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

Cell Reports (Jul 2024)

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

Affiliations

Kivilcim Ozturk: 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
Rebecca Panwala: Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
Jeanna Sheen: School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
Kyle Ford: Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
Nathan Jayne: 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
Andrew Portell: Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
Dong-Er Zhang: Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA
Stephan Hutter: MLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, 81377 Munich, Germany
Torsten Haferlach: MLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, 81377 Munich, Germany
Trey Ideker: 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
Prashant Mali: Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Corresponding author
Hannah Carter: 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; Corresponding author

Journal volume & issue: Vol. 43, no. 7
p. 114436

Abstract

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Summary: 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.

Published in Cell Reports

ISSN: 2211-1247 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Biology (General)
Website: http://www.cell.com/cell-reports/home

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