Comparative genomic analysis identifies an evolutionary shift of vomeronasal receptor gene repertoires in the vertebrate transition from water to land
Bibliographic record
Abstract
Two evolutionarily unrelated superfamilies of G-protein coupled receptors, V1Rs and V2Rs, bind pheromones and "ordinary" odorants to initiate vomeronasal chemical senses in vertebrates, which play important roles in many aspects of an organism's daily life such as mating, territoriality, and foraging. To study the macroevolution of vomeronasal sensitivity, we identified all V1R and V2R genes from the genome sequences of 11 vertebrates. Our analysis suggests the presence of multiple V1R and V2R genes in the common ancestor of teleost fish and tetrapods and reveals an exceptionally large among-species variation in the sizes of these gene repertoires. Interestingly, the ratio of the number of intact V1R genes to that of V2R genes increased by approximately 50-fold as land vertebrates evolved from aquatic vertebrates. A similar increase was found for the ratio of the number of class II odorant receptor (OR) genes to that of class I genes, but not in other vertebrate gene families. Because V1Rs and class II ORs have been suggested to bind to small airborne chemicals, whereas V2Rs and class I ORs recognize water-soluble molecules, these increases reflect a rare case of adaptation to terrestrial life at the gene family level. Several gene families known to function in concert with V2Rs in the mouse are absent outside rodents, indicating rapid changes of interactions between vomeronasal receptors and their molecular partners. Taken together, our results demonstrate the exceptional evolutionary fluidity of vomeronasal receptors, making them excellent targets for studying the molecular basis of physiological and behavioral diversity and adaptation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".