Interface-guided phenotyping of coding variants in the transcription factor RUNX1

Kivilcim Ozturk; Rebecca Panwala; Jeanna Sheen; Kyle Ford; Nathan Jayne; Andrew Portell; Dong-Er Zhang; Stephan Hutter; Torsten Haferlach; Trey Ideker; Prashant Mali; Hannah Carter

doi:10.1016/j.celrep.2024.114436

Interface-guided phenotyping of coding variants in the transcription factor RUNX1

Cell Rep. 2024 Jul 23;43(7):114436. doi: 10.1016/j.celrep.2024.114436. Epub 2024 Jul 4.

Authors

Affiliations

¹ Division of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA.
² Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
³ School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
⁴ School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
⁵ Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
⁶ MLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, 81377 Munich, Germany.
⁷ Division of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
⁸ Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA. Electronic address: pmali@ucsd.edu.
⁹ Division of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA. Electronic address: hkcarter@health.ucsd.edu.

Abstract

Single-gene missense mutations remain challenging to interpret. Here, we deploy scalable functional screening by sequencing (SEUSS), a Perturb-seq method, to generate mutations at protein interfaces of RUNX1 and quantify their effect on activities of downstream cellular programs. We evaluate single-cell RNA profiles of 115 mutations in myelogenous leukemia cells and categorize them into three functionally distinct groups, wild-type (WT)-like, loss-of-function (LoF)-like, and hypomorphic, that we validate in orthogonal assays. LoF-like variants dominate the DNA-binding site and are recurrent in cancer; however, recurrence alone does not predict functional impact. Hypomorphic variants share characteristics with LoF-like but favor protein interactions, promoting gene expression indicative of nerve growth factor (NGF) response and cytokine recruitment of neutrophils. Accessible DNA near differentially expressed genes frequently contains RUNX1-binding motifs. Finally, we reclassify 16 variants of uncertain significance and train a classifier to predict 103 more. Our work demonstrates the potential of targeting protein interactions to better define the landscape of phenotypes reachable by missense mutations.

Keywords: CP: Genomics; CP: Molecular biology; Perturb-seq; RNA-seq; cancer; coding variant; interface; protein-protein interaction; single-cell; transcription factor.

MeSH terms

Binding Sites
Cell Line, Tumor
Core Binding Factor Alpha 2 Subunit* / genetics
Core Binding Factor Alpha 2 Subunit* / metabolism
Humans
Mutation / genetics
Mutation, Missense
Phenotype
Single-Cell Analysis / methods

Substances

Core Binding Factor Alpha 2 Subunit
RUNX1 protein, human

Abstract

MeSH terms

Substances

Grants and funding