Mammalian Sperm Proteins Are Rapidly Evolving: Evidence of Positive Selection in Functionally Diverse Genes
Bibliographic record
Abstract
A growing number of genes involved in sex and reproduction have been demonstrated to be rapidly evolving. Here, we show that genes expressed solely in spermatozoa represent a highly diverged subset among mouse and human tissue-specific orthologs. The average rate of nonsynonymous substitutions per site (K(a)) is significantly higher in sperm proteins (mean K(a) = 0.18; N = 35) than in proteins expressed specifically in all other tissues (mean K(a) = 0.074; N = 473). No differences, however, are found in the synonymous substitution rate (K(s)) between tissues, suggesting that selective forces, and not mutation rate, explain the high rate of replacement substitutions in sperm proteins. Four out of 19 sperm-specific genes with characterized function demonstrated evidence of strong positive Darwinian selection, including a protein involved in gene regulation, Protamine-1 (PRM1), a protein involved in glycolysis, GAPDS, and two egg-binding proteins, Adam-2 precursor (ADAM2) and sperm-adhesion molecule-1 (SAM1). These results demonstrate the rapid evolution of sperm-specific genes and highlight the molecular action of sexual selection on a variety of characters involved in mammalian sperm function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".