Evolution of genes involved in the unusual genitals of the bear macaque, <i>Macaca arctoides</i>
Bibliographic record
Abstract
Abstract Genital divergence is thought to contribute to reproductive barriers by establishing a “lock- and-key” mechanism for reproductive compatibility. One such example, Macaca arctoides , the bear macaque, has compensatory changes in both male and female genital morphology as compared to close relatives. Macaca arctoides also has a complex evolutionary history, having extensive introgression between the fascicularis and sinica macaque species groups. Here, phylogenetic relationships were analyzed via whole genome sequences from five species, including M. arctoides , and two species each from the putative parental species groups. This analysis revealed ∼3x more genomic regions supported placement in the sinica species group as compared to the fascicularis species group. Additionally, introgression analysis of the M. arctoides genome revealed it is a mosaic of recent polymorphisms shared with both species groups. To examine the evolution of their unique genital morphology further, the prevalence of candidate genes involved in genital morphology were compared against genome-wide outliers in various population genetic metrics, while accounting for background variation in recombination rate. This analysis identified 66 outlier genes, including several genes that influence baculum morphology in mice, which were of interest since the bear macaque has the longest primate baculum. The mean of several metrics was statistically different in the candidate genes as compared to the rest of the genome, suggesting that genes involved in genital morphology have increased divergence and decreased diversity beyond expectations. These results highlight how extensive introgression may have contributed to reproductive isolation and shaped the unique genital morphology in the bear macaque.
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 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 | 0.001 | 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".