Divergent Selection in Low Recombination Regions Shapes the Genomic Islands in Two Incipient Shorebird Species
Bibliographic record
Abstract
Speciation in the face of gene flow is usually associated with a heterogeneous genomic landscape of divergence in nascent species pairs. However, multiple factors, such as divergent selection and local recombination rate variation, can influence the formation of these genomic islands. Examination of the genomic landscapes of species pairs that are still in the early stages of speciation provides an insight into this conundrum. In this study, population genomic analyses were undertaken using a wide range of sampling and whole-genome resequencing data from 96 unrelated individuals of Kentish plover (Charadrius alexandrinus) and white-faced plover (Charadrius dealbatus). We suggest that the two species exhibit varying levels of population admixture along the Chinese coast and on the Taiwan Island. Genome-wide analyses for introgression indicate that ancient introgression had occurred in Taiwan population, and gene flow is still ongoing in mainland coastal populations. Furthermore, we identified a few genomic regions with significant levels of interspecific differentiation and local recombination suppression, which contain several genes potentially associated with disease resistance, coloration, and regulation of plumage molting and thus may be relevant to the phenotypic and ecological divergence of the two nascent species. Overall, our findings suggest that divergent selection in low recombination regions may be a main force in shaping the genomic islands in two incipient shorebird species.
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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".