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Bioinformatics. 2018 Dec 1;34(23):4095-4101. doi: 10.1093/bioinformatics/bty450.

Improved design and analysis of CRISPR knockout screens.

Chen CH1,2,3, Xiao T1,4, Xu H1,2,5, Jiang P1,2, Meyer CA1,2, Li W1,2,6,7, Brown M1,4, Liu XS1,2.

Author information

1
Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
2
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA, USA.
3
Biological and Biomedical Science Program, Harvard Medical School, Boston, MA, USA.
4
Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
5
Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA.
6
Center for Genetic Medicine Research, Children's National Health System, Washington, DC, USA.
7
Department of Genomics and Precision Medicine, The George Washington School of Medicine and Health Sciences, Washington, DC, USA.

Abstract

Motivation:

Genome-wide clustered, regularly interspaced, short palindromic repeat (CRISPR)-Cas9 screen has been widely used to interrogate gene functions. However, the rules to design better libraries beg further refinement.

Results:

We found single guide RNA (sgRNA) outliers are characterized by higher G-nucleotide counts, especially in regions distal from the PAM motif and are associated with stronger off-target activities. Furthermore, using non-targeting sgRNAs as negative controls lead to strong bias, which can be mitigated by using sgRNAs targeting multiple 'safe harbor' regions. Custom-designed screens confirmed our findings and further revealed that 19 nt sgRNAs consistently gave the best signal-to-noise ratio. Collectively, our analysis motivated the design of a new genome-wide CRISPR/Cas9 screen library and uncovered some intriguing properties of the CRISPR-Cas9 system.

Availability and implementation:

The MAGeCK workflow is available open source at https://bitbucket.org/liulab/mageck_nest under the MIT license.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
29868757
PMCID:
PMC6247926
DOI:
10.1093/bioinformatics/bty450
[Indexed for MEDLINE]
Free PMC Article

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