Heat stress response in the closest algal relatives of land plants reveals conserved stress signaling circuits
Bibliographic record
Abstract
All land plants (embryophytes) share a common ancestor that likely evolved from a filamentous freshwater alga. Elucidating the transition from algae to embryophytes - and the eventual conquering of Earth's surface - is one of the most fundamental questions in plant evolutionary biology. Here, we investigated one of the organismal properties that might have enabled this transition: resistance to drastic temperature shifts. We explored the effect of heat stress in Mougeotia and Spirogyra, two representatives of Zygnematophyceae - the closest known algal sister lineage to land plants. Heat stress induced pronounced phenotypic alterations in their plastids, and high-performance liquid chromatography-tandem mass spectroscopy-based profiling of 565 transitions for the analysis of main central metabolites revealed significant shifts in 43 compounds. We also analyzed the global differential gene expression responses triggered by heat, generating 92.8 Gbp of sequence data and assembling a combined set of 8905 well-expressed genes. Each organism had its own distinct gene expression profile; less than one-half of their shared genes showed concordant gene expression trends. We nevertheless detected common signature responses to heat such as elevated transcript levels for molecular chaperones, thylakoid components, and - corroborating our metabolomic data - amino acid metabolism. We also uncovered the heat-stress responsiveness of genes for phosphorelay-based signal transduction that links environmental cues, calcium signatures and plastid biology. Our data allow us to infer the molecular heat stress response that the earliest land plants might have used when facing the rapidly shifting temperature conditions of the terrestrial habitat.
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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 | 0.000 | 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 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".