RNAi/CRISPR Screens: from a Pool to a Valid Hit. Issue 1 (January 2019)

• Record Type: Journal Article
• Authors: Schuster, Anne; Erasimus, Hélène; Fritah, Sabrina; Nazarov, Petr V.; van Dyck, Eric; Niclou, Simone P.; Golebiewska, Anna
• Is Part Of: Trends in biotechnology. Volume 37:Issue 1(2019)
• Page Start: 38
• Page End: 55
• Publication Date: 2019-01
• Subjects: RNAi -- CRISPR/Cas9 -- CRISPRi -- CRISPRa -- library pooled screens -- essential genes; Biotechnology -- Periodicals; Biochemical engineering -- Periodicals; Genetic engineering -- Periodicals; Industrial microbiology -- Periodicals; 660.605
• DOI: 10.1016/j.tibtech.2018.08.002
• Languages: English
• ISSNs: 0167-7799

Abstract

Abstract : High-throughput genetic screens interfering with gene expression are invaluable tools to identify gene function and phenotype-to-genotype interactions. Implementing such screens in the laboratory is challenging, and the choice between currently available technologies based on RNAi and CRISPR/Cas9 (CRISPR-associated protein 9) is not trivial. Identifying reliable candidate hits requires a streamlined experimental setup adjusted to the specific biological question. Here, we provide a critical assessment of the various RNAi/CRISPR approaches to pooled screens and discuss their advantages and pitfalls. We specify a set of best practices for key parameters enabling a reproducible screen and provide a detailed overview of analysis methods and repositories for identifying the best candidate gene hits. Highlights: Pooled genetic screens based on RNAi and CRISPR technologies are a powerful approach for high-throughput interrogation of loss- or gain-of-function and phenotype-to-genotype correlations. Several CRISPR technologies are applicable for pooled screens, allowing for a wide range of genetic perturbations and mutagenesis beyond classical RNAi-based gene knockdown. Stringent experimental design, appropriate controls and careful library selection are essential to identify valid hits. Appropriate library representation throughout the screening procedure is key to avoid false positives/negatives. Different bioinformatics pipelines can be applied to data analysis, and their combination may lead to increased specificity of selected hits.