Emerging Pleiotropic Mechanisms Underlying Aluminum Resistance and Phosphorus Acquisition on Acidic Soils
Bibliographic record
Abstract
Aluminum (Al) toxicity on acidic soils significantly damages plant roots and inhibits root growth. Hence, crops intoxicated by Al become more sensitive to drought stress and mineral nutrient deficiencies, particularly phosphorus (P) deficiency, which is highly unavailable on tropical soils. Advances in our understanding of the physiological and genetic mechanisms that govern plant Al resistance have led to the identification of Al resistance genes, both in model systems and in crop species. It has long been known that Al resistance has a beneficial effect on crop adaptation to acidic soils. This positive effect happens because the root systems of Al tolerant plants show better development in the presence of soil ionic Al3+ and are, consequently, more efficient in absorbing sub-soil water and mineral nutrients. This effect of Al resistance on crop production, by itself, warrants intensified efforts to develop and implement, on a breeding scale, modern selection strategies to profit from the knowledge of the molecular determinants of plant Al resistance. Recent studies now suggest that Al resistance can exert pleiotropic effects on P acquisition, potentially expanding the role of Al resistance on crop adaptation to acidic soils. This appears to occur via both organic acid- and non-organic acid transporters governing a joint, iron-dependent interplay between Al resistance and enhanced P uptake, via changes in root system architecture. Current research suggests this interplay to be part of a P stress response, suggesting that this mechanism could have evolved in crop species to improve adaptation to acidic soils. Should this pleiotropism prove functional in crop species grown on acidic soils, molecular breeding based on Al resistance genes may have a much broader impact on crop performance than previously anticipated. To explore this possibility, here we review the components of this putative effect of Al resistance genes on P stress responses and P nutrition to provide the foundation necessary to discuss the recent evidence suggesting pleiotropy as a genetic linkage between Al resistance and P efficiency. We conclude by exploring what may be needed to enhance the utilization of Al resistance genes to improve crop production on acidic soils.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".