Resequencing of reindeer genomes provides clues to their docile habits
Bibliographic record
Abstract
Reindeer have long been served as vital subsistence resources for inhabitants of Arctic and subarctic regions owing to their domestication. However, the evolutionary relationships and divergence times among different reindeer populations, genetic traits that distinguish domesticated reindeer, and factors that contribute to their relative docility compared with that of other Cervidae specie, remain unclear. In this study, we sequenced the genomes of 32 individuals from wild and domestic reindeer populations that inhabit Arctic and subarctic regions. We found that reindeer experienced 2 or more independent domestication events characterized by weak artificial selection pressure and limited significant differences in genomic parameters between wild and domestic populations. Alterations in conserved noncoding elements in the reindeer genomes, particularly those associated with nervous system development, may have contributed to their domestication by rendering the nervous system less responsive. Together, our results suggest that inherent species-specific traits, rather than intense artificial selection, may have played a significant role in the relatively docile behavior of reindeer and offer valuable insights into the domestication process of these animals.
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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 | 0.001 |
| 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".