The Transcriptomics of Ecological Convergence between 2 Limnetic Coregonine Fishes (Salmonidae)
Bibliographic record
Abstract
Species living in comparable habitats often display strikingly similar patterns of specialization, suggesting that natural selection can lead to predictable evolutionary changes. Elucidating the genomic basis underlying such adaptive phenotypic changes is a major goal in evolutionary biology. Increasing evidence indicates that natural selection would first modulate gene regulation during the process of population divergence. Previously, we showed that parallel phenotypic adaptations of the dwarf whitefish (Coregonus clupeaformis) ecotype to the limnetic trophic niche involved parallel transcriptional changes at the same genes involved in muscle contraction and energetic metabolism relative to the sympatric normal ecotype. Here, we tested whether the same genes are also implicated in a limnetic specialist species, the cisco (Coregonus artedi), which is the most likely competitor of dwarf whitefish. Significant upregulation was detected in cisco at the same 6 candidate genes functionally involved in modulating swimming activity, namely 5 variants of a major protein of fast muscle and 1 putative catalytic crystallin enzyme. Moreover, 3 of 5 variants and the same putative catalytic crystallin enzyme were upregulated in cisco relative to the dwarf ecotype, indicating a greater physiological potential of the former for exploiting the limnetic trophic niche. This study provides the first empirical evidence that recent, parallel phenotypic evolution toward the use of the same ecological niche occupied by a specialist competitor involved similar adaptive changes in expression at the same genes. As such, this study provides strong support to the general hypothesis that directional selection acting on gene regulation may promote rapid phenotypic divergence and ultimately speciation.
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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 | 0.001 |
| 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".