Comparative analysis of TIDE and ICE algorithms for predicting mutations in F0 and F1 generation mice after CRISP-Cas9 genome editing
- 31 March 2026
- journal article
- Published by ECO-Vector LLC (Publications) in Ecological genetics
- Vol. 24 (1) , 95-100
Abstract
BACKGROUND: The CRISPR/Cas9 technology enables the generation of genetically modified founder animals (F0 generation) already at the stage of zygote editing. However, the resulting offspring are often mosaic, meaning they carry different mutations in different cells, which complicates accurate genotyping using standard tissue samples. To establish a stable knockout line, it is necessary to identify F0 individuals carrying the target mutations, which requires subsequent crossing with wild-type mice and a large-scale analysis of the F1 offspring, involving significant costs. Therefore, the efficient prediction of inheritable mutations at the F0 generation stage is a critical task. AIM: A comparative evaluation of the efficiency of the TIDE and ICE bioinformatic algorithms for analyzing Sanger sequencing data to accurately predict inheritable mutations in the vldlr gene in F0 mosaic mice. METHODS: The study was conducted on five F0 mosaic mice with mutations in the vldlr gene, obtained by microinjection of CRISPR/Cas9 components into zygotes. Genomic DNA was isolated from ear tissue, the target region of the vldlr gene was amplified by PCR and sequenced by the Sanger method. The resulting chromatograms were analyzed using the TIDE and ICE algorithms. The predictions were validated by crossing the F0 mice with wild-type mice and analyzing the inheritance of mutations in the F1 generation. RESULTS: The comparison of the algorithms showed that both programs correctly predicted all mutations that were subsequently detected in the F1 generation. In total, 31 F1 offspring were analyzed. CONCLUSION: Both tools are suitable for primary screening. The analysis of the offspring confirmed that all actually inherited mutations were predicted by both methods.Keywords
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