Genome-aware annotation of CRISPR guides validates targets in variant cell lines and enhances discovery in screens

Abstract

Abstract Background CRISPR-Cas9 technology has revolutionised genetic screens and can inform on gene essentiality and chemo-genetic interactions. It is easily deployed and widely supported with many pooled CRISPR libraries available commercially. However, discrepancies between the reference genomes used in the design of those CRISPR libraries and the cell line under investigation can lead to loss of signal or introduction of bias. The problem is particularly acute when dealing with variant cell lines such as cancer cell lines. Results Here, we present an algorithm, EXOme-guided Re-annotation of nuCleotIde SEquences (Exorcise), which uses sequence search to detect and correct mis-annotations in CRISPR libraries. Exorcise verifies the presence of CRISPR targets in the target genome and applies corrections to CRISPR libraries using existing exome annotations. We applied Exorcise to re-annotate guides in pooled CRISPR libraries available on Addgene and found that libraries designed on a more permissive reference sequence had more mis-annotations. In simulated CRISPR screens, we modelled common mis-annotations and found that they adversely affect discovery of hits in the intermediate range. We then confirmed this by applying Exorcise on datasets from Dependency Map (DepMap) and the DNA Damage Response CRISPR Screen Viewer (DDRcs), where we found improved discovery power upon Exorcise while retaining the strongest hits. Conclusions Pooled CRISPR libraries map guide sequences to genes and these mappings might not be ready to use due to permissive library design or investigating a variant cell line. By re-annotating CRISPR guides, Exorcise focuses CRISPR experiments towards the genome of the cell line under investigation. Exorcise can be applied at the library design stage or the analysis stage and allows post hoc re-analysis of completed screens. It is available under a Creative Commons Zero v1.0 Universal licence at https://github.com/SimonLammmm/exorcise .

Keywords

• Bioinformatics
• CRISPR
• Sequence annotation
• Computational biology
• Software