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Computational Tool Tracks Genetic Variation Effects of Off-Target Gene Editing

NEW YORK – A team from the US, Italy, and elsewhere has developed a computational tool for predicting the off-target gene editing consequences of genetic differences that occur between human individuals and populations, highlighting the incorrect edits that can arise if such variants are not considered.

"CRISPR-based systems may create unintended off-target modifications posing potential genotoxicity for therapeutic use," co-senior and co-corresponding authors Luca Pinello, Daniel Bauer, and Rosalba Giugno, and their colleagues wrote in Nature Genetics on Thursday, adding that "computational methods may be especially useful to predict the impact of off-target sequences not found in reference genomes."

Pinello is affiliated with Massachusetts General Hospital's Molecular Pathology Unit and the Broad Institute, while Bauer is a researcher at Dana-Farber Cancer Institute and the Broad. Giugno is a computer science researcher with the University of Verona.

Building on an existing CRISPRitz tool for taking genetic variation into account for guide RNA (gRNA) design, the researchers came up with a tool called CRISPRme for predicting off-target gene editing events based on factors including personalized or population variant profiles, sequence structures, regulatory annotations, editing enzyme selection, spacer sequences, and neighboring protospacer adjacent motif (PAM) sequences influencing gRNA-DNA interactions.

Along with insights into variant interactions and off-target effects related to base editor selection, the team pointed to the possibility of using CRISPRme for prioritizing gRNAs in therapeutic settings or performing other analyses that rely on a refined understanding of nucleic acid sequence recognition such as transcript targeting with antisense oligonucleotides.

"We expect that variant-aware off-target assessment will become integral to therapeutic genome editing evaluation and provide a powerful approach for comprehensive off-target nomination," the authors suggested, calling CRISPRme "a simple-to-use tool to comprehensively evaluate off-target potential across diverse populations and within individuals."

With the help of cutting frequency determination (CFD) scores, CRISPR target assessment (CRISTA) scores, and other reports generated by the CRISPRme tool, for example, the researchers profiled potential off-target sites for a gRNA with possible clinical relevance — the gRNA #1617, which targets a binding site in the BCL11A erythroid enhancer. The gRNA is being explored in the context of sickle cell disease and beta-thalassemia treatment, they explained, where it is being used to edit hematopoietic stem and progenitor cells (HSPCs).

In addition to hundreds of possible off-target variants found with diverse genome sequences from large efforts such as the 1000 Genomes Project and the Human Genome Diversity Project, the team focused in on a variant called rs114518452 with off-target potential during gRNA #1617-editing.

The team found further support for the off-target consequences of the variant with follow-up experiments on CD34-positive HSPCs from African ancestry individuals with alternate versions of rs114518452. While on-targeting editing alters a chromosome 2p enhancer intron influencing BCL11A activity, for example, the off-target-related variant was capable of introducing edits affecting a CPS1 intron on chromosome 2q.

The off-target version of the rs114518452 variant appeared to be relatively common in African or African American populations, the researchers noted, where it had a minor allele frequency of 4.5 percent. In contrast, the variant allele turned up in zero to 0.91 percent of individuals from several other populations from the Middle East, Europe, Asia, or Latin America.

"Our results highlight that allele-specific off-target editing potential is not equally distributed across all ancestral groups but is especially concentrated in those of African ancestry where genomic variation is most pronounced," the authors noted, adding that "[g]ene editing efforts that focus on a specific patient population should consider genetic variants enriched in that population during off-target evaluation."