GENETIC VARIATION IN THE timeless GENE MEDIATES METABOLIC STATES OF Drosophila melanogaster IN RESPONSE TO PHOTOPERIOD
Bibliographic record
Abstract
Genetic variations in the circadian clock may regulate photoperiod-induced anticipatory metabolic adjustments that allow organisms to meet the changes in energetic demands associated with different seasons. Both mammalian and Drosophila studies have shown that perturbed circadian feeding rhythm and aberrant light cycles result in disruptions in fat and glucose metabolism. In this thesis, Drosophila melanogaster was used to investigate the effect of genetic variation in the circadian system on the regulation of feeding and metabolic responses to photoperiod. Here, we analyzed the metabolic responses of two naturally occurring variants of the Drosophila timeless (tim) gene to changes in photoperiod. We found that ls-tim variants, which are known to have attenuated light-sensitivity and are more responsive to diapause, display metabolic traits that are associated with enhanced energy stores and reduced energy expenditure in response to a short-day. Analysis of tim RNA levels in the fat body revealed that it is elevated in ls-tim in response to a short-day suggesting that altered regulation of the clock in the fat body of ls-tim may mediate these enhanced metabolic adjustments to short-day. To examine the role of the foraging gene as a mediator of metabolic outputs regulated by the clock, we analyzed the circadian feeding pattern of foraging variants. Genetic variation in the foraging gene, which encodes cGMP dependent protein kinase (PKG), is known to regulate feeding behavior and energy homeostasis in Drosophila. Our results suggest that foraging regulates the frequency and daily distribution of meals. These findings demonstrate that genetic variations in the circadian system are important in mediating photoperiodic responses to feeding and metabolic state. Characterization of a role of genetic variations in clock genes on the regulation of feeding and metabolism by aberrant light cycles is important in identifying candidate pathways involved in metabolic perturbations associated with shift-work and Seasonal Affective Disorder.
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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 | 0.000 | 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) | 0.001 | 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".