In Search of Food: Exploring the Evolutionary Link Between cGMP-Dependent Protein Kinase (PKG) and Behaviour
Bibliographic record
Abstract
Despite an immense amount of variation in organisms throughout the animal kingdom many of their genes show substantial conservation in DNA sequence and protein function. Here we explore the potential for a conserved evolutionary relationship between genes and their behavioural phenotypes. We investigate the evolutionary history of cGMP-dependent protein kinase (PKG) and its possible conserved function in food-related behaviours. First identified for its role in the foraging behaviour of fruit flies, the PKG encoded by the foraging gene has since been associated with the maturation of behaviour (from nurse to forager) in honey bees and the roaming and dwelling food-related locomotion in nematodes. These parallels encouraged us to construct protein phylogenies using 32 PKG sequences that include 19 species. Our analyses suggest five possible evolutionary histories that can explain the apparent conserved link between PKG and behaviour in fruit flies, honey bees and nematodes. Three of these raise the hypothesis that PKG influences the food-related behaviours of a wide variety of animals including vertebrates. Moreover, it appears that the PKG gene was duplicated some time between the evolution of nematodes and a common ancestor of vertebrates and insects whereby current evidence suggests only the for-like PKG might be associated with food-related behaviour.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".