Genomic variation, environmental adaptation, and feralization in ramie, an ancient fiber crop
Bibliographic record
Abstract
Feralization is an important evolutionary process, but the mechanisms behind it remain poorly understood. Here, we use the ancient fiber crop ramie (Boehmeria nivea (L.) Gaudich.) as a model to investigate genomic changes associated with both domestication and feralization. We first produced a chromosome-scale de novo genome assembly of feral ramie and investigated structural variations between feral and domesticated ramie genomes. Next, we gathered 915 accessions from 23 countries, comprising cultivars, major landraces, feral populations, and the wild progenitor. Based on whole-genome resequencing of these accessions, we constructed the most comprehensive ramie genomic variation map to date. Phylogenetic, demographic, and admixture signal detection analyses indicated that feral ramie is of exoferal or exo-endo origin, i.e., descended from hybridization between domesticated ramie and the wild progenitor or ancient landraces. Feral ramie has higher genetic diversity than wild or domesticated ramie, and genomic regions affected by natural selection during feralization differ from those under selection during domestication. Ecological analyses showed that feral and domesticated ramie have similar ecological niches that differ substantially from the niche of the wild progenitor, and three environmental variables are associated with habitat-specific adaptation in feral ramie. These findings advance our understanding of feralization, providing a scientific basis for the excavation of new crop germplasm resources and offering novel insights into the evolution of feralization in nature.
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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 | 0.001 |
| 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) | 0.000 | 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".