Establishing an Immune System Conferring DNA and RNA Virus Resistance in Plants Using CRISPR/Cas12a Multiplex Gene Editing
Bibliographic record
Abstract
ABSTRACT Two types of CRISPR/Cas systems (Cas9 and Cas13) have been used to combat eukaryotic viruses successfully. In this study, we established resistance to the DNA virus BSCTV and RNA virus TMV in Nicotiana benthamiana using the CRISPR‐Cas12a multiplex gene editing system. We employed two effector proteins LbCas12a and FnCas12a coupled with six guide RNAs targeting virus genome and a novel mRNA–gRNA nucleic acid complex to transport gRNA efficiently. Compared with the BSCTV accumulation in the wild‐type N. benthamiana, it was reduced by more than 90% by most transgenic events derived at 7 days post‐inoculation. Additionally, the shoot‐tip leaves were normal in the transgenic plants, whereas they appeared severely curled and stunted in wild‐type N. benthamiana at 15 days post‐infection. Target sites evaluation revealed that the editing system can directly destroy the structure of BSCTV viral genomes via large fragment deletions. We quantified TMV virus accumulation in the transgenic N. benthamiana lines by monitoring dynamic changes in GFP fluorescence and quantitative analysis by qPCR showed that the CRISPR‐Cas12a system can introduce TMV virus resistance to N. benthamiana by preventing its systemic spread. Our study provides an innovative strategy—an mRNA–gRNA nucleic acid complex—which has proven to be highly effective in the gene‐editing system and offers an efficient antiviral approach for generating virus‐resistant plants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".