Mutation rate estimate and population genomic analysis reveals decline of koalas prior to human arrival
Bibliographic record
Abstract
The koala (Phascolarctos cinereus), an iconic Australian marsupial, has experienced substantial historical and contemporary population declines. Identifying the drivers of these declines has been hindered by limited genomic data and uncertainty regarding the koala mutation rate. Here, we report a direct estimate of the koala mutation rate, based on genome sequences of four parent-offspring trios, yielding a mean of 6.12 × 10-9 mutations per base pair per generation (95% confidence interval: 5.03 to 7.45 × 10-9). Using this estimate of the mutation rate, we reconstructed the demographic history of koalas using 457 whole-genome sequences sampled across their entire range. Our results refine the estimated timing of past changes in population size, suggesting a large decline beginning ∼100 kya, before the arrival of humans in Australia. The koala population then split into five genetic populations 6 to 30 kya, which are now distributed along the east coast of Australia. We also use our estimate of the mutation rate to infer recombination maps for each koala population, confirming lower recombination rates in marsupials than in eutherian mammals. Using these estimates of population-specific recombination rates, we inferred the timing of recent population declines for koalas across all eastern states. These findings provide critical insights into the evolutionary history of koalas, while highlighting the impacts of using species-specific estimates of evolutionary rates on the inference of demographic histories. Our estimates of the genome-wide mutation rate and population-specific recombination maps for koalas provide valuable resources for future evolutionary and conservation analyses of marsupials.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".