sgRNA Scorer 2.0: A Species-Independent Model To Predict CRISPR/Cas9 Activity

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.