Abstract
Prime editing (PE) is a recent advancement in CRISPR-Cas9 technology that involves the fusion of a reverse transcriptase (RT) to a Cas9 nickase (nCas9). This fusion protein is complexed with a prime editing guide RNA (pegRNA), which includes both a spacer sequence for Cas9 targeting and a template used by the RT to install desired edits into the genome. This system can generate small-scale insertions, deletions, and substitutions while elegantly bypassing double-stranded break formation, reducing the risk of unwanted indels and off-target editing. However, there is high variability in editing reported by different studies using different methodologies and disease models. In this review, we systematically examine how PE performs in different models and how different approaches improve or hinder PE efficiency. Furthermore, as assessing DNA editing efficiency is a time-consuming process, we discuss reporter assays used to detect editing events and select for edited cells. Finally, we examine the detected downstream effects of PE and investigate potential explanations for variability between models. Taken together, this review provides a valuable insight for researchers as to how PE may perform in their chosen cellular and animal models and how to effectively analyze and troubleshoot their PE experiments.