Necessity for Validation of Effectiveness of Selected Guide RNA In Silico for Application of CRISPR/Cas9

Selection of guide RNA (gRNA) is important to increase the efficiency of gene editing in the CRISPR/Cas9 system. Due to the variation in actual efficiency of insertion/deletion (indel) mutation among selected gRNAs in silico, reliable methods for validation of efficiency of gRNA need to be developed...

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Bibliographic Details
Published in:Molecular biotechnology 2021-02, Vol.63 (2), p.140-149
Main Authors: Kim, Dong-Hwan, Lee, Joonbum, Suh, Yeunsu, Lee, Kichoon
Format: Article
Language:English
Subjects:
Animals
Base Sequence
Biochemistry
Biological Techniques
Biotechnology
Cell Biology
Cell Line
Chemistry
Chemistry and Materials Science
Computer Simulation
CRISPR
CRISPR-Cas Systems - genetics
Efficiency
Gene deletion
Genetic modification
Genetic Vectors - metabolism
Genome editing
Green Fluorescent Proteins - metabolism
gRNA
Human Genetics
INDEL Mutation - genetics
Insertion
Mutation
Mutation rates
Original Paper
Polymorphism, Single Nucleotide - genetics
Protein Science
Quail
Retinol-Binding Proteins - genetics
Ribonucleic acid
RNA
RNA, Guide, CRISPR-Cas Systems - genetics
Vitamin A
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Summary:Selection of guide RNA (gRNA) is important to increase the efficiency of gene editing in the CRISPR/Cas9 system. Due to the variation in actual efficiency of insertion/deletion (indel) mutation among selected gRNAs in silico, reliable methods for validation of efficiency of gRNA need to be developed. Three gRNAs with high on-target scores (72.0 for target 1, 65.4 for target 2, and 62.9 for target 3) were designed to target the quail retinol binding protein 7 (qRbp7) gene, and indel efficiencies were predicted by the Sanger sequencing and Inference of CRISPR Edits (ICE) analysis of sorted cell populations receiving the CRISPR/Cas9 vector. Unlike the order of on-target scores among 3 gRNAs, predicted rates of indel mutations were highest in gRNA2, intermediate in gRNA1, and lowest in gRNA3. This was confirmed by actual indel mutation rates, 51.8% in gRNA2, 31% in gRNA1, and 12.9% in gRNA3, which were calculated by sequencing individual allele cloned into a vector. These data showed a rapid and reliable method for estimation of the efficiency of selected gRNAs, providing a critical necessary step for successful gene editing for further applications.
ISSN:1073-6085
1559-0305
DOI:10.1007/s12033-020-00290-8