Genomic signatures of extreme body size divergence in baboons
Bibliographic record
Abstract
Abstract Kinda and gray-footed chacma baboons occupy opposite extremes of the body size distribution in extant baboons (genus Papio ). In order to detect signatures of natural selection in these two species, we genotyped 24,790 genome-wide autosomal SNPs from populations of Zambian baboons using double digest RADseq. We scanned the genome for evidence of selection by identifying regions with extreme differentiation between populations. We find evidence of selection on body size influencing multiple genes in one or both species, including FGF1, ATXN2 , and PRKCE . We also find an enriched signal of selection associated with biological processes involved in multicellular organism growth and development, cell proliferation and cell growth, nutrient metabolism, and chondrocyte differentiation. Finally, we find that selection has impacted components of the CCKR signaling pathway, which regulates food intake and metabolism, and the JAK/STAT signaling pathway, which mediates the effect of cytokine signals on processes including epiphyseal chondrocyte proliferation essential for longitudinal bone growth. Our findings highlight promising avenues for future studies disentangling the genetic architecture of body size in primates including humans.
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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 | 0.000 |
| 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 | 0.000 | 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".