Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Sean A. Misek, Aaron Fultineer, Jeremie Kalfon, Javad Noorbakhsh, Isabella Boyle, Priyanka Roy, Joshua Dempster, Lia Petronio, Katherine Huang, Alham Saadat, Thomas Green, Adam Brown, John G. Doench, David E. Root, James M. McFarland, Rameen Beroukhim () and Jesse S. Boehm ()
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Sean A. Misek: Broad Institute of MIT and Harvard
Aaron Fultineer: Broad Institute of MIT and Harvard
Jeremie Kalfon: Broad Institute of MIT and Harvard
Javad Noorbakhsh: Broad Institute of MIT and Harvard
Isabella Boyle: Broad Institute of MIT and Harvard
Priyanka Roy: Broad Institute of MIT and Harvard
Joshua Dempster: Broad Institute of MIT and Harvard
Lia Petronio: Broad Institute of MIT and Harvard
Katherine Huang: Broad Institute of MIT and Harvard
Alham Saadat: Broad Institute of MIT and Harvard
Thomas Green: Broad Institute of MIT and Harvard
Adam Brown: Broad Institute of MIT and Harvard
John G. Doench: Broad Institute of MIT and Harvard
David E. Root: Broad Institute of MIT and Harvard
James M. McFarland: Broad Institute of MIT and Harvard
Rameen Beroukhim: Broad Institute of MIT and Harvard
Jesse S. Boehm: Broad Institute of MIT and Harvard

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract Reducing disparities is vital for equitable access to precision treatments in cancer. Socioenvironmental factors are a major driver of disparities, but differences in genetic variation likely also contribute. The impact of genetic ancestry on prioritization of cancer targets in drug discovery pipelines has not been systematically explored due to the absence of pre-clinical data at the appropriate scale. Here, we analyze data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models to identify ancestry-associated genetic dependencies essential for cell survival. Surprisingly, we find that most putative associations between ancestry and dependency arise from artifacts related to germline variants. Our analysis suggests that for 1.2-2.5% of guides, germline variants in sgRNA targeting sequences reduce cutting by the CRISPR/Cas9 nuclease, disproportionately affecting cell models derived from individuals of recent African descent. We propose three approaches to mitigate this experimental bias, enabling the scientific community to address these disparities.

Date: 2024
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DOI: 10.1038/s41467-024-48957-z

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