Utilizing Short Interspersed Nuclear Element as a Genetic Marker for Pre-Harvest Sprouting in Wheat
Bibliographic record
Abstract
Pre-harvest sprouting (PHS) is a complex abiotic stress caused by multiple exogenous and endogenous variables that results in random but significant quality and yield loss at the terminal crop stage in more than half of the wheat-producing areas of the world. Systematic research over more than five decades suggests that addressing this challenge requires tools beyond the traditional genetic manipulation approach. Previous molecular studies indicate a possible role of epigenetics in the regulation of seed dormancy and PHS in crops, especially through RNA-directed DNA methylation (RdDM) pathways mediated by Argonaute (AGO) proteins. In this study, we explore the role of the AGO802B gene associated with PHS resistance in wheat, through the presence of a SINE retrotransposon insertion. The current study found the SINE insertion at 3′UTR of the TaAGO802B present in 73.2% of 41 cultivars analyzed and in 92.6% of the resistant cultivar subset. The average expression of TaAGO802B in cultivars with the SINE insertion was 73.3% lower than in cultivars without insertion. This study also indicated a significant positive correlation between the PHS score and methylation levels in the cultivars. The resistant cultivars with the SINE insertion recorded 54.7% lower methylation levels than susceptible cultivars. Further analysis of a DH population (Sadash × P2711) reveals that SINE insertion co-segregates with PHS resistance. This sets forth the SINE insertion in TaAGO802B as a genetic marker for screening wheat germplasm and as an efficient tool for breeding PHS-resistant wheat cultivars.
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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) | 0.000 | 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".