A personal cost of cheating can stabilize reproductive altruism during the early evolution of clonal multicellularity
Bibliographic record
Abstract
Understanding how cooperation evolved and is maintained remains an important and often controversial topic because cheaters that reap the benefits of cooperation without paying the costs can threaten the evolutionary stability of cooperative traits. Cooperation—and especially reproductive altruism—is particularly relevant to the evolution of multicellularity, as somatic cells give up their reproductive potential in order to contribute to the fitness of the newly emerged multicellular individual. Here, we investigated cheating in a simple multicellular species—the green alga Volvox carteri , in the context of the mechanisms that can stabilize reproductive altruism during the early evolution of clonal multicellularity. We found that the benefits cheater mutants can gain in terms of their own reproduction are pre-empted by a cost in survival due to increased sensitivity to stress. This personal cost of cheating reflects the antagonistic pleiotropic effects that the gene coding for reproductive altruism— regA —has at the cell level. Specifically, the expression of regA in somatic cells results in the suppression of their reproduction potential but also confers them with increased resistance to stress. Since regA evolved from a life-history trade-off gene, we suggest that co-opting trade-off genes into cooperative traits can provide a built-in safety system against cheaters in other clonal multicellular lineages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".