Genomic Analyses of Pre-European Conquest Human Remains from the Canary Islands Reveal Close Affinity to Modern North Africans
Bibliographic record
Abstract
The origins and genetic affinity of the aboriginal inhabitants of the Canary Islands, commonly known as Guanches, are poorly understood. Though radiocarbon dates on archaeological remains such as charcoal, seeds, and domestic animal bones suggest that people have inhabited the islands since the 5 th century BCE [1–3], it remains unclear how many times, and by whom, the islands were first settled [4, 5]. Previously published ancient DNA analyses of uniparental genetic markers have shown that the Guanches carried common North African Y chromosome markers (E-M81, E-M78, and J-M267) and mitochondrial lineages such as U6b, in addition to common Eurasian haplogroups [6–8]. These results are in agreement with some linguistic, archaeological, and anthropological data indicating an origin from a North African Berber-like population [1, 4, 9]. However, to date there are no published Guanche autosomal genomes to help elucidate and directly test this hypothesis. To resolve this, we generated the first genome-wide sequence data and mitochondrial genomes from eleven archaeological Guanche individuals originating from Gran Canaria and Tenerife. Five of the individuals (directly radiocarbon dated to a time transect spanning the 7 th –11 th centuries CE) yielded sufficient autosomal genome coverage (0.21× to 3.93×) for population genomic analysis. Our results show that the Guanches were genetically similar over time and that they display the greatest genetic affinity to extant Northwest Africans, strongly supporting the hypothesis of a Berber-like origin. We also estimate that the Guanches have contributed 16%–31% autosomal ancestry to modern Canary Islanders, here represented by two individuals from Gran Canaria.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".