The soybean GmDi19-5 interacts with GmLEA3.1 and increases sensitivity of transgenic plants to abiotic stresses
Bibliographic record
Abstract
Drought-induced (Di19) proteins played important roles in plant growth, development, and abiotic stress responses. In the present study, a total of seven Di19 genes were identified in soybean. Each soybean Di19 gene showed specific responses to salt, drought, oxidative, and ABA stresses based on expression profiles. With a relatively higher transcript level among Di19 members under four stress treatments, GmDi19-5 was selected for detailed analysis. Inhibitor assays revealed that ABA inhibitor (Fluridone) or H2O2 inhibitor (DMTU) was involved in the drought- or salt-induced transcription of GmDi19-5. The GUS activity driven by the GmDi19-5 promoter was induced by salt, PEG, ABA, and MV treatments and tended to be accumulated in the vascular bundles and young leaves. A subcellular localization assay showed that GmDi19-5 protein localized in the nucleus. Further investigation showed that GmDi19-5 protein was involved in the interaction with GmLEA3.1. Overexpression of GmDi19-5 increased sensitivity of transgenic Arabidopsis plants to salt, drought, oxidative, and ABA stresses and regulated expression of several ABA/stress-associated genes. This present investigation showed that GmDi19-5 functioned as a negative factor under abiotic stresses and was involved in ABA and SOS signaling pathway by altering transcription of stress-associated genes.
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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 | 0.000 |
| 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".