Whole genome sequences from non-invasively collected caribou faecal samples
Bibliographic record
Abstract
Abstract Conservation genomics is an important tool to manage threatened species under current biodiversity loss. Recent advances in sequencing technology mean that we can now use whole genomes to investigate demographic history, local adaptation, inbreeding, and more in unprecedented detail. However, for many rare and elusive species only non-invasive samples such as faeces can be obtained, making it difficult to take advantage of whole genome data. We present a method to extract DNA from the mucosal layer of faecal samples to re-sequence high coverage whole genomes using standard laboratory techniques. We use wild collected faecal pellets collected from caribou ( Rangifer tarandus ), a species undergoing declines in many parts of its range in Canada and subject to comprehensive conservation and population monitoring measures. We compare four faecal genomes to two tissue genomes sequenced in the same run. Quality metrics were similar between faecal and tissue samples with the main difference being the alignment success of raw reads to the reference genome due to differences in low quality and endogenous DNA content, affecting overall coverage. One of our faecal genomes was only re-sequenced at low coverage (1.6 ×), however the other three obtained between 7 and 15 ×, compared to 19 and 25 × for the tissue samples. We successfully re-sequenced high-quality whole genomes from faecal DNA and are one of the first to obtain genome-wide data from wildlife faecal DNA in a non-primate species. Our work represents an important advancement for non-invasive conservation genomics.
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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 | 0.000 |
| 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".