Evolutionary Adaptations of TRPA1 Thermosensitivity and Skin Thermoregulation in Vertebrates
Bibliographic record
Abstract
Abstract Altering skin color and reflectance is crucial for temperature regulation in poikilothermic vertebrates, while less so in homeotherms like birds and mammals, which evolved feathers, fur, and other insulation for endothermy. Heat-sensing in vertebrates relies primarily on Transient Receptor Potential (TRP) channels, with certain channels (TRPA1) shifting thermosensitivity over evolution and others retaining heat sensitivity (TRPV1). Exploration of a role for TRP channels in skin physiology has largely focused on human pigmentation and overlooked the evolution of different thermoregulatory structures in the integument of distinct vertebrates. For instance, colour/reflector pigment cells in ectotherms, fur and feathers in endotherms, hairless skin in hominids, and blubber in marine mammals. Therefore, we investigated whether a TRP channel mediates skin darkening induced by heat in the ectotherm Xenopus laevis and then explored the evolution of TRPA1 thermal sensitivity and its link with skin physiology. We find Trpa1 mediates heat-induced melanosome dispersion, darkening skin under warmer conditions. In contrast, TRPA1 is known to mediate cold sensation in rodents and UV-induced tanning in humans, leading us to investigate the co-evolution of TRPA1 and skin thermoregulation. Our findings reveal TRPA1 is a heat sensor in ectotherms with uncovered integuments. In mammals, we suggest TRPA1 was thermally insensitive in Euarchontoglires but became cold-sensitive in several rodent lineages. TRPA1 shows reduced selection pressure for thermosensitivity in aquatic mammals (manatees, whales) that depend on blubber for insulation as compared to their terrestrial relatives. These findings emphasize adaptive evolution of TRPA1 in vertebrates, linking thermal sensitivity to the evolution of skin physiology.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".