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A side-by-side comparison of variant function measurements using deep mutational scanning and base editing.

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Deep Mutational Scanning (DMS) and CRISPR base editing (BE) show strong correlation for variant annotation. Optimizing BE methods, like filtering sgRNAs, improves accuracy for functional genomics research.

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Area of Science:

  • Mammalian functional genomics
  • CRISPR base editing technology
  • High-throughput screening

Background:

  • Variant annotation is essential for understanding gene function.
  • Deep Mutational Scanning (DMS) is a standard method, but CRISPR base editing (BE) offers a promising alternative.
  • Direct comparisons and validation needs for BE in variant annotation are unclear.

Purpose of the Study:

  • To directly compare Deep Mutational Scanning (DMS) and CRISPR base editing (BE) for variant annotation.
  • To assess the required experimental validation for BE-based variant function annotation.
  • To optimize BE screening strategies for improved data concordance with DMS.

Main Methods:

  • Performed parallel DMS and BE screens in the same cell line.
  • Applied filtering strategies to BE data, focusing on high-efficiency sgRNAs and single-edit outcomes.
  • Quantified variant effects by directly measuring edited variants in pooled screens.

Main Results:

  • Optimizing BE screens by selecting high-efficiency sgRNAs and focusing on likely edits significantly improved agreement with DMS data.
  • A simple filter for sgRNAs inducing single edits enabled direct variant annotation from pooled sgRNA sequencing.
  • Measuring actual variants in pooled BE screens, rather than sgRNA abundance, recovered high-quality annotation data, even with multi-edit guides.

Conclusions:

  • CRISPR base editing (BE) demonstrates a high degree of correlation with gold-standard Deep Mutational Scanning (DMS) for variant annotation.
  • Strategic filtering and direct variant measurement enhance the reliability and efficiency of BE for functional genomics.
  • BE is a viable and effective alternative for large-scale human gene variant annotation.