Identification of genes and pathways associated with aluminum stress and tolerance using transcriptome profiling of wheat near-isogenic lines
Bibliographic record
Abstract
BACKGROUND: Aluminum is considered the most limiting factor for plant productivity in acidic soils, which cover large areas of the world's potential arable lands. The inhibition of root growth is recognized as the primary effect of Al toxicity. To identify genes associated with Al stress and tolerance, transcriptome analyses of four different wheat lines (2 Al-tolerant and 2 Al sensitive) that differ in their response to Al were performed. RESULTS: Microarray expression profiling revealed that 83 candidate genes are associated with Al stress and 25 are associated with tolerance. The stress-associated genes include important enzymes such as pyruvate dehydrogenase, alternative oxidase, and galactonolactone oxidase, ABC transporter and ascorbate oxido-reducatase. The Al tolerance-associated genes include the ALMT-1 malate transporter, glutathione S-transferase, germin/oxalate oxidase, fructose 1,6-bisphosphatase, cysteine-rich proteins, cytochrome P450 monooxygenase, cellulose synthase, zinc finger transcription factor, disease resistance response protein and F-box containing domain protein. CONCLUSION: In this survey, we identified stress- and tolerance-associated genes that may be involved in the detoxification of Al and reactive oxygen species. Alternative pathways could help maintain the supply of important metabolites (H2O2, ascorbate, NADH, and phosphate) needed for Al tolerance and root growth. The Al tolerance-associated genes may be key factors that regulate these pathways.
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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".