HTL/KAI2 signalling substitutes for light to control plant germination
Bibliographic record
Abstract
SUMMARY Deciphering signalling pathways is essential to understanding how organisms respond to environmental cues but elucidating how these signalling pathways evolve in new environments is less clear. 1,2 Most plants, for example, monitor multiple environmental cues to optimize the time and place to germinate. Some root parasitic plants, however, germinate in response to small molecules like strigolactones (SLs) emanating from host roots 3,4 whilst a number of ephemeral weeds germinate in response to chemicals called karrikins (KARs) released after a forest fire. 5,6 Although these species represent distinct clades, they use the same HYPOSENSITIVE TO LIGHT/KARRIKIN INSENSITIVE 2 (HTL/KAI2) signalling pathway to perceive strigolactones or karrikins, which suggests convergent evolution. 3,5 Because specialist lifestyles are derived traits, it is not clear if HTL/KAI2 signalling in these species evolved from a specific germination-signalling pathway or whether this pathway had other functions that were co-opted for specialist germination circumstances. Here, we show HTL/KAI2 signalling in Arabidopsis bypasses the light requirement for germination. In part, this is because the HTL/KAI2 downstream component, SMAX1 impinges on PHYTOCHROME INTERACTING FACTOR 1/PHYTOCHROME INTERACTING FACTOR 3-LIKE 5 (PIF1/PIL5)-regulated hormone response pathways conducive to germination. We identified Arabidopsis accessions that can germinate in the dark, which had altered expression of HTL/KAI2 signalling components, suggesting that divergence in this signalling pathway occurs in nature. Moreover, Arabidopsis HTL/KAI2 -regulated gene signatures were observed in germinating Striga seed. The ability of HTL/KAI2 signalling to substitute for light advances an explanation for how some specialist plants evolved their underground germination behaviour in response to specific environments.
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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 | 0.001 | 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".