A benchmark of computational CRISPR-Cas9 guide design methods
A benchmark of computational CRISPR-Cas9 guide design methods
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DOI：
10.1371/journal.pcbi.1007274
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发表时间：
2019-08-01
影响因子：
4.3
通讯作者：
Perrin, Dimitri
中科院分区：
文献类型：
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作者：
Bradford, Jacob;Perrin, Dimitri
基于 CRISPR 的基因编辑的流行带来了丰富的 CRISPR-Cas9 向导设计工具。这也是因为在使用 CRISPR 进行基因编辑时，设计高度特异性和高效的向导是一项至关重要但并非微不足道的任务。在这里，我们深入分析了18种设计工具的性能。它们是根据运行时性能、计算要求和生成的指南进行评估的。为了实现这一目标，我们实施了一种在给定工具执行时审核系统资源的方法，并在源自小鼠基因组的不断增大的数据集上测试了每个工具。我们发现只有五种工具的计算性能允许它们在合理的时间内分析整个基因组，并且不会耗尽计算资源。所确定的指南存在很大差异，一些工具报告所有可能的指南，而另一些工具则根据预测的效率进行筛选。一些工具也未能排除针对基因组中多个位置的指导。我们还考虑了两个集合，每个集合都有超过一千个指南，其中有可用的实验数据。数据集之间的性能存在很大差异，但工具的相对顺序部分保留。重要的是，最引人注目的结果是这些工具之间缺乏共识。我们的结果表明，CRISPR-Cas9 引导设计工具需要进一步的工作才能实现快速的全基因组分析，并且引导设计的改进可能需要结合多种方法。
The popularity of CRISPR-based gene editing has resulted in an abundance of tools to design CRISPR-Cas9 guides. This is also driven by the fact that designing highly specific and efficient guides is a crucial, but not trivial, task in using CRISPR for gene editing. Here, we thoroughly analyse the performance of 18 design tools. They are evaluated based on runtime performance, compute requirements, and guides generated. To achieve this, we implemented a method for auditing system resources while a given tool executes, and tested each tool on datasets of increasing size, derived from the mouse genome. We found that only five tools had a computational performance that would allow them to analyse an entire genome in a reasonable time, and without exhausting computing resources. There was wide variation in the guides identified, with some tools reporting every possible guide while others filtered for predicted efficiency. Some tools also failed to exclude guides that would target multiple positions in the genome. We also considered two collections with over a thousand guides each, for which experimental data is available. There is a lot of variation in performance between the datasets, but the relative order of the tools is partially conserved. Importantly, the most striking result is a lack of consensus between the tools. Our results show that CRISPR-Cas9 guide design tools need further work in order to achieve rapid whole-genome analysis and that improvements in guide design will likely require combining multiple approaches.