An optimized base editor with efficient C-to-T base editing in zebrafish

Abstract Background Zebrafish is a model organism widely used for the understanding of gene function, including the fundamental basis of human disease, enabled by the presence in its genome of a high number of orthologs to human genes. CRISPR/Cas9 and next-generation gene-editing techniques using cy...

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Bibliographic Details
Main Authors: Yu Zhao, Dantong Shang, Ruhong Ying, Hanhua Cheng, Rongjia Zhou
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Biology
Subjects:
Online Access:https://doi.org/10.1186/s12915-020-00923-z
Description
Summary:Abstract Background Zebrafish is a model organism widely used for the understanding of gene function, including the fundamental basis of human disease, enabled by the presence in its genome of a high number of orthologs to human genes. CRISPR/Cas9 and next-generation gene-editing techniques using cytidine deaminase fused with Cas9 nickase provide fast and efficient tools able to induce sequence-specific single base mutations in various organisms and have also been used to generate genetically modified zebrafish for modeling pathogenic mutations. However, the editing efficiency in zebrafish of currently available base editors is lower than other model organisms, frequently inducing indel formation, which limits the applicability of these tools and calls for the search of more accurate and efficient editors. Results Here, we generated a new base editor (zAncBE4max) with a length of 5560 bp following a strategy based on the optimization of codon preference in zebrafish. Our new editor effectively created C-to-T base substitution while maintaining a high product purity at multiple target sites. Moreover, zAncBE4max successfully generated the Twist2 p.E78K mutation in zebrafish, recapitulating pathological features of human ablepharon macrostomia syndrome (AMS). Conclusions Overall, the zAncBE4max system provides a promising tool to perform efficient base editing in zebrafish and enhances its capacity to precisely model human diseases.
ISSN:1741-7007