The Dynamics, Causes, and Impacts of Mammalian Evolutionary Rates Revealed by the Analyses of Capybara Draft Genome Sequences
Bibliographic record
Abstract
Capybara (Hydrochoerus hydrochaeri) is the largest species among the extant rodents. The draft genome of capybara was sequenced with the estimated genome size of 2.6 Gb. Although capybara is about 60 times larger than guinea pig, comparative analyses revealed that the neutral evolutionary rates of the two species were not substantially different. However, analyses of 39 mammalian genomes revealed very heterogeneous evolutionary rates. The highest evolutionary rate, 8.5 times higher than the human rate, was found in the Cricetidae-Muridae common ancestor after the divergence of Spalacidae. Muridae, the family with the highest number of species among mammals, emerged after the rate acceleration. Factors responsible for the evolutionary rate heterogeneity were investigated through correlations between the evolutionary rate and longevity, gestation length, litter frequency, litter size, body weight, generation interval, age at maturity, and taxonomic order. The regression analysis of these factors showed that the model with three factors (taxonomic order, generation interval, and litter size) had the highest predictive power (R2 = 0.74). These three factors determine the number of meiosis per unit time. We also conducted transcriptome analysis and found that the evolutionary rate dynamics affects the evolution of gene expression patterns.
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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 | 0.000 | 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 | 0.001 |
| 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".