3/20/2024 0 Comments Sure cuts a lot 2 knockout textWe developed a novel web-based tool, CRISPOR ( ), to assist with guide selection in 120 genomes, including plants and many emerging model organisms, and pre-calculated results for all human coding exons as a UCSC Genome Browser track. The optimal selection parameters that we identified were integrated into a new CRISPR/Cas9 guide designer tool. In this article, we compare existing scoring systems against published datasets and our own experimental data. Although published tools and scoring systems allow ranking sequences by specificity and efficiency, they are usually limited to a handful of genomes and only few evidence-based recommendations exist to optimize off-target search parameters and on-target efficiency. The guide sequence also determines the efficiency of on-target cleavage thus, current genome editing protocols recommend that researchers select guides carefully to minimize potential off-target effects and test several to optimize on-target activity. As more researchers face the task of selecting an optimal Cas9 guide RNA sequence that targets a genome sequence of interest, the overall specificity of the technique is still under discussion: high-throughput cell culture studies have found numerous off-targets not predicted by existing algorithms, sometimes even involving 1-bp indels (“bulges”) in the alignment with the guide sequence, while studies in Drosophila, Caenorhabditis elegans, zebrafish, and mice have found virtually no off-target effects. The CRISPR/Cas9 “revolution” is sweeping through the life sciences. To make these guidelines easily accessible to anyone planning a CRISPR genome editing experiment, we built a new website ( ) that predicts off-targets and helps select and clone efficient guide sequences for more than 120 genomes using different Cas9 proteins and the eight efficiency scoring systems evaluated here. We further demonstrate that the best predictions can significantly reduce the time spent on guide screening. Together with novel data from our labs, we find that the optimal on-target efficiency prediction model strongly depends on whether the guide RNA is expressed from a U6 promoter or transcribed in vitro. The correlation between the predictions and the guide activity varied considerably, especially for zebrafish. We also evaluate on-target efficiency prediction algorithms against available datasets. We identify problems in one implementation but found that sequence-based off-target predictions are very reliable, identifying most off-targets with mutation rates superior to 0.1 %, while the number of false positives can be largely reduced with a cutoff on the off-target score. To this end, we collect data from eight SpCas9 off-target studies and compare them with the sites predicted by popular algorithms. We conduct the first independent evaluation of CRISPR/Cas9 predictions. Despite the importance and popularity of these algorithms, it is unclear to which extent their predictions are in agreement with actual measurements. The success of the CRISPR/Cas9 genome editing technique depends on the choice of the guide RNA sequence, which is facilitated by various websites.
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