Interrogating 11 Fast-Evolving Genes for Signatures of Recent Positive Selection in Worldwide Human Populations
Bibliographic record
Abstract
Different signatures of natural selection persist over varying time scales in our genome, revealing possible episodes of adaptative evolution during human history. Here, we identify genes showing signatures of ancestral positive selection in the human lineage and investigate whether some of those genes have been evolving adaptatively in extant human populations. Specifically, we compared more than 11,000 human genes with their orthologs in chimpanzee, mouse, rat, and dog and applied a branch-site likelihood method to test for positive selection on the human lineage. Among the significant cases, a robust set of 11 genes was then further explored for signatures of recent positive selection using single nucleotide polymorphism (SNP) data. We genotyped 223 SNPs in 39 worldwide populations from the HGDP-CEPH diversity panel and supplemented this information with available genotypes for up to 4,814 SNPs distributed along 2 Mb centered on each gene. After exploring the allele frequency spectrum, population differentiation and the maintenance of long unbroken haplotypes, we found signals of recent adaptative phenomena in only one of the 11 candidate gene regions. However, the signal of recent selection in this region may come from a different, neighboring gene (CD5) rather than from the candidate gene itself (VPS37C). For this set of positively selected genes in the human lineage, we find no indication that these genes maintained their rapid evolutionary pace among human populations. Based on these data, it therefore appears that adaptation for human-specific and for population-specific traits may have involved different genes.
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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 | 0.000 |
| 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 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".