BACKGROUND Cannabis has been used worldwide for centuries for industrial, recreational and medicinal use, however, to date no successful attempts at editing genes involved in cannabinoid biosynthesis have been reported. This study proposes and develops an in silico best practices approach for the design and implementation of genome editing technologies in cannabis to target all genes involved in cannabinoid biosynthesis. RESULTS A large dataset of reference genomes was accessed and mined to determine copy number variation and associated SNP variants for optimum target edit sites for genotype independent editing. Copy number variance and highly polymorphic gene sequences exist in the genome making genome editing using CRISPR, Zinc Fingers and TALENs technically difficult. Evaluation of allele or additional gene copies was determined through nucleotide and amino acid alignments with comparative sequence analysis performed. From determined gene copy number and presence of SNPs, multiple online CRISPR design tools were used to design sgRNA targeting every gene, accompanying allele and homologs throughout all involved pathways to create knockouts for further investigation. Universal sgRNA were designed for highly homologous sequences using MultiTargeter and visualised using Sequencher, creating unique sgRNA avoiding SNP and shared nucleotide locations targeting optimal edit sites. CONCLUSIONS Using this framework, the approach has wider applications to all plant species regardless of ploidy number or highly homologous gene sequences. SIGNIFICANCE STATEMENT Using this framework, a best-practice approach to genome editing is possible in all plant species, including cannabis, delivering a comprehensive in silico evaluation of the cannabinoid pathway diversity from a large set of whole genome sequences. Identification of SNP variants across all genes could improve genome editing potentially leading to novel applications across multiple disciplines, including agriculture and medicine.

中文翻译：

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计算机分析可实现药用大麻基因组编辑的知情设计；基因家族和变异特征。

背景技术几个世纪以来，大麻已在全世界用于工业、娱乐和医药用途，然而，迄今为止，尚未报道编辑涉及大麻素生物合成的基因的成功尝试。这项研究提出并开发了一种计算机最佳实践方法，用于设计和实施大麻基因组编辑技术，以针对涉及大麻素生物合成的所有基因。结果访问并挖掘了参考基因组的大型数据集，以确定拷贝数变异和相关的 SNP 变异，从而为基因型独立编辑提供最佳目标编辑位点。基因组中存在拷贝数变异和高度多态性的基因序列，使得使用 CRISPR、锌指和 TALEN 进行基因组编辑在技术上变得困难。通过核苷酸和氨基酸比对以及比较序列分析来确定等位基因或额外基因拷贝的评估。根据确定的基因拷贝数和 SNP 的存在，使用多种在线 CRISPR 设计工具来设计针对每个基因的 sgRNA，以及所有相关途径中的伴随等位基因和同源物，以创建敲除以供进一步研究。通用 sgRNA 使用 MultiTargeter 设计用于高度同源序列，并使用 Sequencher 进行可视化，创建独特的 sgRNA，避免针对最佳编辑位点的 SNP 和共享核苷酸位置。结论 使用该框架，该方法对所有植物物种都有更广泛的应用，无论倍性数或高度同源的基因序列如何。意义声明使用该框架，可以在包括大麻在内的所有植物物种中采用基因组编辑的最佳实践方法，从而对大量全基因组序列中的大麻素途径多样性进行全面的计算机评估。识别所有基因的 SNP 变异可以改善基因组编辑，从而可能在农业和医学等多个学科中产生新的应用。