Genomic parallelism and lack thereof in contrasting systems of three‐spined sticklebacks
Bibliographic record
Abstract
Parallel evolution and the extent to which it involves gene reuse have attracted much interest. Whereas it has theoretically been predicted under which circumstances gene reuse is expected, empirical studies that directly compare systems showing high and low parallelism are rare. Three-spined stickleback (Gasterosteus aculeatus), where freshwater populations have been independently founded by ancestral marine populations, represent prime examples of phenotypic and genomic parallelism, but cases exist where parallelism is low. Based on RAD (restriction site associated DNA) sequencing, we analysed SNPs and chromosome inversions in populations in Denmark and Greenland showing low and high parallelism, respectively. We identified parallelism across freshwater populations in Greenland at genomic regions previously identified to be associated with marine-freshwater divergence. These same markers also separated Danish marine and freshwater sticklebacks, albeit to a weaker extent. Hence, parallelism was not absent in Denmark but possibly constrained by spatially and temporally varying selection. Divergence time estimates found one Danish freshwater population to be much older than the others. It also deviated strongly with respect to parallelism and may represent earlier postglacial colonization based on a different pool of standing variation and eliciting different adaptive responses to freshwater conditions. These findings provide empirical support to previous suggestions that the time since replicate populations had access to a common pool of standing variation is a major factor determining gene reuse. At last, based on the observed parallelism in the Greenlandic system we discuss the predictability of adaptive responses in newly established populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".