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Rigorous alignment tools ensure high specificity of gene editing
Streptococcus pyogenes CRISPR-Cas9 system can be used for genome engineering in mammalian cells, as well as other eukaryotic organisms. The natural CRISPR-Cas9 system consists of Cas9 nuclease and two RNAs, a CRISPR RNA (crRNA) comprised of a spacer-derived sequence and a repeat-derived sequence, and a trans-activating CRISPR RNA (tracrRNA), which hybridizes to the crRNA through repeat-derived sequences. The crRNA:tracrRNA complex guides the Cas9 nuclease and cleaves DNA upstream of a protospacer-adjacent motif (PAM), typically NGG for S. pyogenes. Designing a guide RNA to create a double strand break (DSB) at a specific genomic location can seem straightforward (just look for a PAM site) but there are many factors to consider for ensuring that the genome editing occurs only at the desired location, since any unintended edits, or off-targets, are permanent and heritable changes in the genome.
Figure 1. Variable tolerance for flaws along the guide RNA.
Off-targets can occur when a guide RNA has sequence homology to other areas of the genome. Also, off-targeting has been shown to occur with imperfect complementarity between the guide RNA and the genome, which complicates the task of anticipating where a guide RNA might cause off-targets. It has been shown that mismatches within the guide RNA seed region (8-12 nt proximal to the PAM site) are more likely to disrupt target recognition and Cas9 nuclease will not cleave at that site (Figure 1A). However, there is greater tolerance for mismatches or gaps further away from the PAM, leading to potential off-target cleavage (Figure 1B). Therefore, it is necessary to avoid the use of guide RNAs that could result in off-target genome editing, as it could lead to misinterpretation of experimental data.
There are many publicly available guide RNA design and specificity tools. However, they do not identify all potential off-target sites because they (a) only identify RNA-DNA mismatches as potential off-target sites, not gaps and bulges and (b) are not rigorous enough to identify all alignments. The Dharmacon CRISPR specificity analysis tool not only identifies multiple mismatches, but also considers gaps between the RNA and DNA sequence for off-target identification, which we collectively refer to as "flaws" (Figure 2A).
We selected a target sequence and compared our alignment tool to other publically available guide RNA design and alignment tools. All tools found the intended target (perfect match) shown as the single alignment in the "zero flaws" column, and all of the tools confirmed that there were no single flaw alignments (Figure 2B). However, beyond one-flaw alignments, the Dharmacon CRISPR specificity analysis tool was the only one that identified four target sites with two flaws, and overwhelmingly was able to identify alignments with three flaws, illustrating the rigor of the Dharmacon tool. In a subsequent experiment it was observed that a guide RNA with two flaws resulted in significant editing at a predicted off-target locus (data not shown). Therefore, avoiding guide RNAs with any potential off-targets is especially important for cell line generation, in vivo, or therapeutic applications.
Figure 2. A. More rigorous identification of both mismatches AND gaps between a DNA target and guide RNA is required to avoid all potential off-targets. B. Comparison of the number of off-target alignments found by Dharmacon CRISPR specificity analysis tool versus other CRISPR tools.
The Dharmacon Edit-R proprietary design algorithm for guide RNAs (synthetic crRNA and lentiviral sgRNA) incorporates specificity analysis results to predesign easy-to-order reagents for high specificity and gene editing efficiency for human, mouse and rat model organisms. Just search for your gene and select from the available designs.
Figure 3. (A) Input a gene identifier or DNA sequence and the Dharmacon CRISPR RNA Configurator will return (B) target sequences for synthetic crRNAs and/or lentiviral sgRNAs.
The CRISPR RNA Configurator makes it easy to design guide RNAs, and is amenable to many experimental applications. There are two options to design a custom guide RNA (Figure 3A).
The Configurator will find the PAMs and check specificity for all guide RNAs designed to your genomic sequence. Then you can confidently choose the guide RNAs for your experiment as synthetic crRNA or lentiviral sgRNA (Figure 3B). We recommend testing 3-5 guide RNAs per gene target to identify the one that is most efficient in your cells.
And the Configurator can currently design to 33 species!
If you already have a guide RNA sequence, use the CRISPR Specificity Analysis tool to assess its specificity. You might be surprised by what you find!
To identify criteria for choosing the best functional guide RNA, we developed an algorithm based on functional gene knockout using a phenotypic assay for proteasome function with a GFP readout. Get an overview of how the Edit-R algorithm was developed to select guide RNAs more likely to cause functional protein knockout.
High quality, ready-to-use lentiviral and synthetic reagents to guide Cas9 cleavage
Optimized tools for high-confidence genome engineering
Configure the optimal promoter for your cell type to ensure robust Cas9 expression or explore DNA-free options
Proper controls are essential to assessment of CRISPR-Cas9 genomic editing experiments
Pooled sgRNA or arrayed crRNA for high-throughput gene editing studies