Introduction of loxP sites by electroporation in the mouse genome; a simple approach for conditional allele generation in complex targeting loci

通过电穿孔在小鼠基因组中引入 loxP 位点;一种在复杂靶位点中生成条件等位基因的简单方法

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作者:Guillaume Bernas, Mariette Ouellet, Andréa Barrios, Hélène Jamann, Catherine Larochelle, Émile Lévy, Jean-François Schmouth

Background

The discovery of the CRISPR-Cas9 system and its applicability in mammalian embryos has revolutionized the way we generate genetically engineered animal models. To date, models harbouring conditional alleles (i.e. two loxP sites flanking an exon or a critical DNA sequence of interest) are amongst the most widely requested project type that are challenging to generate as they require simultaneous cleavage of the genome using two guides in order to properly integrate the repair template. An approach, using embryo sequential electroporation has been reported in the literature to successfully introduce loxP sites on the same allele. Here, we describe a modification of this sequential electroporation procedure that demonstrated the production of conditional allele mouse models for eight different genes via one of two possible strategies: either by consecutive sequential electroporation (strategy A) or non-consecutive sequential electroporation (strategy B). This latest strategy originated from using the by-product produced when using consecutive sequential electroporation (i.e. mice with a single targeted loxP site) to complete the project.

Conclusion

Our modified electroporation-based approach, involving one of the two alternative strategies, allowed the production of conditional allele models for eight different genes via two different possible paths. This reproducible method will serve as another reliable approach in addition to other well-established methodologies in the literature for conditional allele mouse model generation.

Results

By using strategy A, we demonstrated successful generation of conditional allele models for three different genes (Icam1, Lox, and Sar1b), with targeting efficiencies varying between 5 and 13%. By using strategy B, we generated five conditional allele models (Loxl1, Pard6a, Pard6g, Clcf1, and Mapkapk5), with targeting efficiencies varying between 3 and 25%.

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