Abstract
Off-target effects are well established confounders of CRISPR negative selection screens that impair the identification of essential genomic loci. In particular, non-coding regulatory elements and repetitive regions are often difficult to target with specific gRNAs, effectively precluding the unbiased screening of a large portion of the genome. To address this, we developed CRISPR Specificity Correction (CSC), a computational method that corrects for the effect of off-targeting on gRNA depletion. We benchmark CSC with data from the Cancer Dependency Map and show that it significantly improves the overall sensitivity and specificity of viability screens while preserving known essentialities, particularly for genes targeted by highly promiscuous gRNAs. We believe this tool will further enable the functional annotation of the genome as it represents a robust alternative to the traditional filtering strategy of discarding unspecific guides from the analysis. CSC is an open-source software that can be seamlessly integrated into current CRISPR analysis pipelines.
Highlights
Off-target effects are well established confounders of CRISPR negative selection screens that impair the identification of essential genomic loci
Despite the ongoing efforts to comprehensively discover and annotate genomic features[10,11], a large fraction of them cannot currently be screened for essentiality using conventional CRISPR strategies. This limitation significantly hinders our ability to gain insight into the functional roles of large segments of the genome. It argues for the need for approaches that can be used as alternatives to filtering unspecific gRNAs, analogous to those used for gRNAs targeting amplified genomic regions[12,13]
We set out to develop a computational strategy to correct for the effect of off-targeting on gRNA depletion without the need to filter out unspecific gRNAs
Summary
We set out to develop a computational strategy to correct for the effect of off-targeting on gRNA depletion without the need to filter out unspecific gRNAs. To validate our strategy, we focused our analysis on loss-of-function screens from the 19Q4 release of the Project Achilles Avana dataset from the Cancer Dependency Map initiative[2,12], performed across 26 distinct cellular lineages (Fig. 1a). In agreement with previous studies[8,9], gRNAs with low specificities were on average more depleted from the population during viability screens, often beyond the levels observed for gRNAs targeting known essential genes (Fig. 2a, left, Supplementary Fig. 1a–d) This observation held true even for guides that had a single perfect target site in the genome (H0 = 1) but increasing numbers of off-targets with mismatches (Fig. 2b, Supplementary Fig. 1c). Gene Set Enrichment Analysis (GSEA) showed that genes targeted by unspecific gRNAs were significantly enriched in high BF values, as the number of unspecific gRNAs per gene increased or as the a
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