Functional divergences of natural variations of <i>TaNAM-A1</i> controlling leaf senescence initiation during wheat grain filling
Bibliographic record
Abstract
Summary Leaf senescence is an essential physiological process related to grain yield potential and nutritional quality. Green leaf duration (GLD) after anthesis directly reflects the leaf senescence process and exhibits large genotypic differences in common wheat; however, the underlying gene regulatory mechanism is still lacking up to now. Here, we report TaNAM-A1 as the causal gene of major loci qGLD-6A for GLD during grain filling by map-based cloning. The role of TaNAM-A1 in regulating leaf senescence, spike length, and grain size was proved by transgenic assay and TILLING mutants analyses. Furthermore, the functional divergences among TaNAM-A1 three haplotypes were systematically evaluated. Wheat varieties with TaNAM-A1d (containing two mutations in CDS of TaNAM-A1 ) had longer GLD and advantages in yield-related traits than those with the wild type TaNAM-A1a . All three haplotypes were functional in transactivating the expression of genes involved in macromolecular degradation and mineral nutrient remobilization, with TaNAM-A1a the strongest activity and TaNAM-A1d the weakest. TaNAM-A1 modulates the expression of TaNAC016-3A and TaNAC-S-7A to trigger senescence initiation. TaNAC016-3A enhances TaNAM-A1 transcriptional activation ability by protein-protein interaction. Our study provides new insights into fine-tuning the leaf functional period and grain yield formation for wheat breeding under different geographical climatic conditions.
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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) | 0.001 | 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".