Examining Sleep Signals at the Cradle of Life: Can phylogenomic analysis of the Last Universal Common Ancestor (LUCA) reveal the fundamental role of sleep?
Bibliographic record
Abstract
Abstract In common with most physiological activities, sleep is a highly evolutionarily conserved function. Nevertheless, the purpose of sleep remains inadequately investigated. One possible cause of this deficiency is the limitations of the traditional methods used for examining sleep. Up to this time, the mainstay tool used to look at the evolutionary basis of sleep has been phylogenetic analysis. This approach has provided many valuable insights into sleep, yet it has left many questions unanswered. The present study uses a relatively new hybrid technique at the interface of phylogenetics and genomics, known as phylogenomic analysis. This study is the first to use phylogenomic analysis to investigate the basis of sleep by evaluating the presence and conservation of sleep-related genes in the reconstructed genome of the Last Universal Common Ancestor (LUCA). Our gene set enrichment analysis of humans and LUCA indicates that the conserved sleep genes are linked to signaling, metabolism, and circadian rhythm pathways, suggesting that these genes possess primordial roles in essential physiological functions. These findings indicate that the component genes carry out essential physiological tasks that were subsequently repurposed to regulate sleep in more advanced organisms throughout evolution. This study lays the foundation for a systematic phylogenomic exploration of sleep-related genes, connecting molecular evolution with sleep science. By tracing the biological history of sleep to its deep evolutionary origins, our research presents novel insights into sleep’s nature, origin, and evolutionary function, paving the way for further interdisciplinary exploration of the biology of sleep. Graphical abstract
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".