Identification and characterization of suppressor mutants of stop1
Bibliographic record
Abstract
BACKGROUND: Proton stress and aluminum (Al) toxicity are major constraints limiting crop growth and yields on acid soils (pH < 5). In Arabidopsis, STOP1 is a master transcription factor that controls the expression of a set of well-characterized Al tolerance genes and unknown processes involved in low pH resistance. As a result, loss-of-function stop1 mutants are extremely sensitive to low pH and Al stresses. RESULTS: Here, we report on screens of an ethyl-methane sulphonate (EMS)-mutagenized stop1 population and isolation of nine strong stop1 suppressor mutants, i.e., the tolerant to proton stress (tps) mutants, with significantly enhanced root growth at low pH (4.3). Genetic analyses indicated these dominant and partial gain-of-function mutants are caused by mutations in single nuclear genes outside the STOP1 locus. Physiological characterization of the responses of these tps mutants to excess levels of Al and other metal ions further classified them into five groups. Three tps mutants also displayed enhanced resistance to Al stress, indicating that these tps mutations partially rescue the hypersensitive phenotypes of stop1 to both low pH stress and Al stress. The other six tps mutants showed enhanced resistance only to low pH stress but not to Al stress. We carried out further physiologic and mapping-by-sequencing analyses for two tps mutants with enhanced resistance to both low pH and Al stresses and identified the genomic regions and candidate loci in chromosomes 1 and 2 that harbor these two TPS genes. CONCLUSION: We have identified and characterized nine strong stop1 suppressor mutants. Candidate loci for two tps mutations that partially rescue the hypersensitive phenotypes of stop1 to low pH and Al stresses were identified by mapping-by-sequencing approaches. Further studies could provide insights into the structure and function of TPSs and the regulatory networks underlying the STOP1-mediated processes that lead to resistance to low pH and Al stresses in Arabidopsis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".