Alanine Aminotransferase Variants Conferring Diverse NUE Phenotypes in Arabidopsis thaliana
Bibliographic record
Abstract
Alanine aminotransferase (AlaAT, E.C. 2.6.1.2), is a pyridoxal-5'-phosphate-dependent (PLP) enzyme that catalyzes the reversible transfer of an amino group from alanine to 2-oxoglutarate to produce glutamate and pyruvate, or vice versa. It has been well documented in both greenhouse and field studies that tissue-specific over-expression of AlaAT from barley (Hordeum vulgare, HvAlaAT) results in a significant increase in plant NUE in both canola and rice. While the physical phenotypes associated with over-expression of HvAlaAT have been well characterized, the role this enzyme plays in vivo to create a more N efficient plant remains unknown. Furthermore, the importance of HvAlaAT, in contrast to other AlaAT enzyme homologues in creating this phenotype has not yet been explored. To address the role of AlaAT in NUE, AlaAT variants from diverse sources and different subcellular locations, were expressed in the wild-type Arabidopsis thaliana Col-0 background and alaat1;2 (alaat1-1;alaat2-1) knockout background in various N environments. The analysis and comparison of both the physical and physiological properties of AlaAT over-expressing transgenic plants demonstrated significant differences between plants expressing the different AlaAT enzymes under different external conditions. This analysis indicates that the over-expression of AlaAT variants other than HvAlaAT in crop plants could further increase the NUE phenotype(s) previously observed.
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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".