Simple and reliable detection of CRISPR-induced on-target effects by qgPCR and SNP genotyping

The recent CRISPR revolution has provided researchers with powerful tools to perform genome editing in a variety of organisms. However, recent reports indicate widespread occurrence of unintended CRISPR-induced on-target effects (OnTEs) at the edited site in mice and human induced pluripotent stem cells (iPSCs) that escape standard quality controls. By altering gene expression of targeted or neighbouring genes, OnTEs can severely affect phenotypes of CRISPR-edited cells and organisms and thus lead to data misinterpretation, which can undermine the reliability of CRISPR-based studies. Here we describe a broadly applicable framework for detecting OnTEs in genome-edited cells and organisms after non-homologous end joining-mediated and homology-directed repair-mediated editing. Our protocol enables identification of OnTEs such as large deletions, large insertions, rearrangements or loss of heterozygosity (LOH). This is achieved by subjecting genomic DNA first to quantitative genotyping PCR (qgPCR), which determines the number of intact alleles at the target site using the same PCR amplicon that has been optimized for genotyping. This combination of genotyping and quantitation makes it possible to exclude clones with monoallelic OnTEs and hemizygous editing, which are often mischaracterized as correctly edited in standard Sanger sequencing. Second, occurrence of LOH around the edited locus is detected by genotyping neighbouring single-nucleotide polymorphisms (SNPs), using either a Sanger sequencing-based method or SNP microarrays. All steps are optimized to maximize simplicity and minimize cost to promote wide dissemination and applicability across the field. The entire protocol from genomic DNA extraction to OnTE exclusion can be performed in 6-9 d.

Automated summary

The study presents a framework for detecting OnTEs in genome-edited cells and organisms which can exclude large deletions, insertions, rearrangements, and loss of heterozygosity. The protocol uses optimized PCR primers and SNP detection methods to efficiently and accurately identify these unintended effects while maximizing simplicity and minimizing costs.