Development of a Csy4-processed guide RNA delivery system with soybean-infecting virus ALSV for genome editing
Bibliographic record
Abstract
Abstract Background A key issue for implementation of CRISPR-Cas9 genome editing for plant trait improvement and gene function analysis is to efficiently deliver the components, including guide RNAs (gRNAs) and Cas9, into plants. Plant virus-based gRNA delivery strategy has proven to be an important tool for genome editing. However, its application in soybean which is an important crop has not been reported yet. ALSV (apple latent spherical virus) is highly infectious virus and could be explored for delivering elements for genome editing. Results To develop a ALSV-based gRNA delivery system, the Cas9-based Csy4-processed ALSV Carry (CCAC) system was developed. In this system, we engineered the soybean-infecting ALSV to carry and deliver gRNA(s). The endoribonuclease Csy4 effectively releases gRNAs that function efficiently in Cas9-mediated genome editing. Genome editing of endogenous phytoene desaturase (PDS) loci and exogenous 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) sequence in Nicotiana. benthamiana (N. benthamiana) through CCAC was confirmed using Sanger sequencing. Furthermore, CCAC-induced mutagenesis in two soybean endogenous GW2 paralogs was detected. Conclusions With the aid of the CCAC system, the target-specific gRNA(s) can be easily manipulated and efficiently delivered into soybean plant cells by viral infection. This is the first virus-based gRNA delivery system for soybean for genome editing and can be used for gene function study and trait improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".