Balanced polymorphisms in gamete-binding genes are not associated with human infertility
Bibliographic record
Abstract
ABSTRACT Genes expressed in gametes that mediate sperm interaction with the mammalian egg are of considerable interest to evolutionary biologists because the evolution of such genes can account for variation in reproductive compatibility between mates and reproductive isolation between species. The human orthologs of such genes are also potential targets for both contraception and treatment of infertility. One gene system of particular interest is the sperm-binding genes of the inner egg coat or zona pellucida ( Zp2, Zp3 ) and their cognate protein in the mouse sperm acrosome ( Zp3r ). Previous population genetic analyses in humans pointed toward three balanced polymorphisms (one in each gene ZP2, ZP3 , and ZP3R ) as potential targets of some form of balancing selection in the evolution of human fertility. We tested that association using genetic analysis of couples seeking fertility assistance, but we could not reject the null hypothesis of no association between balanced polymorphisms and infertility. Our study was based on a small sample of couples, but the data were sound: the allele frequencies at those three balanced polymorphisms were not different from random expectation in that clinical sample. If an effect of those allele frequencies on infertility exists it is probably small. Our study was based in part on an old error in gene annotation that was only recently discovered (after the start of participant recruitment for this genetic analysis), and this error may account for our results, which argue against a role for balancing selection on those three genes in 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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".