Predicting prime editing efficiency and product purity by deep learning.

Abstract excerpt

Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423 pegRNAs on a highly diverse set of 13,349 human pathogenic mutations that include base substitutions, insertions and deletions. Based on this dataset, we identified...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to CRISPR-Cas Systems
• Share to Deep Learning