A vertebrate-wide catalogue of T1R receptors reveals diversity in taste perception
Bibliographic record
Abstract
Taste is a vital chemical sense for feeding behaviour. In mammals, the umami and sweet taste receptors comprise three members of the taste receptor type 1 (T1R/TAS1R) family: T1R1, T1R2 and T1R3. Because their functional homologues exist in teleosts, only three TAS1R genes generated by gene duplication are believed to have been inherited from the common ancestor of bony vertebrates. Here, we report five previously uncharacterized TAS1R members in vertebrates, TAS1R4, TAS1R5, TAS1R6, TAS1R7 and TAS1R8, based on genome-wide survey of diverse taxa. We show that mammalian and teleost fish TAS1R2 and TAS1R3 genes are paralogues. Our phylogenetic analysis suggests that the bony vertebrate ancestor had nine TAS1Rs resulting from multiple gene duplications. Some TAS1Rs were lost independently in descendent lineages resulting in retention of only three TAS1Rs in mammals and teleosts. Combining functional assays and expression analysis of non-teleost fishes we show that the novel T1Rs form heterodimers in taste-receptor cells and recognize a broad range of ligands such as essential amino acids, including branched-chain amino acids, which have not been previously considered as T1R ligands. This study reveals diversity of taste sensations in both modern vertebrates and their ancestors, which might have enabled vertebrates to adapt to diverse habitats on Earth.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.003 | 0.002 |
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".