Genomic Architecture Underlying the Striking Colour Variation in the Presence of Gene Flow for the Guinan Toad‐Headed Lizard
Bibliographic record
Abstract
How divergence occurs between closely related organisms in the absence of geographic barriers to gene flow stands as one of the long-standing questions in evolutionary biology. Previous studies suggested that the interplay between selection, gene flow and recombination strongly affected the process of divergence with gene flow. However, the extent to which these forces interact to drive divergence remains largely ambiguous. Guinan toad-headed lizards (Phrynocephalus guinanensis) in the Mugetan Desert exhibit striking colour differences from lizards outside the desert and provide an excellent model to address this question. Through extensive sampling and whole genome sequencing, we obtained genotypes for 191 samples from 14 populations inside and outside the desert. Despite the colour differences, continuous and asymmetric gene flow was detected across the desert border. More importantly, 273 highly diverged regions (HDRs) were identified between them, accounting only for 0.47% of the genome but widely distributed across 20 (out of the total 24) chromosomes. Strong signatures of selection were identified in HDRs, and local recombination rates were repressed. Furthermore, five HDRs exhibited significantly higher divergence, which contained key genes associated with crucial functions in animal coloration, including pteridine and melanocyte pigmentation. Genes related to retinal cells and steroid hormones were identified in other HDRs, which might have also contributed to the formation of colour variation in the presence of gene flow. This study provided novel insights into the understanding of the evolutionary mechanisms of genetic divergence in the presence of gene flow.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".