Fast and scalable off-target assessment for CRISPR guide RNAs using partial matches

Abstract

The design of CRISPR-Cas9 guide RNAs is not trivial. In particular, it is crucial to evaluate the risk of unintended, off-target modifications, but this is computationally expensive. To avoid a brute-force approach where each guide RNA is compared against every possible CRISPR target site in the genome, we previously introduced Crackling, a guide RNA design tool that relies on exact matches over 4bp subsequences to approximate a neighbourhood and accelerate off-target scoring by greatly reducing the search space. While this was faster than other existing tools, it still generates large neighbourhoods. Here, we aim to further reduce the search space by requiring more, now non-contiguous, exact matches. The new implementation, called Crackling++, is benchmarked against our initial approach and other off-target evaluation tools. We show that it provides the fastest way to assess candidate guide RNAs. By using memorymapped files, it also scales to the largest genomes. Crackling++ is available at https://github.com/bmds-lab/CracklingPlusPlus under the Berkeley Software Distribution (BSD) 3-Clause license.