Summary
The recent advancements of CRISPR and next-generation technology has enabled researchers to create more precise zebrafish models of human disease. This being said, knock-in (KI) techniques in zebrafish still aren’t fully optimized. In this article we discuss the current state of CRISPR-Cas9-mediated targeted knock-ins in zebrafish, and what the future holds.
CRISPR-based gene editing works by using a guide RNA and a Cas9 nuclease to target a specific site. Originally applied to making knock-outs (KOs) (models where a gene is inactivated, or ‘knocked out’), CRISPR’s capability has expanded to include the generation of knock-ins (models in which genetic material is inserted) [Figure 1]. The application of CRISPR techniques to zebrafish has enabled big gains within biomedical and disease research, however, achieving site-specific zebrafish knock-ins is still challenging. This can be attributed to two main factors: the competing repair mechanisms of non homologous end joining (NHEJ) and homology directed repair (HDR), and imperfect prediction tools for zebrafish models.
Figure 1: NHEJ and HDR. (Ramon Guitart et al., 2016: “Research Techniques Made Simple: The Application of CRISPR-Cas9 and Genome Editing in Investigative Dermatology” http://dx.doi.org/10.1016/j.jid.2016.06.007)
The difference in the level of difficulty to achieve successful knockouts and knock-ins has been compared to home construction, with knock-ins being considered more difficult since “building something is harder than tearing it down,” however, the differences between these two techniques are a little more complicated than that (Nowogrodzki, 2019). This is due to the repair mechanisms that the two techniques rely on: whereas knockouts utilize NHEJ or MMEJ repair pathways which are the most active in the cell, knock-ins require homology-directed repair (HDR). Thus, zebrafish knock-ins encounter the same challenge of encouraging HDR repair and avoiding NHEJ repair that all knock-in models face.
When attempting to make successful zebrafish knock-ins, sgRNA cutting efficiency predictor tools are an essential first step. After all, you have to have an efficient cut before you can generate repair from a template! Unfortunately, the tools we have are still evolving and are based on input data that may need expansion and updating. In our own labs, we have found that predictors are still imperfect: in a recent survey where we compared the predicted cutting efficiency from two popular algorithms to our own in vivo measured efficiencies, we found little evidence of correlation [Figure two]. Even after a cut is achieved, there is at present no reliable predictor for whether HDR will occur at a genomic locus.
Figure 2. Predicted vs. Observed Efficiencies for sgRNA Targets. sgRNAs used in recent client projects were selected and evaluated. Pearson correlation coefficient revealed no significant correlations (r= -0.12, p=.6 for FusiScore, r=0.21, p=0.4 for CRISPRscan).
At InVivo Biosystems we have dedicated many operational and protocol improvements to developing more effective techniques for zebrafish knock-in creation, and are now approaching an 80% success rate at knocking in small (several nucleotides) to medium sized (up to several hundred nucleotides) templates. Knocking in larger insertions such as fluorophores remains a challenge for all of us in the field. We see the value in undertaking knock-in projects and we are here to help; our hope is that as more research is conducted, knock-in techniques can become more attuned towards the zebrafish community so that more avenues of study become possible.
References
- Albadri, S., Del Bene, F., & Revenu, C. (2017). Genome editing using CRISPR/Cas9-based knock-in approaches in zebrafish. Methods (San Diego, Calif.), 121-122, 77–85. https://doi.org/10.1016/j.ymeth.2017.03.005
- Choi, TY., Choi, TI., Lee, YR. et al. (2021). Zebrafish as an animal model for biomedical research. Exp Mol Med 53, 310–317 https://doi.org/10.1038/s12276-021-00571-5
- Howe, K., Clark, M., Torroja, C. et al. (2013). The zebrafish reference genome sequence and its relationship to the human genome. Nature 496, 498–503 https://doi.org/10.1038/nature12111
- Moreno-Mateos, M. A., Vejnar, C. E., Beaudoin, J. D., Fernandez, J. P., Mis, E. K., Khokha, M. K., & Giraldez, A. J. (2015). CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo. Nature methods, 12(10), 982–988. https://doi.org/10.1038/nmeth.3543
- Nowogrodzki, A. (2019). The Challenge of Using CRISPR to Knock In Genes. The Scientist. https://www.the-scientist.com/lab-tools/jacking-up-gene-knock-ins-65504
About the Author: Alexandra Narin
Alexandra is a Content Marketing Specialist and Grant Writer for InVivo Biosystems. She graduated from the University of St Andrews in 2020 where she earned a Joint MA Honours Degree in English & Psychology/Neuroscience with BPS [British Psychology Society] Accreditation. She has worked as a research assistant, examining the LEC's (lateral entorhinal cortex) involvement in spatial memory and integrating long term multimodal item-context associations, and completed her dissertation on how the number and kinds of sensory cues affect memory persistence across timescales. Her hobbies include running, boxing, and reading.