The Genetic Architecture of Ecological Speciation and the Association with Signatures of Selection in Natural Lake Whitefish (Coregonus sp. Salmonidae) Species Pairs
Bibliographic record
Abstract
Adaptive evolutionary change is contingent on variation and selection; thus, understanding adaptive divergence and ultimately speciation requires information on both the genetic basis of adaptive traits as well as an understanding of the role of divergent natural selection on those traits. The lake whitefish (Coregonus clupeaformis) consists of several sympatric "dwarf" (limnetic) and normal (benthic) species pairs that co-inhabit northern postglacial lakes. These young species pairs have evolved independently and display parallelism in life history, behavioral, and morphological divergence associated with the use of distinct trophic resources. We identified phenotype-environment associations and determined the genetic architecture and the role of selection modulating population genetic divergence in sympatric dwarf and normal lake whitefish. The genetic architecture of 9 adaptive traits was analyzed in 2 hybrid backcrosses individually phenotyped throughout their life history. Significant quantitative trait loci (QTL) were associated with swimming behavior (habitat selection and predator avoidance), growth rate, morphology (condition factor and gill rakers), and life history (onset of maturity and fecundity). Genome scans among 4 natural sympatric pairs, using loci segregating in the map, revealed a signature of selection for 24 loci. Loci exhibiting a signature of selection were associated with QTL relative to other regions of the genome more often than expected by chance alone. Two parallel QTL outliers for growth and condition factor exhibited segregation distortion in both mapping families, supporting the hypothesis that adaptive divergence contributing to parallel reductions of gene flow among natural populations may cause genetic incompatibilities. Overall, these findings offer evidence that the genetic architecture of ecological speciation is associated with signatures of selection in nature, providing strong support for the hypothesis that divergent natural selection is currently maintaining adaptive differentiation and promoting ecological speciation in lake whitefish species pairs.
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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 | 0.001 |
| 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".