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Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.
Nature Genetics ( IF 31.7 ) Pub Date : 2017-Dec-01 , DOI: 10.1038/ng.3984
Robin M Meyers , Jordan G Bryan , James M McFarland , Barbara A Weir , Ann E Sizemore , Han Xu , Neekesh V Dharia , Phillip G Montgomery , Glenn S Cowley , Sasha Pantel , Amy Goodale , Yenarae Lee , Levi D Ali , Guozhi Jiang , Rakela Lubonja , William F Harrington , Matthew Strickland , Ting Wu , Derek C Hawes , Victor A Zhivich , Meghan R Wyatt , Zohra Kalani , Jaime J Chang , Michael Okamoto , Kimberly Stegmaier , Todd R Golub , Jesse S Boehm , Francisca Vazquez , David E Root , William C Hahn , Aviad Tsherniak

The CRISPR-Cas9 system has revolutionized gene editing both at single genes and in multiplexed loss-of-function screens, thus enabling precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, previous studies have reported that a gene-independent antiproliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, thereby leading to false-positive results 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. In our efforts to define a cancer dependency map, we performed genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines and applied CERES to this data set. We found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sgRNA libraries. We further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.

中文翻译:

拷贝数效应的计算校正提高了CRISPR-Cas9必需性筛选在癌细胞中的特异性。

CRISPR-Cas9系统彻底改变了单个基因和多重功能丧失筛选中的基因编辑,从而实现了精确的基因组规模鉴定,这些基因对于癌细胞的增殖和存活至关重要。但是,以前的研究报道,Cas9介导的DNA裂解的基因非依赖性抗增殖作用混淆了对遗传依赖性的测量,从而导致拷贝数扩增区域的假阳性结果。我们开发了CERES,一种计算方法,可从CRISPR-Cas9必需性筛选中评估基因依赖性水平,同时考虑拷贝数特异性效应。在定义癌症依赖图的过程中,我们对342个癌细胞系进行了基因组规模的CRISPR-Cas9必需性筛选,并将CERES应用于该数据集。我们发现,对于该数据集和使用不同sgRNA文库进行的先前发表的筛查,CERES减少了假阳性结果并估计了sgRNA活性。在CERES校正之后,我们进一步证明了此筛查集合的效用,用于识别特定于癌症类型的漏洞。
更新日期:2017-11-10
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