Ancient hybridization patterns between bighorn and thinhorn sheep
Bibliographic record
Abstract
Whole-genome sequencing has advanced the study of species evolution, including the detection of genealogical discordant events such as ancient hybridization and incomplete lineage sorting (ILS). The evolutionary history of bighorn (Ovis canadensis) and thinhorn (Ovis dalli) sheep present an ideal system to investigate evolutionary discordance due to their recent and rapid radiation and putative secondary contact between bighorn and thinhorn sheep subspecies, specifically the dark pelage Stone sheep (O. dalli stonei) and predominately white Dall sheep (O. dalli dalli), during the last ice age. Here, we used multiple genomes of bighorn and thinhorn sheep, together with snow (O. nivicola) and the domestic sheep (O. aries) as outgroups, to assess their phylogenomic history, potential introgression patterns and their adaptive consequences. Among the Pachyceriforms (snow, bighorn and thinhorn sheep) a consistent monophyletic species tree was retrieved; however, many genealogical discordance patterns were observed. Alternative phylogenies frequently placed Stone and bighorn as sister clades. This relationship occurred more often and was less divergent than that between Dall and bighorn. We also observed many blocks containing introgression signal between Stone and bighorn genomes in which coat colour genes were present. Introgression signals observed between Dall and bighorn were more random and less frequent, and therefore probably due to ILS or intermediary secondary contact. These results strongly suggest that Stone sheep originated from a complex series of events, characterized by multiple, ancient periods of secondary contact with bighorn sheep.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".