One-step efficient generation of dual-function conditional knockout and geno-tagging alleles in zebrafish

CRISPR/Cas systems are widely used to knock out genes by inducing indel mutations, which are prone to genetic compensation. Complex genome modifications such as knockin (KI) might bypass compensation, though difficult to practice due to low efficiency. Moreover, no ‘two-in-one’ KI strategy combining conditional knockout (CKO) with fluorescent gene-labeling or further allele-labeling has been reported. Here, we developed a dual-cassette-donor strategy and achieved one-step and efficient generation of dual-function KI alleles at tbx5a and kctd10 loci in zebrafish via targeted insertion. These alleles display fluorescent gene-tagging and CKO effects before and after Cre induction, respectively. By introducing a second fluorescent reporter, geno-tagging effects were achieved at tbx5a and sox10 loci, exhibiting CKO coupled with fluorescent reporter switch upon Cre induction, enabling tracing of three distinct genotypes. We found that LiCl purification of gRNA is critical for highly efficient KI, and preselection of founders allows the efficient germline recovery of KI events.


Sample-size estimation
 You should state whether an appropriate sample size was computed when the study was being designed  You should state the statistical method of sample size computation and any required assumptions  If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
 You should report how often each experiment was performed  You should include a definition of biological versus technical replication  The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates  If you encountered any outliers, you should describe how these were handled  Criteria for exclusion/inclusion of data should be clearly stated  High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: About 100 one-cell stage zebrafish embryos were used for the generation of knock-in founders for each target gene. Details can be found in the Results section in the manuscript.
The micro-injection of founder embryos were performed at least three times for each target gene to optimize the injection conditions, and the efficiency of knock-in was determined by the ratio of founder embryos bearing positive fluorescent signals. 2 Statistical reporting  Statistical analysis methods should be described and justified  Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10)  For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d)  Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
 Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied  Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data")  We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table  Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table  Include model definition files including the full list of parameters used  Include code used for data analysis (e.g., R, MatLab)  Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: The statistical analysis method for the qRT-PCR analysis can be found in the section of Materials and Methods.
In some experiments, founder embryos were separated into two or three groups according to the presence or absence of certain fluorescent signals, or different injection methods. Details can be found in the Results section in our manuscript.
We do not have source data file for our manuscript.