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The tool addresses the critical challenge of Cas9 re-cleavage by simplifying the selection of \u201cblocking\u201d silent variants that are effective at inhibiting RNP binding upon donor-templated editing. SNIPSNP handles complex edits, including indels, and uses multi-objective optimization to balance editing efficiency with biological safety. From user-defined wild-type and desired HDR alleles, the pipeline identifies candidate guides, annotating them with integrated efficiency scores and genome-wide off-target assessments. Uniquely, SNIPSNP evaluates guide binding against the post-edit genome to determine whether the therapeutic variant alone disrupts repeated Cas9 recognition. When necessary, it introduces synonymous blocking variants, prioritizing PAM and seed regions to minimize re-cleavage probability and editing of the wild-type (WT) allele when editing heterozygous variants. All candidate modifications undergo safety profiling and prioritization of known benign variants from dbSNP. We experimentally validated SNIPSNP and benchmarked it on pathogenic inborn error of immunity variants in primary patient T-cells. Across loci, SNIPSNP-designed templates outperform standard \u201ccorrection-only\u201d strategies, demonstrating enhanced precision editing, and reduced re-cleavage, establishing SNIPSNP as a robust platform for genome editing and disease modeling.<\/jats:p>","DOI":"10.1093\/nar\/gkag409","type":"journal-article","created":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T11:50:55Z","timestamp":1776858655000},"page":"W145-W153","source":"Crossref","is-referenced-by-count":0,"title":["SNIPSNP: precision design of CRISPR\/Cas9 knock-in reagents for variant correction and disease modeling"],"prefix":"10.1093","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1262-2611","authenticated-orcid":false,"given":"Kornel","family":"Labun","sequence":"first","affiliation":[{"name":"Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw , 02-106 Warsaw ,","place":["Poland"]},{"name":"Computational Biology Unit, Department of Informatics, University of 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