Microevolution of the VQ gene family in six species of <i>Fragaria</i>
Bibliographic record
Abstract
VQ motif-containing proteins play crucial roles in plant growth, development, and stress responses. However, no information of VQ motif-containing proteins has been studied at the microevolutionary level in species of Fragaria. In this study, a total of 19, 21, 23, 23, 23, and 25 genes containing the VQ motif were identified from the genomes of F. nipponica, F. iinumae, F. orientalis, F. vesca, F. nubicola, and F. x ananassa, respectively. We classified the VQ genes into 15 clades with grapevine VQ genes, which indicated that at least 15 ancient VQ genes existed before the divergence of the six studied species of Fragaria. Phylogenetic analysis indicated that 28 gene duplication events have occurred in the evolutionary process of the six species of Fragaria. Structural analysis showed that most of the VQ genes have no introns and that VQ proteins in each clade have a similar motif composition. The majority of gene pairs had Ka/Ks ratios less than 1, which illustrated that most of the VQ genes underwent purifying selection in the six species of Fragaria. Four types of cis-elements in promoters of VQ genes were detected, which is an important basis for further studies about plant stress responses. Furthermore, the expression analysis of FvVQ genes indicated that these genes are expressed differentially in the examined organs and tissues. The identification of VQ genes and the analysis of VQ gene duplication and polyploidization events in the six species of Fragaria provide important information on the evolutionary fate of VQ genes during the divergence of the six species of Fragaria.
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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".