Identifying positive selection candidate loci for high-altitude adaptation in Andean populations
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Bibliographic record
Abstract
High-altitude environments (>2,500 m) provide scientists with a natural laboratory to study the physiological and genetic effects of low ambient oxygen tension on human populations. One approach to understanding how life at high altitude has affected human metabolism is to survey genome-wide datasets for signatures of natural selection. In this work, we report on a study to identify selection-nominated candidate genes involved in adaptation to hypoxia in one highland group, Andeans from the South American Altiplano. We analysed dense microarray genotype data using four test statistics that detect departures from neutrality. Using a candidate gene, single nucleotide polymorphism-based approach, we identified genes exhibiting preliminary evidence of recent genetic adaptation in this population. These included genes that are part of the hypoxia-inducible transcription factor ( HIF ) pathway, a biochemical pathway involved in oxygen homeostasis, as well as three other genomic regions previously not known to be associated with high-altitude phenotypes. In addition to identifying selection-nominated candidate genes, we also tested whether the HIF pathway shows evidence of natural selection. Our results indicate that the genes of this biochemical pathway as a group show no evidence of having evolved in response to hypoxia in Andeans. Results from particular HIF -targeted genes, however, suggest that genes in this pathway could play a role in Andean adaptation to high altitude, even if the pathway as a whole does not show higher relative rates of evolution. These data suggest a genetic role in high-altitude adaptation and provide a basis for genotype/phenotype association studies that are necessary to confirm the role of putative natural selection candidate genes and gene regions in adaptation to altitude.
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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 | 0.000 |
| 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 it