DAJIN enables multiplex genotyping to simultaneously validate intended and unintended target genome editing outcomes

Proofing gene editing helps avoid unintended mutations

30 June 2022

Newly developed software enables researchers to reliably identify and classify all mutations induced by gene editing, both intentional and unintentional ones.

With the development of the CRISPR-Cas9 gene-editing technique over a decade ago, gene editing has really taken off. But since gene-editing techniques can cause unintended mutations, it is important to screen for them.

Now, a team led by researchers from University of Tsukuba in Japan has developed a program that can identify intended and unintended mutations caused by gene editing and uses deep learning to classify mutations according to type.

Unlike other programs that can only identify up to two different gene arrangements, the software can identify and classify most mutations even a pool consisting of many possible mutations. Furthermore, it can process up to about 100 samples at once.

The team has made the code freely available on the software repository GitHub.

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References

1. PLoS Biology 20, e3001507 (2022). doi: 10.1371/journal.pbio.3001507