Issue 28, 2024

A platform for precise quantification of gene editing products based on microfluidic chip-based digital PCR

Abstract

The new generation of gene editing technologies, primarily based on CRISPR/Cas9 and its derivatives, allows for more precise editing of organisms. However, when the editing efficiency is low, only a small fraction of gene fragments is edited, leaving behind minimal traces and making it difficult to detect and evaluate the editing effects. Although a series of technologies and methods have been developed, they lack the ability for precise quantification and quantitative analysis of these products. Digital polymerase chain reaction (dPCR) offers advantages such as high precision and sensitivity, making it suitable for absolute quantification of nucleic acid samples. In the present study, we developed a novel platform for precise quantification of gene editing products based on microfluidic chip-based dPCR. The results indicated that our assay accurately identified different types of edited samples within a variety of different types, including more complex genomic crops such as tetraploid rapeseed and soybean (highly repetitive sequence). The sensitivity of this detection platform was as low as 8.14 copies per μL, with a detection limit of 0.1%. These results demonstrated the superior performance of the platform, including high sensitivity, low detection limit, and wide applicability, enabling precise quantification and assessment of gene editing efficiency. In conclusion, microfluidic chip-based dPCR was used as a powerful tool for precise quantification and assessment of gene editing products.

Graphical abstract: A platform for precise quantification of gene editing products based on microfluidic chip-based digital PCR

Supplementary files

Article information

Article type
Paper
Submitted
09 May 2024
Accepted
09 Jun 2024
First published
14 Jun 2024

Anal. Methods, 2024,16, 4783-4793

A platform for precise quantification of gene editing products based on microfluidic chip-based digital PCR

J. Chi, L. Ding, X. Wang, X. Chen, C. Peng and J. Xu, Anal. Methods, 2024, 16, 4783 DOI: 10.1039/D4AY00863D

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