Whole-Genome Sequencing of a 900-Year-Old Human Skeleton Supports Two Past Migration Events from the Russian Far East to Northern Japan
Bibliographic record
Abstract
Recent studies on paleogenomics have reported some Paleolithic and Neolithic genomes that have provided new insights into the human population history in East and Northeast Asia. However, there remain some cases where more recent migration events need to be examined to elucidate the detailed formation process of local populations. Although the area around northern Japan is one of the regions archaeologically suggested to have been affected by migration waves after the Neolithic period, the genetic source of these migrations are still unclear. Thus, genomic data from such past migrant populations would be highly informative to clarify the detailed formation process of local populations in this region. Here, we report the genome sequence of a 900-year-old adult female (NAT002) belonging to the prehistoric Okhotsk people, who have been considered to be the past migrants to northern Japan after the Neolithic period. We found a close relationship between NAT002 and modern Lower Amur populations and past admixture events between the Amur, Jomon, and Kamchatka ancestries. The admixture dating suggested migration of Amur-related ancestry at approximately 1,600 BP, which is compatible with the archaeological evidence regarding the settlement of the Okhotsk people. Our results also imply migration of Kamchatka-related ancestry at approximately 2,000 BP. In addition, human leukocyte antigen (HLA) typing detected the HLA-B*40 allele, which is reported to increase the risk of arthritis, suggesting the genetic vulnerability of NAT002 to hyperostosis, which was observed around her chest clavicle.
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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 | 0.000 | 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) | 0.001 | 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".