Abstract
CRISPR guide RNA libraries have been iteratively improved to provide increasingly efficient reagents, although their large size is a barrier for many applications. We design an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9) by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other CRISPR-Cas9 libraries while preserving assay sensitivity and specificity. MinLibCas9 provides backward compatibility with existing datasets, increases the dynamic range of CRISPR-Cas9 screens and extends their application to complex models and assays.
Highlights
CRISPR-Cas9 loss-of-function screens have been used in a variety of model organisms, including human cells [1, 2]
The recent availability of data from CRISPR-Cas9 knockout screens performed in hundreds of cell lines [13, 17] makes it possible to empirically improve library design through selection of single-guide RNA (sgRNA) with strong and consistent biological effects across diverse contexts, incorporating additional factors that might influence guide efficacy [18, 19]
A pseudo count of 1 was added to the whole matrix and log2 fold-changes were calculated compared to plasmid DNA (pDNA). sgRNAs recall curves are drawn by sorting the guides by fold-change, from the most negative to the most positive, and the cumulative distribution is calculated for the different guide groups
Summary
CRISPR-Cas loss-of-function screens have been used in a variety of model organisms, including human cells [1, 2]. MinLibCas combines some of these strategies to design a minimal and optimised sgRNA library, which unlocks the application of Cas genome-wide screens to complex models currently limited to the delivery of libraries focused on predefined and small gene sets It provides a data-driven approach to prioritise the selection of the most effective sgRNAs for assays using more complex read-outs, e.g. Perturb-seq [41, 42], and to build large-scale genetic interaction libraries
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