The Genetics and Genome-Wide Screening of Regrowth Loci, a Key Component of Perennialism in <i>Zea diploperennis</i>
Bibliographic record
Abstract
Abstract Perennialism is common among the higher plants, yet little is known about its inheritance. Previous genetic studies of the perennialism in Zea have yielded contradictory results. In this study, we take a reductionist approach by specifically focusing on one trait: regrowth (the plant’s ability to restart a new life cycle after senescence on the same body). To address this, six hybrids were made by reciprocally crossing perennial Zea diploperennis Iltis, Doebley & R. Guzman with inbred lines B73 and Mo17 and Rhee Flint, a heirloom variety, of Z. mays L. ssp. mays. All the F1 plants demonstrated several cycles of growth, flowering, senescence and regrowth into normal flowering plants, indicating a dominant effect of the Z. diploperennis alleles. The regrowability (i.e., the plants’ ability to regrow after senescence) was stably transmitted to progeny of the hybrids. Segregation ratios of regrowth in the F2 generations are consistent with the trait controlled by two dominant, complementary loci, but do not exclude the influence of other modifiers or environment. Genome-wide screening with genotyping-by-sequencing technology indicated two major regrowth loci, regrowth 1 (reg1) and regrowth 2 (reg2), were on chromosomes 2 and 7, respectively. These findings lay the foundation for further exploration of the molecular mechanism of regrowth in Z. diploperennis. Importantly, our data indicate that there is no major barrier to transferring this trait into maize or other grass crops for perennial crop development with proper technology, which enhances sustainability of grain crop production in an environmentally friendly way.
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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 | 0.001 | 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".