MADS1-regulated lemma and awn development benefits barley yield
Bibliographic record
Abstract
Floral organ shape and size in cereal crops can affect grain size and yield, so genes that regulate their development are promising breeding targets. The lemma, which protects inner floral organs, can physically constrain grain growth; while the awn, a needle-like extension of the lemma, creates photosynthate to developing grain. Although several genes and modules controlling grain size and awn/lemma growth in rice have been characterized, these processes, and the relationships between them, are not well understood for barley and wheat. Here, we demonstrate that the barley E-class gene HvMADS1 positively regulates awn length and lemma width, affecting grain size and weight. Cytological data indicates that HvMADS1 promotes awn and lemma growth by promoting cell proliferation, while multi-omics data reveals that HvMADS1 target genes are associated with cell cycle, phytohormone signaling, and developmental processes. We define two potential targets of HvMADS1 regulation, HvSHI and HvDL, whose knockout mutants mimic awn and/or lemma phenotypes of mads1 mutants. Additionally, we demonstrate that HvMADS1 interacts with APETALA2 (A-class) to synergistically activate downstream genes in awn/lemma development in barley. Notably, we find that MADS1 function remains conserved in wheat, promoting cell proliferation to increase awn length. These findings extend our understanding of MADS1 function in floral organ development and provide insights for Triticeae crop improvement strategies.
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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) | 0.004 | 0.001 |
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".