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Updated: May 16, 2026

09:11
Genome Editing with CompoZr Custom Zinc Finger Nucleases (ZFNs)
Published on: June 14, 2012
Highly active zinc-finger nucleases by extended modular assembly.
Mital S Bhakta1, Isabelle M Henry, David G Ousterout
1Genome Center and Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA.
Genome Research
|December 11, 2012
Summary
Modular assembly (MA) of zinc-finger nucleases (ZFNs) can be inefficient. This study shows that longer, six-finger ZFN arrays significantly improve genome engineering success rates in human and mouse cells.
Area of Science:
- Molecular Biology
- Genome Engineering
- Biotechnology
Background:
- Zinc-finger nucleases (ZFNs) are crucial for genome engineering but their widespread adoption is limited by the lack of robust, noncommercial methods.
- The modular assembly (MA) method allows rapid ZFN creation but often results in inactive nucleases, particularly with three- and four-finger arrays, with success rates below 25%.
Purpose of the Study:
- To systematically investigate the impact of array length on ZFN activity and efficiency.
- To identify optimal ZFN designs for enhanced genome targeting and success rates.
Main Methods:
- Systematic study of ZFN array lengths, focusing on three- to six-finger combinations.
- Development and application of a novel drop-out linker scheme for rapid assessment of ZFN combinations.
- Analysis of 268 array variants, correlating activity with an ab initio B-score cutoff.
Main Results:
- Six-finger MA ZFN arrays successfully produced mutations at 71% (15 of 21) of targeted loci in human and mouse cells.
- Shorter arrays demonstrated improved activity in specific cases.
- Half of MA ZFNs exceeding an ab initio B-score cutoff of 15 were active, irrespective of array composition.
Conclusions:
- Optimizing ZFN array length, particularly using longer six-finger arrays, significantly enhances the success rate of genome engineering.
- The MA method, when appropriately applied with optimized array lengths, offers a highly effective approach for targeting diverse DNA sequences.
- This research provides a pathway to more robust and successful genome engineering applications using ZFN technology.

