CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) are two workhorse technologies for loss-of-function studies, yet direct comparisons between the two are scant relative to their widespread adoption. Here, we establish benchmarking libraries for Cas9-based CRISPRko and CRISPRi screens using Perturb-seq as the read-out. For both modalities, we observe consistent transcriptional signatures among cells with the same genes perturbed, strong evidence of on-target signal. We also examine tradeoffs between modalities: while CRISPRi guides demonstrate heightened rates of off-target activity, we also observe artifacts stemming from the cellular response to double-stranded breaks with the use of CRISPRko. The libraries and analyses presented here will be a useful benchmarking and de-risking resource for any group preparing for a large-scale Perturb-seq screen.
Laura M Drepanos, Berta Escude Velasco, Abigail J Chase et al.· bioRxiv· 1 citation
CRISPR interference (CRISPRi) is a powerful technology for studying loss-of-function phenotypes, enabling transient and reversible control of gene expression without the introduction of double-stranded DNA breaks. The cost of conducting large-scale CRISPR screens necessitates the selection of effective and specific single-guide RNAs for the design of compact libraries. While several genome-wide CRISPRi-Cas9 libraries have been created, updates to transcript annotations, the generation of higher-resolution chromatin accessibility datasets, and the development of newer on-target prediction models motivate an updated CRISPRi library design approach. Here, we generate large CRISPRi datasets tiling essential and nonessential genes. We compare the performance of multiple KRAB domain systems, develop an updated CRISPRi-specific on-target scoring scheme, and quantitatively characterize off-target effects associated with seed-sequence patterns. We leverage these findings to design an optimized CRISPRi-Cas9 library, Katsano, and validate its performance with genome-wide viability screens.
Smriti Srikanth, Fengyi Zheng, Laura M Drepanos et al.· Cell Genomics· 0 citations