Genetic Diversity, Inbreeding Level, and Genetic Load in Endangered Snub-Nosed Monkeys (Rhinopithecus)
Bibliographic record
Abstract
The snub-nosed monkey genus ( Rhinopithecus ) comprises five closely related species ( R. avunculus, R. bieti, R. brelichi, R. roxellana , and R. strykeri ). All are among the world's rarest and most endangered primates. However, the genomic impact associated with their population decline remains unknown. We analyzed population genomic data of all five snub-nosed monkey species to assess their genetic diversity, inbreeding level, and genetic load. For R. roxellana, R. bieti , and R. strykeri , population size is positively correlated with genetic diversity and negatively correlated with levels of inbreeding. Other species, however, which possess small population sizes, such as R. brelichi and R. avunculus , show high levels of genetic diversity and low levels of genomic inbreeding. Similarly, in the three populations of R. roxellana , the Shennongjia population, which possesses the lowest population size, displays a higher level of genetic diversity and lower level of genomic inbreeding. These findings suggest that although R. brelichi and R. avunculus and the Shennongjia population might be at risk, it possess significant genetic diversity and could thus help strengthen their long-term survival potential. Intriguingly, R. roxellana with large population size possess high genetic diversity and low level of genetic load, but they show the highest recent inbreeding level compared with the other snub-nosed monkeys. This suggests that, despite its large population size, R. roxellana has likely been experiencing recent inbreeding, which has not yet affected its mutational load and fitness. Analyses of homozygous-derived deleterious mutations identified in all snub-nosed monkey species indicate that these mutations are affecting immune, especially in smaller population sizes, indicating that the long-term consequences of inbreeding may be resulting in an overall reduction of immune capability in the snub-nosed monkeys, which could provide a dramatic effect on their long-term survival prospects. Altogether, our study provides valuable information concerning the genomic impact of population decline of the snub-nosed monkeys. We revealed multiple counterintuitive and unexpected patterns of genetic diversity in small and large population, which will be essential for conservation management of these endangered species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".