Chromatin structure and context-dependent sequence features control prime editing efficiency.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Prime editing (PE) is a versatile CRISPR-Cas9 genome editing technology.
• Current PE constructs exhibit variable efficiency, necessitating experimental optimization.

Purpose of the Study:

• Develop statistical models to identify factors influencing PE efficiency.
• Provide guidelines for designing more effective PE systems.

Main Methods:

• Statistical modeling to analyze epigenomic and sequence features of target sites.
• Investigated effects of chromatin structure (heterochromatin, nucleosomes) on editing.
• Analyzed sequence composition (G/C nucleotides, PAM, template regions) of prime editing guide RNA (pegRNA).

Main Results:

• Constitutive heterochromatin and nucleosome occlusion hinder PE efficiency.
• Specific G/C nucleotide positions in pegRNA's primer-binding site (PBS) and reverse transcription (RT) template enhance editing.
• Identified AGG as a preferred protospacer adjacent motif (PAM) and a guanine four bases downstream of PAM facilitating editing.
• Discovered multi-nucleotide preferences and base dependencies within pegRNA using neural network analysis.

Conclusions:

• Epigenomic context and pegRNA sequence features critically impact PE efficiency.
• Optimized PE designs can be achieved by considering identified sequence and structural determinants.
• This study clarifies previous findings and offers a predictive framework for enhancing prime editing outcomes.