Development of Agrobacterium-mediated transient expression system in Caragana intermedia and characterization of CiDREB1C in stress response
Bibliographic record
Abstract
BACKGROUND: The Agrobacterium-mediated transient transformation is a versatile and indispensable way of rapid analyzing gene function in plants. Despite this transient expression system has been successfully applied in a number of plant species, it is poorly developed in Caragana intermedia. RESULTS: In this study, we established an Agrobacterium-mediated transient expression system in C. intermedia leaves and optimized the effect of different Agrobacterial strains, several surfactants and the concentration of Silwet L-77, which would affect transient expression efficiency. Among the 5 Agrobacterial strains examined, GV3101 produced the highest GUS expression level. Besides, higher level of transient expression was observed in plants infiltrated with Silwet L-77 than with Triton X-100 or Tween-20. Silwet L-77 at a concentration of 0.001% greatly improved the level of GUS transient expression. Real-time PCR showed that expression of CiDREB1C was highly up-regulated in transiently expressed plants and reached the highest level at the 2nd day after infiltration. Based on this optimized transient transformation method, we characterized CiDREB1C function in response to drought, salt and ABA treatment. The results showed that transiently expressed CiDREB1C in C. intermedia leaves could enhance the survival rate and chlorophyll content, and reduce the lodging rate compared with the control seedlings under drought, salt and ABA treatments. Furthermore, the rate of leaf shedding of CiDREB1C transient expression seedlings was lower than that of the control under ABA treatment. CONCLUSIONS: The optimized transient expression condition in C. intermedia leaves were infiltrated with Agrobacterial strains GV3101 plus Silwet L-77 at a concentration of 0.001% added into the infiltration medium. Transiently expressed CiDREB1C enhanced drought, salt and ABA stress tolerance, indicated that it was a suitable and effective tool to determine gene function involved in abiotic stress response in C. intermedia.
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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 | 0.001 |
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".