Shifts in Selective Pressures on Snake Phototransduction Genes Associated with Photoreceptor Transmutation and Dim-Light Ancestry
Bibliographic record
Abstract
The visual systems of snakes are heavily modified relative to other squamates, a condition often thought to reflect their fossorial origins. Further modifications are seen in caenophidian snakes, where evolutionary transitions between rod and cone photoreceptors, termed photoreceptor transmutations, have occurred in many lineages. Little previous work, however, has focused on the molecular evolutionary underpinnings of these morphological changes. To address this, we sequenced seven snake eye transcriptomes and utilized new whole-genome and targeted capture sequencing data. We used these data to analyze gene loss and shifts in selection pressures in phototransduction genes that may be associated with snake evolutionary origins and photoreceptor transmutation. We identified the surprising loss of rhodopsin kinase (GRK1), despite a low degree of gene loss overall and a lack of relaxed selection early during snake evolution. These results provide some of the first evolutionary genomic corroboration for a dim-light ancestor that lacks strong fossorial adaptations. Our results also indicate that snakes with photoreceptor transmutation experienced significantly different selection pressures from other reptiles. Significant positive selection was found primarily in cone-specific genes, but not rod-specific genes, contrary to our expectations. These results reveal potential molecular adaptations associated with photoreceptor transmutation and also highlight unappreciated functional differences between rod- and cone-specific phototransduction proteins. This intriguing example of snake visual system evolution illustrates how the underlying molecular components of a complex system can be reshaped in response to changing selection pressures.
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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 | 0.000 | 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".