Thermoinhibition Uncovers a Role for Strigolactones in Arabidopsis Seed Germination
Why this work is in the frame
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Bibliographic record
Abstract
Strigolactones are host factors that stimulate seed germination of parasitic plant species such as Striga and Orobanche. This hormone is also important in shoot branching architecture and photomorphogenic development. Strigolactone biosynthetic and signaling mutants in model systems, unlike parasitic plants, only show seed germination phenotypes under limited growth condition. To understand the roles of strigolactones in seed germination, it is necessary to develop a tractable experimental system using model plants such as Arabidopsis. Here, we report that thermoinhibition, which involves exposing seeds to high temperatures, uncovers a clear role for strigolactones in promoting Arabidopsis seed germination. Both strigolactone biosynthetic and signaling mutants showed increased sensitivity to seed thermoinhibition. The synthetic strigolactone GR24 rescued germination of thermoinbibited biosynthetic mutant seeds but not a signaling mutant. Hormone analysis revealed that strigolactones alleviate thermoinhibition by modulating levels of the two plant hormones, GA and ABA. We also showed that GR24 was able to counteract secondary dormancy in Arabidopsis ecotype Columbia (Col) and Cape Verde island (Cvi). Systematic hormone analysis of germinating Striga helmonthica seeds suggested a common mechanism between the parasitic and non-parasitic seeds with respect to how hormones regulate germination. Thus, our simple assay system using Arabidopsis thermoinhibition allows comparisons to determine similarities and differences between parasitic plants and model experimental systems for the use of strigolactones.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it