Increased genome editing efficiency in poplar by optimizing sgRNA length and copy number

The CRISPR/Cas9 system has achieved remarkable success in genome engineering; however, its application in woody plants remains challenging due to their complex genomic architecture and low transformation efficiency. This study established an optimized CRISPR/Cas9-based genome editing strategy for 84 K poplar ( Populus alba × Populus tremula var. glandulosa ), achieving editing efficiencies of up to 50 % through systematic optimization of transformation conditions. Comprehensive analysis revealed two critical factors determining editing efficiency: sgRNA length and copy number. Among targeting sequences spanning 18–22 nucleotides, 20 nt sgRNA exhibited optimal performance with 30 % editing efficiency following a normal distribution pattern relative to sgRNA length. Integration of triple sgRNA copies enhanced editing outcomes, particularly for allelic and homologous gene editing. Three candidate reporter genes, PDS , HEMA , and RbcS, were evaluated for monitoring editing outcomes. PDS and HEMA proved effective for detecting biallelic null mutations but were unsuitable for identifying monoallelic editing. This optimized protocol establishes a robust foundation for genetic manipulation in forest trees, advancing fundamental research and biotechnology applications in sustainable forestry. • High genome editing efficiency of approximately 50 % was achieved in 84 K poplar. • The 20 nt sgRNA demonstrated the highest editing efficiency among the tested range of 18–22 nt. • Triple sgRNA constructs enhanced editing outcomes for allelic and homologous genes. • Phenotypic changes in PDS and HEMA served as visible reporters for biallelic mutations.

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Publication Details

Journal
Industrial Crops and Products
Published
2025-02-12
DOI
https://doi.org/10.1016/j.indcrop.2025.120664
Citations
4
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
3.22
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Increased genome editing efficiency in poplar by optimizing sgRNA length and copy number

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article

Increased genome editing efficiency in poplar by optimizing sgRNA length and copy number

Hai Lu, Yu Sun, Xueqin Guo, Yuqian Feng, Yuping Feng, Huimin Zhang, Di Liu
article en
4 citations

Abstract

The CRISPR/Cas9 system has achieved remarkable success in genome engineering; however, its application in woody plants remains challenging due to their complex genomic architecture and low transformation efficiency. This study established an optimized CRISPR/Cas9-based genome editing strategy for 84 K poplar ( Populus alba × Populus tremula var. glandulosa ), achieving editing efficiencies of up to 50 % through systematic optimization of transformation conditions. Comprehensive analysis revealed two critical factors determining editing efficiency: sgRNA length and copy number. Among targeting sequences spanning 18–22 nucleotides, 20 nt sgRNA exhibited optimal performance with 30 % editing efficiency following a normal distribution pattern relative to sgRNA length. Integration of triple sgRNA copies enhanced editing outcomes, particularly for allelic and homologous gene editing. Three candidate reporter genes, PDS , HEMA , and RbcS, were evaluated for monitoring editing outcomes. PDS and HEMA proved effective for detecting biallelic null mutations but were unsuitable for identifying monoallelic editing. This optimized protocol establishes a robust foundation for genetic manipulation in forest trees, advancing fundamental research and biotechnology applications in sustainable forestry. • High genome editing efficiency of approximately 50 % was achieved in 84 K poplar. • The 20 nt sgRNA demonstrated the highest editing efficiency among the tested range of 18–22 nt. • Triple sgRNA constructs enhanced editing outcomes for allelic and homologous genes. • Phenotypic changes in PDS and HEMA served as visible reporters for biallelic mutations.

Industrial Crops and ProductsVol. 226
Beijing Forestry University (CN), Research Institute of Forestry (CN)
Openalex Percentile: Top 9%
CRISPR and Genetic Engineering
3.22
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