The Evolutionary History of Iconic North American Wild Sheep (Ovis spp.)
Bibliographic record
Abstract
The increased accessibility of complete DNA sequences from individual organisms, i.e., nuclear whole-genome sequences (WGS), allows us to explore evolutionary processes, including hybridization events. The North American wild thinhorn (Ovis dalli) and bighorn (Ovis canadensis) sheep are interesting systems for studying such patterns. The former comprises the dark pelage Stone (O. d. stonei) and the pure white Dall (O. d. dalli) subspecies. These species diverged due to geographical separation and isolation, with potential hybridization leading to adaptive features. No recent hybridization is expected, given their non-overlapping distributions. Here, I aimed to study the WGS of fossil and modern sheep to shed new light on their mosaic genomic patterns shaped by various evolutionary processes. The dataset consisted of WGS of fossils from the Yukon (Canada) and Wyoming (USA), and WGS and mitogenomes of modern thinhorn and bighorn sheep. I explored their evolution in the following data chapters: (2) fossils versus modern species using nuclear WGS data, and contemporary thinhorn and bighorn with (3) mitogenomes, (4) low-quality nuclear and (5) high-quality nuclear WGS data. Concerning the first comparison (2), I identified hybridization signals between missing lineages and the Yukon and Wyoming fossils and found evidence that might support the Wyoming sample as a hybrid lineage between the ancestors of thinhorn and bighorn sheep. In chapters 3 and 4, I observed potential ancient hybridization signals between Stone and bighorn sheep. Nuclear genomic fragments showing hybridization had coat-colour genes often present, suggesting that hybridization somehow contributed to Stone’s darker pelage. Finally, I used high-quality genomes (5) to investigate evolutionary processes and WGS reference choice, confirming previous results and providing new insights into their evolution. Dall and Stone sheep presented similar effective population size fluctuations over time. I also observed that Stone had, on average, higher cumulative length and count for runs of homozygosity (ROH) than Dall and bighorn sheep, likely due to their restricted geographic distribution. The WGS reference used impacted ROH, demonstrating the need to reassess which references should be used. By using WGS of ancient and modern species, this project more fully illuminated the ancient hybridization signals between these North American species.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".