Chari Raj, Yeo Nan Cher, Chavez Alejandro, Church George M
Department of Genetics, Harvard Medical School , Boston, Massachusetts 02115, United States.
Wyss Institute for Biologically Inspired Engineering, Harvard University , Boston, Massachusetts 02115, United States.
ACS Synth Biol. 2017 May 19;6(5):902-904. doi: 10.1021/acssynbio.6b00343. Epub 2017 Feb 10.
It has been possible to create tools to predict single guide RNA (sgRNA) activity in the CRISPR/Cas9 system derived from Streptococcus pyogenes due to the large amount of data that has been generated in sgRNA library screens. However, with the discovery of additional CRISPR systems from different bacteria, which show potent activity in eukaryotic cells, the approach of generating large data sets for each of these systems to predict their activity is not tractable. Here, we present a new guide RNA tool that can predict sgRNA activity across multiple CRISPR systems. In addition to predicting activity for Cas9 from S. pyogenes and Streptococcus thermophilus CRISPR1, we experimentally demonstrate that our algorithm can predict activity for Cas9 from Staphylococcus aureus and S. thermophilus CRISPR3. We also have made available a new version of our software, sgRNA Scorer 2.0, which will allow users to identify sgRNA sites for any PAM sequence of interest.
由于在sgRNA文库筛选中产生了大量数据，已经能够创建工具来预测源自化脓性链球菌的CRISPR/Cas9系统中单个向导RNA（sgRNA）的活性。然而，随着从不同细菌中发现了其他CRISPR系统，这些系统在真核细胞中显示出强大的活性，为每个系统生成大量数据集以预测其活性的方法并不容易处理。在这里，我们展示了一种新的向导RNA工具，它可以预测多个CRISPR系统中的sgRNA活性。除了预测化脓性链球菌和嗜热链球菌CRISPR1的Cas9活性外，我们还通过实验证明，我们的算法可以预测金黄色葡萄球菌和嗜热链球菌CRISPR3的Cas9活性。我们还提供了软件的新版本sgRNA Scorer 2.0，它将允许用户识别任何感兴趣的PAM序列的sgRNA位点。
