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Electroporation and genetic supply of Cas9 increase the generation efficiency of CRISPR/Cas9 knock-in alleles in C57BL/6J mouse zygotes

Abstract:
CRISPR/Cas9 machinery delivered as ribonucleoprotein (RNP) to the zygote has become a standard tool for the development of genetically modified mouse models. In recent years, a number of reports have demonstrated the effective delivery of CRISPR/Cas9 machinery via zygote electroporation as an alternative to the conventional delivery method of microinjection. In this study, we have performed side-by-side comparisons of the two RNP delivery methods across multiple gene loci and conclude that electroporation compares very favourably with conventional pronuclear microinjection, and report an improvement in mutagenesis efficiency when delivering CRISPR via electroporation for the generation of simple knock-in alleles using single-stranded oligodeoxynucleotide (ssODN) repair templates. In addition, we show that the efficiency of knock-in mutagenesis can be further increased by electroporation of embryos derived from Cas9-expressing donor females. The maternal supply of Cas9 to the zygote avoids the necessity to deliver the relatively large Cas9 protein, and high efficiency generation of both indel and knock-in allele can be achieved by electroporation of small single-guide RNAs and ssODN repair templates alone. Furthermore, electroporation, compared to microinjection, results in a higher rate of embryo survival and development. The method thus has the potential to reduce the number of animals used in the production of genetically modified mouse models.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41598-020-74960-7

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
ORCID:
0000-0002-2251-3291
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Big Data Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author


Publisher:
Springer Nature
Journal:
Scientific Reports More from this journal
Volume:
10
Article number:
17912
Publication date:
2020-10-21
Acceptance date:
2020-10-08
DOI:
EISSN:
2045-2322


Language:
English
Keywords:
Subjects:
Pubs id:
1136437
Local pid:
pubs:1136437
Deposit date:
2020-10-08

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