Clustered regularly interspaced short palindromic repeats (CRISPR) technology is a rapid, cheap, and efficient tool to edit genomes at a precise location. CRISPR technology has now been reduced to just two components: Endonuclease and g RNA. Endonuclease makes an incision at the target DNA molecule to be edited, and gRNA is a single-stranded synthetic 20 nucleotide sequence complementary to the target DNA to be edited; it has a scaffold to bind with endonucleases (cas9 or CFL). g RNA is used for site-specific editing of the genome. gRNA synthesis holds critical importance in the success of genome editing experiment. In this review, we will highlight important factors to be considered while synthesizing a gRNA molecule (Lou, 2019).Two important factors should be kept in mind while designing a suitable gRNA are:
a). The efficiency of binding with our gene of interest
b). Minimum off-target cleavage events (Wong, Liu, & Wang, 2015).
Binding efficiency (how well sgRNA binds to the target sequence) of gRNA is of crucial importance while designing a CRISPR experiment. The binding efficiency of g RNA varies from one sequence to another. A suitable scoring system is used to access the efficiency of g RNA binding; Scoring system used also depends on the model system under consideration. For example, for zebrafish injection experiments or for assays based on the delivery of synthetically produced gRNAs, the Moreno-Mateos score is used to determine gRNA binding efficiency accurately, but the Moreno-Mateos system is not reliable for scoring gRNA if the system under consideration is cultured mammalian cells. The system scores by Doench et al., are commonly used mammalian cells. Wang score is used for some cancer cell lines while generating second-generation libraries of human gRNAs. The web tool http://crispor.org is commonly used to score RNA efficiency for different experiments and has multiple scoring systems, including Moreno-Mateos and Doench scoring.
It should be kept in mind to only select the score trained on the same system as the system you plan to use in your experiment.
The propensity of genomic sites to be cleaved can also be determined using machine learning techniques like CRISTA (Luo, 2019; Wong, Liu, & Wang, 2015) One of the biggest challenges of CRISPR technology is that it has an off-target activity, which means that cas 9 endonuclease can cleave randomly even if there is no complementarity between cas 9 and genome sequence. Earlier it was believed that specificity of Cas 9 depends on the PAM site (Protospacer adjacent motif of 2 to 6 nucleotides upstream of the target sequence), but now it has been suggested that specificity is strictly controlled by a seed sequence: 5 base pair sequence upstream of the PAM site.
Due to the importance of proximal sites in a CRISPR gene editing experiment, the following guidelines were proposed to design a gRNA sequence that can support the minimum off-target activity of endonucleases (Luo, 2019).
- GC content: Synthetic gRNA with increased or decreased GC content can lead to increased activity. Guanine is a preferred first base after the PAM sequence, while it is recommended to use cytosine at 5th position after the PAM sequence.
- Mismatches: At 5’ end of gRNA, mismatches can be introduced.
- Uracil rich seeds: U rich seeds are preferred as they lead to an increased specificity and decreased abundance of sgRNA (Zhang, Tee, Wang, Huang, & Yang, 2015)
- Minimizing the concentration of gRNA and cas9 in cells can also reduce off-target mutations.
- Truncating 5’ end of gRNA in complementarity region (gRNA’s with 17-18 nucleotides with complementarity function) can work as efficiently as a full length construct but have low off-target activity. (Sander & Joung, 2014)
- One of the other methods to reduce the off-target activity of gRNA without compromising its on-target activity is by using cas9 with an engineered structure wherein nucleotide groove positive charges are neutralized that reduces off-target indel formation but increases on-target activity stabilization. This method was proposed by Slaymaker et al. (Slaymaker et al., 2016)
Cutting frequency determination score can be used to predict the off-target activity of sgRNAs (Wong, Liu, & Wang, 2015).
For performing off target and on target activity analysis, different high throughput techniques have been designed like GUIDE-seq and CIRCLE-seq (Luo, 2019)After successfully selecting endonucleases and designing sgRNA, the next step is to deliver sgRNA and endonucleases to the experimental system. Various approaches are used for this:
This method is used to generate gRNA libraries and for efficient gRNA screening. In this procedure, synthesized gRNA is enclosed on to the reverse primer of the U6 promoter template. And it is co-transfected into the cells containing cas9 expression plasmid.
TOPO cloning is the molecular cloning technique that doesn’t require any restriction enzymes or ligase; more precisely, it does not require any post PCR procedures. Topocoloning of gRNA in an episomal vector followed by cotransfection in episomal plasmid can be done.
gRNAs and endonucleases can be transfected into cells.
Ligation into the plasmid
Oligo Pairs with 20 nucleotide guide sequences can be annealed in the plasmid containing cas9 expression vectors (Luo, 2019).For functional validation, in vitro screens can be performed. Cell culture and transfection of endonucleases and gRNAs are performed. Successfully edited clonal cell lines can be isolated by techniques like FACS enrichment (Luo, 2019)
- SURVEYOR nuclease assay The efficiency of the CRISPR experiment can be determined using the SURVEYOR nuclease assay. It is an enzyme mismatch cleavage assay. It can be used to detect insertions and deletions, or single base mismatches.
- The mutation repertoire can also be analyzed by using Sanger sequencing or deep sequencing.
- Indels can be determined by fragment analysis methods (Luo, 2019)
The efficiency of the CRISPR experiment depends on the suitable single guide RNA (sgRNA).To Produce quality results, sgRNA design must support on-target efficiency and minimum off-target cleavage events of the endonuclease. Many computational tools and machine learning techniques are used to design target-specific gRNA molecules.
- Luo, Y. (2019). CRISPR Gene Editing: Methods and Protocols (Methods in Molecular Biology) (1st ed. 2019 ed.). Humana.
- Wong, N., Liu, W. & Wang, X. WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system. Genome Biol 16, 218 (2015). https://doi.org/10.1186/s13059-015-0784-0
- Zhang, X.-H., Tee, L. Y., Wang, X.-G., Huang, Q.-S., & Yang, S.-H. (2015). Off-target Effects in CRISPR/Cas9-mediated Genome Engineering. Molecular Therapy – Nucleic Acids, 4, e264. https://doi.org/10.1038/mtna.2015.37
- Sander, J. D., & Joung, J. K. (2014). CRISPR-Cas systems for editing, regulating and targeting genomes. Nature biotechnology, 32(4), 347–355. https://doi.org/10.1038/nbt.2842
- Slaymaker, I. M., Gao, L., Zetsche, B., Scott, D. A., Yan, W. X., & Zhang, F. (2016). Rationally engineered Cas9 nucleases with improved specificity. Science (New York, N.Y.), 351(6268), 84–88. https://doi.org/10.1126/science.aad5227