GmSYP24, a putative syntaxin gene, confers osmotic/drought, salt stress tolerances and ABA signal pathway
Bibliographic record
Abstract
As major environment factors, drought or high salinity affect crop growth, development and yield. Transgenic approach is an effective way to improve abiotic stress tolerance of crops. In this study, we comparatively analyzed gene structures, genome location, and the evolution of syntaxin proteins containing late embryogenesis abundant (LEA2) domain. GmSYP24 was identified as a dehydration-responsive gene. Our study showed that the GmSYP24 protein was located on the cell membrane. The overexpression of GmSYP24 (GmSYP24ox) in soybean and heteroexpression of GmSYP24 (GmSYP24hx) in Arabidopsis exhibited insensitivity to osmotic/drought and high salinity. However, wild type soybean, Arabidopsis, and the mutant of GmSYP24 homologous gene of Arabidopsis were sensitive to the stresses. Under the abiotic stresses, transgenic soybean plants had greater water content and higher activities of POD, SOD compared with non-transgenic controls. And the leaf stomatal density and opening were reduced in transgenic Arabidopsis. The sensitivity to ABA was decreased during seed germination of GmSYP24ox and GmSYP24hx. GmSYP24hx induced up-regulation of ABA-responsive genes. GmSYP24ox alters the expression of some aquaporins under osmotic/drought, salt, or ABA treatment. These results demonstrated that GmSYP24 played an important role in osmotic/drought or salt tolerance in ABA signal pathway.
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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".