Polyploidy Is Genetic Hence May Cause Non‐Adaptive Radiations, Whereas Pseudopolyploidy Is Genomic Hence May Cause Adaptive Non‐Radiations
Bibliographic record
Abstract
There are two ways eukaryotes double number of chromosomes: (1) whole genome duplication (polyploidy), in which all nuclear DNA is replicated, and (2) karyotypic fission (pseudopolyploidy), in which all chromosomes are physically bifurcated. We contrast polyploidy with pseudopolyploidy, highlighting when it is crucial to look at genetic vs. genomic levels. We review history of pseudopolyploidy, including recent mechanisms by which chromosomal bifurcation may occur and outline methods for detecting such genomic changes. We then delve into the evolutionary implications, with particular focus on adaptive potential, of these two forms of doubling chromosome numbers. We address the common assertion that polyploidy induces adaptive radiations, which contains three fallacies. First, while polyploidy causes quantum speciation, evolutionary theory implies that these radiations should be non-adaptive. Polyploidy causes reproductive isolation, minute effective population sizes, and increased mutation rates, which all imply a diminished role for selection. Second, due to lack of karyotyping in recent decades and lack of distinction between genomic and genetic effects, it is usually impossible to detect pseudopolyploids. Third, pseudopolyploids lack minority cytotype exclusion because they readily backcross with their progenitors, which thereby means no reproductive isolation for newly formed pseudopolyploids. Pseudopolyploidy will thereby not result in radiations until pseudopolyploid descendants undergo subsequent chromosome rearrangements or grow new centromeres. Pseudopolyploids may have a modest selective advantage over their progenitors due to diminished linkage disequilibrium. Thus, pseudopolyploidy may induce adaptive non-radiations. We encourage a renaissance of karyotyping to distinguish between these two mechanisms and a renaissance in genomic perspectives in evolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".