Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens
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.
Show 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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