Nature GeneticsGenomicsPeer-reviewed journal article
Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells
Robin M. MeyersiD, Jordan BryaniD, James M. McFarlandiD, Barbara A. Weir, Ann E. SizemoreiD, Han XuiD, Neekesh V. DhariaiD, Philip G. MontgomeryiD, Glenn S. CowleyiD, Sasha Pantel, Amy B. GoodaleiD, Yenarae LeeiD, Levi D. AliiD, Guozhi JiangiD, Rakela Lubonja, William F Harrington, Matthew R. StricklandiD, Ting WuiD, Derek Hawes, Victor Zhivich, Meghan WyattiD, Zohra KalaniiD, Jaime J. Chang, Michael Okamoto, Kimberly StegmaieriD, , Aviad TsherniakiD
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 gain1-4. 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.
- organism: human
- assay: CRISPR screen
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 1,951
- FWCI
- 52.36
- Field percentile
- top 1%
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