Phenotypic plasticity evolves at multiple biological levels in response to environmental predictability in a long-term experiment with a halotolerant microalga
Bibliographic record
Abstract
Phenotypic plasticity, the change in the phenotype of a given genotype in response to its environment of development, is a ubiquitous feature of life, enabling organisms to cope with variation in their environment. Theoretical studies predict that, under stationary environmental variation, the level of plasticity should evolve to match the predictability of selection at the timing of development. However, the extent to which patterns of evolution of plasticity for more integrated traits are mirrored by their underlying molecular mechanisms remains unclear, especially in response to well-characterized selective pressures exerted by environmental predictability. Here, we used experimental evolution with the microalgae Dunaliella salina under controlled environmental fluctuations, to test whether the evolution of phenotypic plasticity in responses to environmental predictability (as measured by the squared autocorrelation ρ2) occurred across biological levels, going from DNA methylation to gene expression to cell morphology. Transcriptomic analysis indicates clear effects of salinity and ρ2 × salinity interaction on gene expression, thus identifying sets of genes involved in plasticity and its evolution. These transcriptomic effects were independent of DNA methylation changes in cis. However, we did find ρ2-specific responses of DNA methylation to salinity change, albeit weaker than for gene expression. Overall, we found consistent evolution of reduced plasticity in less predictable environments for DNA methylation, gene expression, and cell morphology. Our results provide the first clear empirical signature of plasticity evolution at multiple levels in response to environmental predictability, and highlight the importance of experimental evolution to address predictions from evolutionary theory, as well as investigate the molecular basis of plasticity evolution.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".