Complementary genomic and epigenomic adaptation to environmental heterogeneity
Bibliographic record
Abstract
While adaptation is commonly thought to result from selection on DNA sequence-based variation, recent studies have highlighted an analogous epigenetic component as well. However, the extent to which these adaptive mechanisms to adaptation to environmental heterogeneity are redundant or complementary remains unclear. To address the underlying genetic and epigenetic mechanisms and their relationship underlying environmental adaptation, we screened the genomes and epigenomes of nine global populations of a predominately sessile marine invasive tunicate, Botryllus schlosseri. We detected clear population genetic and epigenetic differentiation, which were both significantly influenced by local environments, and the minimum annual sea surface temperature (T_min) was simultaneously identified as the top explanatory variable for both types of variation. However, there remain some degree of difference in population structure patterns between two levels, suggesting a certain level of autonomy in epigenetic variation. From the functional perspective, a set of functional genes and biological pathways were shared between two levels, indicating a conjoint contribution of genetic and epigenetic variation to environmental adaptation. Moreover, we also detected genetic- or epigenetic-specific genes/pathways in relation to a wide variety of core processes potentially underlying adaptation to local environmental factors, suggesting the partly independent relationship between two mechanisms. We infer that complementary genetic and epigenetic routes to adaptation are available in this system. Collectively, these mechanisms may facilitate population persistence under environmental changes and sustain successful invasions in novel but contrasting 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".