Eusociality in snapping shrimps is associated with larger genomes and an accumulation of transposable elements
Bibliographic record
Abstract
snapping shrimps that exhibit multiple origins of eusociality and extreme interspecific variation in genome size. Our goal is to determine whether eusociality leads to an accumulation of repetitive elements and an increase in genome size, presumably due to reduced effective population sizes resulting from a reproductive division of labor, or whether an initial accumulation of repetitive elements leads to larger genomes and independently promotes the evolution of eusociality through adaptive evolution. Using phylogenetically informed analyses, we find that eusocial species have larger genomes with more transposable elements (TEs) and microsatellite repeats than noneusocial species. Interestingly, different TE subclasses contribute to the accumulation in different species. Phylogenetic path analysis testing alternative causal relationships between sociality and genome architecture is most consistent with the hypothesis that TEs modulate the relationship between sociality and genome architecture. Although eusociality appears to influence TE accumulation, ancestral state reconstruction suggests moderate TE abundances in ancestral species could have fueled the initial transitions to eusociality. Ultimately, we highlight a complex and dynamic relationship between genome and social evolution, demonstrating that sociality can influence the evolution of the genome, likely through changes in demography related to patterns of reproductive skew.
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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".