A high-performance method for CRISPR off-target nomination

Integrated DNA Technologies (IDT), a Danaher company and a global leader in genomics, has announced the publication of a peer-reviewed study establishing a new analytical performance benchmark for CRISPR off-target nomination, providing evidence that can help gene editing developers prioritise biologically relevant sites for downstream confirmation and risk assessment. Published in the journal Nature Communications, the work addresses a critical challenge in therapeutic genome editing: determining whether nomination methods reliably identify biologically relevant sites while producing sufficiently precise results to guide subsequent evaluation.

As gene editing technologies expand across nucleases, high-fidelity variants and base editors, developers must evaluate the possibility that editing could occur at unintended genomic locations. Although multiple computational, biochemical and cell-based methods are available to nominate potential off-target sites, the field has lacked consistent empirical evidence for comparing their analytical sensitivity, precision and operating requirements.

“The future of gene editing will be advanced by generating clear, reliable evidence that helps developers identify and evaluate potential off-target sites with confidence,” said Gavin Kurgan, Senior Manager, Bioinformatics Applications Development at IDT, who was corresponding author on the new study. “By moving the industry conversation from the number of nominated sites to measurable sensitivity, precision and downstream confirmation burden, this study demonstrates how IDT works alongside scientists to solve one of therapeutic genome editing’s hardest challenges and accelerate the path from promising science to responsible impact.”

In the study, scientists from IDT and the University of California, San Francisco created an inter-method benchmarking dataset based on targeted confirmation of potential off-target sites, enabling performance to be assessed against empirically observed editing rather than the size of a method’s candidate list. Across the two guide RNAs used to calculate comparative performance, the study found that UNCOVERseq — IDT’s in cellulo workflow for nominating potential CRISPR off-target editing sites — achieved 97.6% analytical sensitivity and 78% precision, marking the strongest combined sensitivity and precision among the methods evaluated.

The research also defines operating conditions that influence off-target nomination, including biological replication, genomic DNA input, sequencing depth, library preparation, alignment criteria and process controls. The research team found that insufficient operating conditions can limit method performance, while low-precision approaches may generate large candidate lists that increase downstream confirmation burden, time and cost. By clarifying the conditions required for reproducible performance, the study is said to provide a framework for advancing off-target assessment with greater speed and certainty without compromising analytical rigour.

“By working across disciplines to measure sensitivity and precision against empirically confirmed editing — and by establishing the operating parameters that influence those measurements — we hope this work provides scientists, developers and regulators with a practical framework for evaluating off-target nomination strategies with greater confidence,” Kurgan said.

The publication comes as the U.S. Food and Drug Administration considers draft guidance on the use of next-generation sequencing and bioinformatics in non-clinical safety studies for human genome editing products. The draft includes recommendations concerning sequencing strategies, sample selection, analysis parameters and reporting to evaluate off-target editing and loss of genome integrity in support of IND applications and BLAs. Although the study does not represent regulatory guidance or endorsement, its empirical comparison of analytical performance and operating conditions is understood to contribute timely evidence for scientists and developers evaluating how to respond to emerging expectations.

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