Past Connectivity but Recent Inbreeding in Cross River Gorillas Determined Using Whole Genomes from Single Hairs
Bibliographic record
Abstract
) gorilla. Given the difficulty in sampling wild great ape populations and the small estimated size of the Cross River gorilla population, only one whole genome of a Cross River gorilla has been sequenced to date, hindering the study of this subspecies at the population level. In this study, we expand the number of whole genomes available for wild western gorillas, generating 41 new genomes (25 belonging to Cross River gorillas) using single shed hairs collected from gorilla nests. By combining these genomes with publicly available wild gorilla genomes, we confirm that Cross River gorillas form three population clusters. We also found little variation in genome-wide heterozygosity among them. Our analyses reveal long runs of homozygosity (>10 Mb), indicating recent inbreeding in Cross River gorillas. This is similar to that seen in mountain gorillas but with a much more recent bottleneck. We also detect past gene flow between two Cross River sites, Afi Mountain Wildlife Sanctuary and the Mbe Mountains. Furthermore, we observe past allele sharing between Cross River gorillas and the northern western lowland gorilla sites, as well as with the eastern gorilla species. This is the first study using single shed hairs from a wild species for whole genome sequencing to date. Taken together, our results highlight the importance of implementing conservation measures to increase connectivity among Cross River gorilla sites.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".