The cost of survival: mutation in a barley Strigolactone repressor <i>HvD53A</i> impairs photosynthesis but increases drought tolerance
Bibliographic record
Abstract
Strigolactones (SLs) are a class of plant hormones that play a crucial role in shaping plant architecture, significantly influencing plant adaptation to harsh environmental conditions. In this study, we examined the effects of a mutation in a component of the barley SL signalling pathway, the SL repressor HvDWARF53A, on plant growth and drought tolerance. We compared the results with those of a previously described barley mutant, which is highly tillered and drought-sensitive, carrying a mutation in the SL receptor gene HvDWARF14. The two mutants, hvd14.d and hvd53a.f, displayed contrasting phenotypes, including differences in plant height, tillering, and drought sensitivity. Under control conditions, ultrastructural analysis of hvd53a.f revealed smaller chloroplasts and fewer grana stacks, which may account for its reduced photosynthetic efficiency. Conversely, transcriptomic analysis linked the differentially expressed genes in hvd53a.f to antioxidation and stress responses, suggesting a potentially enhanced capacity to cope with drought. Further analysis revealed a strong connection between the SL signalling pathway and circadian clock components. Among these, CIRCADIAN CLOCK ASSOCIATED 1 emerged as a potential SL-responsive transcription factor (TF), possibly playing a key role in regulating tillering. Under drought conditions, hvd53a.f exhibited enhanced tolerance, as evidenced by higher relative water content, reduced chlorophyll degradation, and stable, albeit reduced, photosynthetic performance. Here, we identified the SL-related TF JUNGBRUNNEN 1 as a potential regulator of genes involved in water deficit response and antioxidation processes. Overall, the hvd53a.f mutation enhances drought tolerance while maintaining low, stable photosynthesis, highlighting HvD53A as a central node connecting SL signalling to stress resilience.
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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 | 0.000 | 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) | 0.003 | 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".