Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

Robin M. Meyers(Broad Institute), Jordan Bryan(Broad Institute), James M. McFarland(Broad Institute), Barbara A. Weir(Broad Institute), Ann E. Sizemore(Broad Institute), Han Xu(Broad Institute), Neekesh V. Dharia(Broad Institute), Phillip G. Montgomery(Broad Institute), Glenn S. Cowley(Broad Institute), Sasha Pantel(Broad Institute), Amy Goodale(Broad Institute), Yenarae Lee(Broad Institute), Levi D. Ali(Broad Institute), Guozhi Jiang(Broad Institute), Rakela Lubonja(Broad Institute), William F. Harrington(Broad Institute), Matthew R. Strickland(Broad Institute), Ting Wu(Broad Institute), Derek Hawes(Broad Institute), Victor Zhivich(Broad Institute), Meghan Wyatt(Broad Institute), Zohra Kalani(Broad Institute), Jaime J. Chang(Broad Institute), Michael Okamoto(Broad Institute), Todd R. Golub(Broad Institute), Jesse S. Boehm(Broad Institute), Francisca Vázquez(Broad Institute), David E. Root(Broad Institute), William C. Hahn(Broad Institute), Aviad Tsherniak(Broad Institute)
bioRxiv (Cold Spring Harbor Laboratory)
July 10, 2017
Cited by 46Open Access
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Abstract

The CRISPR-Cas9 system has revolutionized gene editing both on single genes and in multiplexed loss-of-function screens, enabling precise genome-scale identification of genes essential to proliferation and survival of cancer cells. However, previous studies reported that an anti-proliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, particularly in the setting of copy number gain 1-4 . We performed genome-scale CRISPR-Cas9 essentiality screens on 342 cancer cell lines and found that this effect is common to all lines, leading to false positive results when targeting genes in copy number amplified regions. We developed CERES, a computational method to estimate gene dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy-number-specific effect, as well as variable sgRNA activity. We applied CERES to sets of screens performed with different sgRNA libraries and found that it reduces false positive results and provides meaningful estimates of sgRNA activity. As a result, the application of CERES improves confidence in the interpretation of genetic dependency data from CRISPR-Cas9 essentiality screens of cancer cell lines.


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