Comprehensive study of mtDNA among Southwest Asian dogs contradicts independent domestication of wolf, but implies dog–wolf hybridization
Bibliographic record
Abstract
Studies of mitochondrial DNA (mtDNA) diversity indicate explicitly that dogs were domesticated, probably exclusively, in southern East Asia. However, Southwest Asia (SwAsia) has had poor representation and geographical coverage in these studies. Other studies based on archaeological and genome-wide SNP data have suggested an origin of dogs in SwAsia. Hence, it has been suspected that mtDNA evidence for this scenario may have remained undetected. In the first comprehensive investigation of genetic diversity among SwAsian dogs, we analyzed 582 bp of mtDNA for 345 indigenous dogs from across SwAsia, and compared with 1556 dogs across the Old World. We show that 97.4% of SwAsian dogs carry haplotypes belonging to a universal mtDNA gene pool, but that only a subset of this pool, five of the 10 principal haplogroups, is represented in SwAsia. A high frequency of haplogroup B, potentially signifying a local origin, was not paralleled with the high genetic diversity expected for a center of origin. Meanwhile, 2.6% of the SwAsian dogs carried the rare non-universal haplogroup d2. Thus, mtDNA data give no indication that dogs originated in SwAsia through independent domestication of wolf, but dog-wolf hybridization may have formed the local haplogroup d2 within this region. Southern East Asia remains the only region with virtually full extent of genetic variation, strongly indicating it to be the primary and probably sole center of wolf domestication. An origin of dogs in southern East Asia may have been overlooked by other studies due to a substantial lack of samples from this region.
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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 | 0.001 | 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 | 0.001 |
| 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".