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Parallel engineering and activity profiling of a base editor system.

John H C Fong¹, Hoi Yee Chu², Peng Zhou²

¹Laboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China.

|May 10, 2023

Summary

This summary is machine-generated.

This study introduces a platform for evaluating base editor variants, crucial for precise genome editing. It enables large-scale comparisons to identify efficient and accurate tools for genetic engineering.

Keywords:

CRISPR CombiSEAL base editing combinatorial assembly deaminase editing outcome genome editing guide RNA scaffold high-throughput screening precise genome editor

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Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

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Published on: February 28, 2021

Area of Science:

Genomics
Molecular Biology
Biotechnology

Background:

Precise genome editing relies on efficient base editors with minimal off-target effects.
A growing number of engineered base editor components necessitate standardized evaluation methods.

Purpose of the Study:

To develop and utilize a scalable platform for head-to-head comparison of engineered base editor variants.
To quantitatively assess editing efficiency, purity, motif preference, and biases of base editors.
To explore guide RNA scaffold engineering for enhancing base editor activity.

Main Methods:

Creation and analysis of a library of engineered base editor variants.
Quantitative benchmarking of editing outcomes including efficiency, purity, and indel generation.
Investigation of guide RNA scaffold variants to improve base editing activity.

Main Results:

Comprehensive quantitative data on the performance of various base editor variants.
Identification of undesired indel generation and noncanonical base conversions in some existing editors.
Demonstration of guide RNA scaffold variants enhancing base editor activity.

Conclusions:

The developed platform provides an unbiased, scalable method for benchmarking base editor performance.
This facilitates the engineering of next-generation precise genome editors.
It addresses the need for standardized evaluation in the rapidly evolving field of base editing.