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

  • Cell Syst. 2026 Jun 26:101651. doi: 10.1016/j.cels.2026.101651.
Wei He  1 ,  Jen-Wei Huang  2 ,  Yalong Wang  1 ,  Samuel B Hayward  2 ,  Giuseppe Leuzzi  2 ,  Rongjie Fu  1 ,  Shuyue Wang  1 ,  Alina Vaitsiankova  2 ,  Yiwen Chen  3 ,  Mark T Bedford  1 ,  Raphael Guerois  4 ,  Alberto Ciccia  5 ,  Han Xu  6
Affiliations
  • 1. Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA.
  • 2. Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA.
  • 3. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
  • 4. Institute for Integrative Biology of the Cell (I2BC), University of Paris-Saclay, CEA, CNRS, Gif-sur-Yvette, France. Electronic address: [email protected].
  • 5. Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA; Institute for Cancer Genetics, Columbia University Irving Medical Center, New York, NY 10032, USA. Electronic address: [email protected].
  • 6. Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; The Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: [email protected].
PMID: 42361799 DOI: 10.1016/j.cels.2026.101651
Abstract

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.

Keywords
CRISPR; ProTiler-Mut; computational method; mutation-phenotype; tiling mutagenesis screen.
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