Male-biased transmission of deleterious mutations to the progeny in <i>Arabidopsis</i> <i>thaliana</i>
Bibliographic record
Abstract
The extent and cause of male-biased mutation rates, the higher number of mutations in sperm than in eggs, is currently an active and controversial subject. Recent evidence indicates that this male (sperm) bias not only occurs in animals but also in plants. The higher mutation rate in plant sperm was inferred from rates of evolution of neutral DNA regions, and the results were confined to the mitochondria and chloroplasts of gymnosperms. However, the relative transmission rates of deleterious mutations, which have substantial evolutionary consequences, have rarely been studied. Here, an investigation is described by using the hermaphroditic self-compatible flowering plant Arabidopsis thaliana, in which we artificially increased the rate of mutation in pollen (i.e., sperm donor) and maternal (i.e., egg donor) parents, by using two kinds of UV irradiation in parallel and separate experiments, and assessed the deleterious effects on fitness of the F(2) generation. The results show that more deleterious induced mutations are transmitted to the progeny by a sperm than by an egg. These findings provide the first experimental evidence that more deleterious mutations are inherited from sperm than from an egg in any organism. Possible causes underlying this male bias are discussed.
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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 | 0.000 | 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) | 0.001 | 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".