Mitonuclear Interactions and the Origin of Macaque Societies
Bibliographic record
Abstract
In most eukaryotes, aerobic respiration requires interactions between autosomally encoded genes (Ninteract genes) and mitochondrial DNA, RNA, and protein. In species where females are philopatric, contrasting distributions of genetic variation in mitochondrial and nuclear genomes create variation in mitonuclear interactions that may be subject to natural selection. To test this expectation, we turned to a group with extreme female philopatry: the macaque monkeys. We examined four genomic data sets from (1) wild caught and (2) captive populations of rhesus macaque, which is the most widely distributed nonhuman primate, and (3) the stump-tailed macaque and (4) a subspecies of longtail macaque, both of whose mitochondrial DNA is introgressed from a highly diverged ancestor. We identified atypically long runs of homozygosity, low polymorphism, high differentiation, and/or rapid protein evolution associated with Ninteract genes compared with non-Ninteract genes. These metrics suggest a subset of Ninteract genes were independently subject to atypically pervasive natural selection in multiple species. These findings suggest that natural selection on mitonuclear interactions could have influenced several aspects of macaque societies including species diversity, ecological breadth, female-biased adult sex ratio and demography, sexual dimorphism, and mitonuclear phylogenomics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".