Evolutionary signatures of photoreceptor transmutation in geckos reveal potential adaptation and convergence with snakes
Bibliographic record
Abstract
Most vertebrates use a combination of rod and cone photoreceptors to enable vision in conditions ranging from starlight to direct sunlight. Nocturnal geckos, however, have simplex retinas that contain only rods in terms of morphology and physiology, but these rods are thought to be derived from cones through an evolutionary process known as photoreceptor transmutation. To investigate this, we generated eye transcriptomes and analyzed patterns of phototransduction gene evolution in geckos in comparison to other reptiles. We confirm that geckos have lost several major components of the rod phototransduction pathway, including rod opsin (RH1), which we identified as a pseudogene in multiple genomes. We also identified a partial rod transducin transcript, but found no evidence of the protein in retinal sections. However, we find that geckos express several complete rod phototransduction transcripts in the eye, which may contribute to the rod-like physiology of nocturnal gecko photoreceptors. Finally, we found surprising evidence that even though photoreceptor transmutation evolved independently in geckos and snakes, they have experienced parallel shifts in selective constraint on phototransduction genes. These results implicate adaptive change in the underlying molecular machinery of visual transduction, in addition to the convergent changes in cellular morphology, during photoreceptor transmutation.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".