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De novo screening of disease-resistant genes from the chromosome-level genome of rare minnow using CRISPR-cas9 random mutation

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Abstract Background Mutants are important for the discovery of functional genes and creation of germplasm resources. Mutant acquisition depends on the efficiency of mutation technology and screening methods. CRISPR-Cas9 technology… Click to show full abstract

Abstract Background Mutants are important for the discovery of functional genes and creation of germplasm resources. Mutant acquisition depends on the efficiency of mutation technology and screening methods. CRISPR-Cas9 technology is an efficient gene editing technology mainly used for editing a few genes or target sites, which has not been applied for the construction of random mutant libraries and for the de novo discovery of functional genes. Results In this study, we first sequenced and assembled the chromosome-level genome of wild-type rare minnow (Gobiocypris rarus) as a susceptible model of hemorrhagic disease, obtained a 956.05 Mb genome sequence, assembled the sequence into 25 chromosomes, and annotated 26,861 protein-coding genes. Thereafter, CRISPR-Cas9 technology was applied to randomly mutate the whole genome of rare minnow with the conserved bases (TATAWAW and ATG) of the promoter and coding regions as the target sites. The survival rate of hemorrhagic disease in the rare minnow gradually increased from 0% (the entire wild-type population died after infection) to 38.24% (F3 generation). Finally, 7 susceptible genes were identified via genome comparative analysis and cell-level verification based on the rare minnow genome. Conclusions The results provided the genomic resources for wild-type rare minnow, and confirmed that the random mutation system designed using CRISPR-Cas9 technology in this study is simple and efficient and is suitable for the de novo discovery of functional genes and creation of a germplasm resource related to qualitative traits.

Keywords: rare minnow; crispr cas9; technology; mutation; genome

Journal Title: GigaScience
Year Published: 2021

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