Default Sex and Single Gene Sex Determination in Dioecious Plants
Bibliographic record
Abstract
A well-established hypothesis for the evolution of dioecy involves two genes linked at a sex determining region (SDR). Recently there has been increased interest in possible single gene sex determination. Work in Populus has finally provided direct experimental evidence for single gene sex determination in plants, using CRISPR-Cas9 to knock out a single gene and convert individuals from female to male. In poplar, the feminizing factor popARR17 acts as a “master regulator”, analogous to the mammalian masculinizing factor SRY. The production of fully functional males from females by a simple single gene knockout is experimental evidence that an antagonistic male-determining factor does not exist in Populus. Mammals have a “default sex” (female), as do poplar trees (Populus), although the default sex in poplars is male. The occurrence of single gene sex determination with a default sex may be much commoner in plants than hitherto expected, especially when dioecy evolved via monoecy. The master regulator does not even need to be at the SDR (although it may be). In most poplars the feminizing factor popARR17 is not at the SDR, but instead a negative regulator of it. So far there is little information on how high-level regulators are connected to floral phenotype. A model is presented of how sex-determining genes could lead to different floral morphologies via MADS-box floral developmental genes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".