Evaluation of RNAi and CRISPR technologies by large-scale gene expression profiling in the Connectivity Map.

• Main Authors: Ian Smith, Peyton G Greenside, Ted Natoli, David L Lahr, David Wadden, Itay Tirosh, Rajiv Narayan, David E Root, Todd R Golub, Aravind Subramanian, John G Doench
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2017-11-01
• Series: PLoS Biology
• Online Access: http://europepmc.org/articles/PMC5726721?pdf=render

The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss-of-function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that microRNA (miRNA)-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a consensus gene signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 single guide RNAs (sgRNAs) in 6 cells lines and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function.