Activity-based selection for enhanced base editor mutational scanning.

Area of Science:

• Genomics
• Molecular Biology
• Biotechnology

Background:

• CRISPR-based base editing allows nucleotide-level genome interrogation for disease research and therapeutic development.
• Base editing screens are powerful but hampered by cell-to-cell variability in editing efficiency, introducing noise.
• High-throughput functional genomic studies require precise and efficient editing tools.

Purpose of the Study:

• To develop a co-selection method to enrich cells with high base editing activity.
• To enhance the efficiency and reduce noise in base editing screens.
• To improve the resolution of base editing screens for pinpointing functional genetic elements.

Main Methods:

• Development of a novel co-selection strategy for base editing.
• Enrichment of cells exhibiting high base editing efficiency.
• Evaluation of the method by tiling guide RNAs across the TP53 gene.

Main Results:

• The co-selection method substantially increased base editing efficiency at the target locus.
• The activity-based selection method demonstrated enhanced capacity to pinpoint specific mutations and protein regions.
• Comparison with traditional screening approaches showed improved precision.

Conclusions:

• The developed co-selection method significantly enhances base editing efficiency and reduces noise.
• This approach improves the ability to identify functionally important mutations and protein regions.
• The modular selection method is anticipated to boost the resolution of base editing screens across diverse applications.