The Driving W Hypothesis as an Explanation for Low Within-Population Mitochondrial DNA Diversity and Between-Population Mitochondrial Transfer
Bibliographic record
Abstract
Abstract The fields of evolutionary biology, molecular ecology, genetics, and taxonomy have been profoundly influenced by studies of variation in mitochondrial DNA (mtDNA), yet there are often surprising differences between mtDNA and nuclear DNA in the within- and between-population relationships that they display. Here I articulate and evaluate a hypothesis that may explain many of the cases in which mtDNA shows little within-population variation and recent movement between populations. Many taxonomic groups (e.g., birds, butterflies and moths; most snakes; some amphibians, fish, and plants) have sex chromosome systems in which females are heterogametic (i.e., ZW females and ZZ males). If a W chromosome undergoes a mutation that gives it a transmission advantage in getting into the one egg produced by female meiosis, it will tend to cause a female-biased sex ratio in the offspring of females that carry that driving W chromosome. This sex ratio bias increases the frequency of the driving W in relation to the non-driving W in the next generation. In the great majority of species in which mitochondria are inherited matrilineally, the spread of the driving W through the population will carry along the particular mitochondrial genome that happens to be associated with the driving W. I summarize evidence in support of the seven components of this W-mtDNA Drive Hypothesis and present simulations and mathematical formulae showing that W drivers spread much more rapidly than equivalent-strength Z or autosomal drivers. Suppressors of W drive spread at a vastly lower rate. I conclude that many cases of low within-population mitochondrial diversity and mitochondrial transfer between species might be explained by the spread of driving W chromosomes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".