Comparative analysis of TIDE and ICE algorithms for predicting mutations in F0 and F1 generation mice after CRISP-Cas9 genome editing
- Authors: Akhmarov I.I.1, Luganskaya P.S.1, Kirillov O.A.1, Kandina D.A.1, Romanovich A.E.1, Sopova J.V.1, Leonova E.I.1
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Affiliations:
- Saint Petersburg State University
- Issue: Vol 24, No 1 (2026)
- Pages: 95-100
- Section: Genetically modified organism.history, achievements, social and environmental risks.
- Submitted: 31.10.2025
- Accepted: 01.04.2026
- Published: 31.03.2026
- URL: https://journals.eco-vector.com/ecolgenet/article/view/695596
- DOI: https://doi.org/10.17816/ecogen695596
- EDN: https://elibrary.ru/CAXFJT
- ID: 695596
Cite item
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.
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About the authors
Ilyas I. Akhmarov
Saint Petersburg State University
Author for correspondence.
Email: luvk7411@ya.ru
ORCID iD: 0009-0008-8920-6705
SPIN-code: 5952-4539
Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgPolina S. Luganskaya
Saint Petersburg State University
Email: polina.luganskaja@yandex.ru
ORCID iD: 0009-0005-1124-3360
SPIN-code: 1019-8610
Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgOleg A. Kirillov
Saint Petersburg State University
Email: o-kirillov03@mail.ru
ORCID iD: 0009-0004-3400-6678
SPIN-code: 7459-9945
Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgDaria A. Kandina
Saint Petersburg State University
Email: candyda20@mail.ru
ORCID iD: 0009-0007-4108-6161
SPIN-code: 7921-4448
Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgAnna E. Romanovich
Saint Petersburg State University
Email: a.romanovich@spbu.ru
ORCID iD: 0009-0004-7839-8482
SPIN-code: 8364-4430
Resource Center “Development of Molecular and Cellular Technologies”
Russian Federation, Saint PetersburgJulia V. Sopova
Saint Petersburg State University
Email: sopova@hotmail.com
ORCID iD: 0000-0002-7825-273X
SPIN-code: 6019-1547
Cand. Sci. (Biology), Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgElena I. Leonova
Saint Petersburg State University
Email: 1102.elena@gmail.com
ORCID iD: 0000-0002-0236-3302
SPIN-code: 2573-1759
Cand. Sci. (Biology), Center for Transgenesis and Genome Editing
Russian Federation, Saint PetersburgReferences
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