Genome sequence and comparative analysis of reindeer ( <i>Rangifer tarandus</i> ) in northern Eurasia
Bibliographic record
Abstract
Abstract Reindeer are semi-domesticated ruminants that have adapted to the challenging northern Eurasian environment characterized by long winters and marked annual fluctuations in daylight. We explored the genetic makeup behind their unique characteristics by de novo sequencing the genome of a male reindeer and conducted gene family analyses with nine other mammalian species. We performed a population genomics study of 23 additional reindeer representing both domestic and wild populations and several ecotypes from various geographic locations. We assembled 2.66 Gb (N50 scaffold of 5 Mb) of the estimated 2.92 Gb reindeer genome, comprising 27,332 genes. The results from the demographic history analysis suggested marked changes in the effective population size of reindeer during the Pleistocene period. We detected 160 reindeer-specific and expanded genes, of which zinc finger proteins (n=42) and olfactory receptors (n=13) were the most abundant. Comparative genome analyses revealed several genes that may have promoted the adaptation of reindeer, such as those involved in recombination and speciation ( PRDM9 ), vitamin D metabolism ( TRPV5, TRPV6 ), retinal development ( PRDM1, OPN4B ), circadian rhythm ( GRIA1 ), immunity ( CXCR1, CXCR2, CXCR4, IFNW1 ), tolerance to cold-triggered pain ( SCN11A ) and antler development ( SILT2 ). The majority of these characteristic reindeer genes have been reported for the first time here. Moreover, our population genomics analysis suggested at least two independent reindeer domestication events with genetic lineages originating from different refugial regions after the Last Glacial Maximum. Taken together, our study has provided new insights into the domestication, evolution and adaptation of reindeer and has promoted novel genomic research of reindeer.
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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 | 0.001 |
| 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".