• CRISPR-Cas9 Guide RNA Functionality

    CRISPR-Cas9 Guide RNA Functionality

    Development of an algorithm for functional knockout, not just cutting

    The role of guide RNAs in CRISPR Cas-9 gene knockout

    The S. pyogenes Cas9 nuclease can be programmed by a guide RNA to create double-strand breaks (DSB) at a particular genomic region. Imperfect repair of the DSB can lead to loss of function of the targeted gene. Although most guide RNA target sites result in some level of DNA editing (insertions or deletions), not all result in editing that causes a functional gene disruption or gene knockout. Therefore, it is necessary to consider various factors, including the location of the CRISPR-Cas9 target sequence within the gene, when designing a guide RNA for gene knockout.

    Phenotypic data from functional gene knockout

    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. The data training set for the algorithm consisted of > 1100 crRNAs targeting 10 genes. We chemically synthesized the crRNAs, rather than cloning and sequencing sgRNAs, to remove any variability in the level of the expressed sgRNAs, and also to save time and cost. The overall results indicate that location of the guide RNA alone is not an indicator for functional gene knockout, and that it is not best practice to design a guide RNA too close to the ATG start site. Figure 1A demonstrates that although guide RNAs in an early exon gave good indel formation, the functional GFP data (Figure 1B; data points in red circle) indicate that these indels did not produce a phenotype in the assay.

    Figure 1B is an example of the training data set, in this case, targeting the PSMD8 gene, which illustrates the range of functionality of crRNAs across the entire coding region.

    From this training data, we identified many algorithm design rules for choosing the best guide RNAs that include:

    • Cut site location within the gene
    • Sequence composition around cut site
    • Sequence within/around the PAM
    • GC content
    • Strand preference

    Validating the Edit-R algorithm

    To validate the design algorithm, we used next-generation sequencing (NGS) analysis to calculate indel formation. While this does not indicate functional gene knockout, it still requires delivery of the CRISPR-Cas9 reagents, binding to the genomic target site, and cutting and repair of DNA. We also expected to see a difference in indel frequency between the algorithm designed high- and low-scoring crRNAs based on the data training set.

    The algorithm was used to design crRNAs for 10 different genes. We selected 10 high-scoring and 10 low-scoring crRNAs for each gene, which were transfected, along with tracrRNA, into HEK293T cells and performed NGS analysis to calculate percentage of DNA with indel formation. Ninety-three percent of the crRNAs with higher functional scores resulted in > 40% indel formation, and low-scoring designs had only 33% of the crRNAs with > 40% indel formation (Figure 2A).

    We also validated the algorithm designs using additional phenotypic assays, different from the phenotypic GFP readout used in the training set data. In this example, crRNAs were designed to all PAMs within the open reading frame of three target genes involved in the cellular apoptotic pathway: BCL2L1, PLK1 and WEE1. The crRNAs were divided into two bins based on the algorithm functional score; the bins were designated as the top half scores and the bottom half scores (Figure 2B). These data show that the higher scoring crRNAs resulted in a stronger phenotype than the low-scoring crRNAs, again demonstrating the benefits of using an algorithm to design functional guide RNA.

    Edit-R predesigned guide RNAs for easy ordering!

    Edit-R proprietary functional design algorithm for guide RNAs (synthetic crRNA and lentiviral sgRNA) results in easy to order predesigns for high specify and high functionality for gene editing in human, mouse and rat model organisms.

    CRISPR-Cas9 Guide RNA Specificity

    Identification of potential off-target cleavage sites is essential for CRISPR specificity. Learn more about the alignment tools and strategies available.

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    1. E.M. Anderson, A. Haupt, et al., Systematic analysis of CRISPR-Cas9 mismatch tolerance reveals low levels of off-target activity. J. Biotechnol. 211, 56-65 (2015).