Published December 11, 2025 | Version v1
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Amplicon sequencing pipeline files for developing an efficient CRISPR/Cas9 system in plants: a test case in Lotus japonicus

Description

Files for PCR amplicon-based NGS analysis to quantify CRISPR/Cas9 editing events. Part of the work: Developing an efficient CRISPR/Cas9 system in plants: a test case in Lotus japonicus

CRISPR/Cas9-based genome editing is usually employed for both plant functional genomics and trait engineering, with associated components being most commonly delivered via Agrobacterium-mediated T-DNA transformation. Establishing a functional CRISPR/Cas9 system, however, remains an arduous task, despite the well-established delivery method. Here, leveraging the principles of synthetic biology and the Design-Build-Test-Learn framework (DBTL), we describe a step-by-step guide for developing an efficient T-DNA-based CRISPR/Cas9 system in plants, using Lotus japonicus as a case study. The first step involves rational design of the T-DNA region by selecting characterized genetic parts and arranging expression cassettes logically, in various combinations, generating multiple T-DNA architecture variants. The second step includes the assembly of the T-DNA variants into constructs via a flexible cloning scheme. The third and fourth steps include introducing the T-DNA variants into the plant and evaluating their mutation efficiency, using both an optimized T7 endonuclease I-based assay and an amplicon sequencing analysis. We employed two iterative DBTL cycles to identify and improve sub-optimal parts in our constructs and investigated factors that may affect the mutation efficiency of the system. We also observed that the CRISPR/Cas9 activity, but not specificity, can be affected by both the codon-optimization of the Cas9 sequence and the plant growth conditions. This study provides a reference for establishing an efficient CRISPR/Cas9 system in plants by outlining key methodological considerations for successful implementation.

Files

Double35S_Lb3.txt

Files (28.7 kB)

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md5:91e3bbabe4592f3fee3c988aff48e6ca
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