Expression study of soybean germin-like gene family reveals a role of <i>GLP7</i> gene in various abiotic stress tolerances
Bibliographic record
Abstract
Germin-like proteins (GLPs) are ubiquitous plant glycoproteins (belonging to the cupin super family) that play diverse roles, including abiotic stress resistance in many plant species. To identify the molecular functions underlying abiotic stress responses, the expression of germin-like protein encoding genes of soybean GmGLPs was analyzed. qRT-PCR analyses of 21 GmGLPs transcripts abundances were conducted in soybean leave tissues. The results showed that GmGLPs transcripts were highly abundant upon treatments with high salinity, PEG6000, abscisic acid (ABA) and methyl viologen (MV). The peaks of transcript copiousness induced by PEG6000 and NaCl were mostly observed after 18 h, while some genes expressed earlier than 4 h after abiotic stress treatment. A specific GmGLP7 gene, that was highly abundant under salinity, drought, ABA and MV conditions, was further characterized. The ectopic overexpression of GmGLP7 (Glyma.08G226800.1) in transgenic Arabidopsis enhanced drought, salt, and oxidative tolerance and resulted in hypersensitive phenotypes toward ABA-mediated seed germination and primary root elongation, compared to the wild-type. Taken together, these results suggest that GmGLP7 positively confers abiotic tolerance in 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 | 0.000 |
| 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".