein interactions (PPIs). Applying ProTiler-Mut to multi-condition base-editing (BE) screens targeting DNA damage response proteins and T cell regulators, we define a separation-of-function (SoF) category beyond the conventional loss-of-function (LoF) and gain-of-function (GoF) classes, where SoF mutations show the strongest enrichment for ClinVar-annotated pathogenic variants. ProTiler-Mut also identifies candidate substructures that enable functional inference of unscreened pathogenic mutations and prioritizes candidate phenotype-associated PPIs potentially disrupted by functional variants. Using ProTiler-Mut, in cells with elevated programmed cell death 1 (PD-1) expression, we identify pathogenic GoF mutations that constitute a substructure that may disrupt mitogen-activated protein kinase (MAPK)1-RSK1 interactions and lead to MAPK activation. Finally, we show that ProTiler-Mut is applicable across different mutagenesis screening platforms. A record of this paper's transparent peer review process is included in the supplemental information.