Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells

By Daesik Kim, Sangsu Bae, Jeongbin Park, Eunji Kim, Seokjoong Kim, Hyeontaek Yu, Jinha Hwang, Jong-il Kim, Jin-Soo Kim. Nature Methods, 2015

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CRISPR/Cas9 in Genome Editing and Beyond. (2016, methodology): “Different strategies have been developed to improve Sp Cas9 specificity: optimizing the sgRNA design (68, 142, 152); using paired nCas9s (5, 76–78), paired dCas9-FokI nucleases (153, 154) (Figure 1b), enhanced Sp Cas9 with improved specificity (155), shorter (17–18 bp) sgRNAs or sgRNAs with two unpa”
DeepCRISPR: optimized CRISPR guide RNA design by deep learning (2018, methodology): “The off-target profile dataset contained two different cell types: 293-related cell lines (18 sgRNAs) and K562 t (12 sgRNAs) [6, 22, 24 – 27, 44].”
Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR (2016, methodology): “2 % [2, 3, 33] (Additional file 1: Table S1; [26, 28] did not report sensitivity).”
WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system (2015, neutral): “Experimental analysis indicates that Cas9-based genome editing could have wide spread off-target effects, resulting in a significant level of nonspecific editing at other unintended genomic loci [14, 18-20].”