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Unveiling Off-Target Mutations in CRISPR Guide RNAs: Implications for Gene Region Specificity.
Kose, Ali Mertcan; Kocadagli, Ozan; Tastan, Cihan; Aktan, Cagdas; Ünaldi, Onur Mert; Güzenge, Elanur; Erdil, Hamza Emir.
Afiliación
  • Kose AM; Department of Computer Programming, Istanbul Ticaret University, Istanbul, Türkiye.
  • Kocadagli O; Department of Statistics, Mimar Sinan Fine Arts University, Istanbul, Türkiye.
  • Tastan C; Molecular Biology and Genetics Department of Transgenic Cell Techologies and Epigenetic Application and Research Center (TRGENMER), Üsküdar University, Istanbul, Türkiye.
  • Aktan C; Department of Medical Biology, Bandirma Onyedi Eylül University, Balikesir, Türkiye.
  • Ünaldi OM; Molecular Biology and Genetics Department of Transgenic Cell Techologies and Epigenetic Application and Research Center (TRGENMER), Üsküdar University, Istanbul, Türkiye.
  • Güzenge E; Molecular Biology and Genetics Department of Transgenic Cell Techologies and Epigenetic Application and Research Center (TRGENMER), Üsküdar University, Istanbul, Türkiye.
  • Erdil HE; Molecular Biology and Genetics Department of Transgenic Cell Techologies and Epigenetic Application and Research Center (TRGENMER), Üsküdar University, Istanbul, Türkiye.
CRISPR J ; 7(3): 168-178, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38922052
ABSTRACT
The revolutionary CRISPR-Cas9 technology has revolutionized genetic engineering, and it holds immense potential for therapeutic interventions. However, the presence of off-target mutations and mismatch capacity poses significant challenges to its safe and precise implementation. In this study, we explore the implications of off-target effects on critical gene regions, including exons, introns, and intergenic regions. Leveraging a benchmark dataset and using innovative data preprocessing techniques, we have put forth the advantages of categorical encoding over one-hot encoding in training machine learning classifiers. Crucially, we use latent class analysis (LCA) to uncover subclasses within the off-target range, revealing distinct patterns of gene region disruption. Our comprehensive approach not only highlights the critical role of model complexity in CRISPR applications but also offers a transformative off-target scoring procedure based on ML classifiers and LCA. By bridging the gap between traditional target-off scoring and comprehensive model analysis, our study advances the understanding of off-target effects and opens new avenues for precision genome editing in diverse biological contexts. This work represents a crucial step toward ensuring the safety and efficacy of CRISPR-based therapies, underscoring the importance of responsible genetic manipulation for future therapeutic applications.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas / Sistemas CRISPR-Cas / Edición Génica / ARN Guía de Sistemas CRISPR-Cas / Mutación Límite: Humans Idioma: En Revista: CRISPR J Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas / Sistemas CRISPR-Cas / Edición Génica / ARN Guía de Sistemas CRISPR-Cas / Mutación Límite: Humans Idioma: En Revista: CRISPR J Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos