Increasing the performance of pooled CRISPR–Cas9 drop-out screening

• Published in: Scientific reports Vol. 6; no. 1; p. 31782
• Main Authors: Cross, Benedict C. S., Lawo, Steffen, Archer, Caroline R., Hunt, Jessica R., Yarker, Joanne L., Riccombeni, Alessandro, Little, Annette S., McCarthy, Nicola J., Moore, Jonathan D.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.08.2016; Nature Publishing Group
• Subjects: 38/47; 38/77; 49/23; 631/154/555; 631/1647/2163; 631/208/191; 631/208/69; 631/67/68; Base Sequence; Cell Line, Tumor; CRISPR-Cas Systems; Gene Editing - methods; Gene Targeting - methods; Genetic Engineering - methods; Genetic Testing - methods; HEK293 Cells; HL-60 Cells; Humanities and Social Sciences; Humans; multidisciplinary; Reproducibility of Results; RNA, Guide, CRISPR-Cas Systems - genetics; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep31782

Components of the type II CRISPR–Cas complex in bacteria have been used successfully in eukaryotic cells to facilitate rapid and accurate cell line engineering, animal model generation and functional genomic screens. Such developments are providing new opportunities for drug target identification and validation, particularly with the application of pooled genetic screening. As CRISPR–Cas is a relatively new genetic screening tool, it is important to assess its functionality in a number of different cell lines and to analyse potential improvements that might increase the sensitivity of a given screen. To examine critical aspects of screening quality, we constructed ultra-complex libraries containing sgRNA sequences targeting a collection of essential genes. We examined the performance of screening in both haploid and hypotriploid cell lines, using two alternative guide design algorithms and two tracrRNA variants in a time-resolved analysis. Our data indicate that a simple adaptation of the tracrRNA substantially improves the robustness of guide loss during a screen. This modification minimises the requirement for high numbers of sgRNAs targeting each gene, increasing hit scoring and creating a powerful new platform for successful screening.