Phylogeography and adaptation genetics of stickleback from the<scp>H</scp>aida<scp>G</scp>waii archipelago revealed using genome‐wide single nucleotide polymorphism genotyping
Bibliographic record
Abstract
Threespine stickleback populations are model systems for studying adaptive evolution and the underlying genetics. In lakes on the Haida Gwaii archipelago (off western Canada), stickleback have undergone a remarkable local radiation and show phenotypic diversity matching that seen throughout the species distribution. To provide a historical context for this radiation, we surveyed genetic variation at >1000 single nucleotide polymorphism (SNP) loci in stickleback from over 100 populations. SNPs included markers evenly distributed throughout genome and candidate SNPs tagging adaptive genomic regions. Based on evenly distributed SNPs, the phylogeographic pattern differs substantially from the disjunct pattern previously observed between two highly divergent mtDNA lineages. The SNP tree instead shows extensive within watershed population clustering and different watersheds separated by short branches deep in the tree. These data are consistent with separate colonizations of most watersheds, despite underlying genetic connections between some independent drainages. This supports previous suppositions that morphological diversity observed between watersheds has been shaped independently, with populations exhibiting complete loss of lateral plates and giant size each occurring in several distinct clades. Throughout the archipelago, we see repeated selection of SNPs tagging candidate freshwater adaptive variants at several genomic regions differentiated between marine-freshwater populations on a global scale (e.g. EDA, Na/K ATPase). In estuarine sites, both marine and freshwater allelic variants were commonly detected. We also found typically marine alleles present in a few freshwater lakes, especially those with completely plated morphology. These results provide a general model for postglacial colonization of freshwater habitat by sticklebacks and illustrate the tremendous potential of genome-wide SNP data sets hold for resolving patterns and processes underlying recent adaptive divergences.
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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".