bioRxiv · 10.1101/2025.06.30.662330
Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens
Abstract
Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes. To advance efforts toward a reference human GI network, we developed the quantitative Genetic Interaction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in different query mutants constructed in a single human cell line. We found surprising prevalent systematic variation unrelated to GIs in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging [~]40 control screens in wild-type cells and half a billion differential fitness effect measurements, we developed a pipeline for CRISPR screen data processing and normalization to correct these artifacts and measure accurate, quantitative GIs. We also comprehensively characterized GI reproducibility by characterizing 4 - 5 biological replicates for [~]125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.
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Billmann, M., Costanzo, M., Rahman, M., Chan, K., Tong, A., Ward, H. N., Hassan, A. Z., Zhang, X., Brown, K. R., Rohde, T., Shaw, A. H., Ross, C., van Leeuwen, J., Aregger, M., Lawson, K., Mair, B., Mero, P., Usaj, M., Andrews, B. J., Boone, C., Moffat, J., Myers, C. L.. 2025-06-30. Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens. https://doi.org/10.1101/2025.06.30.662330
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