Discrepancy of flowering time between genetically close sublineages of Aegilops umbellulata Zhuk.
Bibliographic record
Abstract
Aegilops umbellulata Zhuk., a wild diploid wheat-related species, has been used as a genetic resource for several important agronomic traits. However, its genetic variations have not been comprehensively studied. We sequenced RNA from 114 accessions of Ae. umbellulata to evaluate DNA polymorphisms and phenotypic variations. Bayesian clustering and phylogenetic analysis based on SNPs detected by RNA sequencing revealed two divergent lineages, UmbL1 and UmbL2. The main differences between them were in the sizes of spikes and spikelets, and culm diameter. UmbL1 is divided into two sublineages, UmbL1e and UmbL1w. These genetic differences corresponded to geographic distributions. UmbL1e, UmbL1w, and UmbL2 are found in Turkey, Iran/Iraq, and Greece, respectively. Although UmbL1e and UmbL1w were genetically similar, flowering time and other morphological traits were more distinct between these sublineages than those between the lineages. This discrepancy can be explained by the latitudinal and longitudinal differences in habitats. Specifically, latitudinal clines of flowering time were clearly observed in Ae. umbellulata, strongly correlated with solar radiation in the winter season. This observation implies that latitudinal differences are a factor in differences in the flowering times of Ae. umbellulata. Differences in flowering time could influence other morphological differences and promote genetic divergence between sublineages.
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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".