Diet and the evolution of <i>ADH7</i> across seven orders of mammals
Bibliographic record
Abstract
Dietary variation within and across species drives the eco-evolutionary responsiveness of genes necessary to metabolize nutrients and other components. Recent evidence from humans and other mammals suggests that sugar-rich diets of floral nectar and ripe fruit have favoured mutations in, and functional preservation of, the ADH7 gene, which encodes the ADH class 4 enzyme responsible for metabolizing ethanol. Here we interrogate a large, comparative dataset of ADH7 gene sequence variation, including that underlying the amino acid residue located at the key site (294) that regulates the affinity of ADH7 for ethanol. Our analyses span 171 mammal species, including 59 newly sequenced. We report extensive variation, especially among frugivorous and nectarivorous bats, with potential for functional impact. We also report widespread variation in the retention and probable pseudogenization of ADH7 . However, we find little statistical evidence of an overarching impact of dietary behaviour on putative ADH7 function or presence of derived alleles at site 294 across mammals, which suggests that the evolution of ADH7 is shaped by complex factors. Our study reports extensive new diversity in a gene of longstanding ecological interest, offers new sources of variation to be explored in functional assays in future study, and advances our understanding of the processes of molecular evolution.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".