Designing genome editing experiments with EditABLE
While many computational tools exist for designing CRISPR-Cas experiments, there is a need for a centralized resource that combines individual tools to predict the most efficient genome editing strategy for a given application. To fill this gap, we develop EditABLE (EditABLE-app.stanford.edu), an online resource that provides optimal CRISPR editors and guide RNAs based on user provided sequence data with functionalities for base editing, prime editing, and integrase-mediated editing. We demonstrate the utility of EditABLE by applying it to one of the most common monogenic disorders, autosomal dominant polycystic kidney disease (ADPKD), identifying specific editing tools across the ADPKD mutation landscape.
Authors
- Juliet Sostena
- Vivek Bhalla (ORCID: https://orcid.org/0000-0002-5420-9657)
- Vivek Charu (ORCID: https://orcid.org/0000-0002-7147-9026)
- Shuchi Anand (ORCID: https://orcid.org/0000-0002-9892-8477)
- MS Demetrios Maxim (ORCID: https://orcid.org/0000-0002-9250-8674)
- David Wu
- George M. Church (ORCID: https://orcid.org/0000-0002-0775-2913)
- Najani Shanee Johnson
- Jennefer N. Carter
Institutions
- Ithaka Harbors (US)
- Albany State University (US)
- Harvard University (US)
- University at Albany, State University of New York (US)
- Stanford Medicine (US)
- Reprogenetics (US)
- University of Pennsylvania (US)
- Stanford University (US)
Publication Details
- Journal
- Genome biology
- Published
- 2026-05-11
- DOI
- https://doi.org/10.1186/s13059-026-04095-x
- Primary Topic
- CRISPR and Genetic Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Diabetes and Digestive and Kidney Diseases
- Stanford Maternal and Child Health Research Institute