CRISPys: Optimal sgRNA Design for Editing Multiple Members of a Gene Family Using the CRISPR System. Issue 15 (20th July 2018) - Hyams, Gal; Abadi, Shiran; Lahav, Shlomtzion; Avni, Adi; Halperin, Eran; Shani, Eilon; Mayrose, Itay
Abstract: The development of the CRISPR–Cas9 system in recent years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simple and effective task. The system is directed to a genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with it, subsequently leading to site-specific modifications. However, many gene families in eukaryotic genomes exhibit partially overlapping functions, and thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR–Cas9 system, which may lead to the modification of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. We introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the efficiency to edit the induced targets is maximized. We suggest several approaches for designing the optimal individual sgRNA and an approach to compute the optimal set of sgRNAs for cases when the experimental platform allows for more than one. The latter may optionally account for the homologous relationships among gene-family members. We further show that CRISPys outperforms simpler alignment-based techniques by in silico examination over all gene families in the Solanum lycopersicum genome. Graphical Abstract: Highlights: Many genes in eukaryotic genomes exhibit partially overlapping functions. This imposes difficulties on reverse-genetics, as the knockout of one gene might be concealed by the function of the other. We present CRISPys, a graph-based algorithm for the optimal design of CRISPR systems given a set of redundant genes. CRISPys harnesses the lack of specificity of the CRISPR–Cas9 genome editing technique, providing researchers the ability to simultaneously mutate multiple genes. We show that CRISPys outperforms existing approaches that are based on simple alignment of the input gene family.