Stable Epigenetic Variants Selected from an Induced Hypomethylated Fragaria vesca Population
Bibliographic record
Abstract
. Epigenetic variation was initially artificially induced using the DNA demethylation reagent 5-azacytidine (5-azaC). It is the first report to explore epigenetic variant selection and phenotypic trait inheritance in strawberry. Transmission frequency of these traits was determined across generations. The early flowering (EF4) and late stolon (LS) phenotypic traits were successfully transmitted across five and three generations through meiosis, respectively. Stable mitotic transmission of the early flowering phenotype was also demonstrated using clonal daughters derived from the 4th Generation (S4) mother plant. In order to further explore the DNA methylation patterns underlying the early flowering trait, the standard MSAP method using isoschizomers Hpa II/Msp I, and newly modified MSAP method using isoschizomers Tfi I/Pfe I which detected DNA methylation at CG, CHG, CHH sites were used in two early flowering lines, EF lines 1 (P2) and EF lines 2 (P3), and control lines (P1). A significant reduction in the number of fully-methylated bands was detected in P2 and P3 when compared to P1 using the novel MSAP method. In the standard MSAP, the symmetric CG and CHG methylation was maintained over generations in the early flowering lines based on the clustering in P2 and P3, the novel MSAP approach revealed the asymmetric CHH methylation pattern was not maintained over generations. This study provides evidence of stable selection of phenotypic traits, particularly early flowering through both meiosis and mitosis, which is meaningful to both breeding programs and commercial horticulture. The maintenance in CG and CHG methylation over generations suggests the early flowering phenotype might be related to DNA methylation alterations at the CG or CHG sites. Finally, this work provides a new approach for studying the role of epigenetics on complex quantitative trait improvement in strawberry, as well as providing a tool to expand phenotypic diversity and expedite potential new horticulture cultivar releases through either seed or vegetative propagation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".