A natural variant of NAL1, selected in high-yield rice breeding programs, pleiotropically increases photosynthesis rate
Bibliographic record
Abstract
Improvement of leaf photosynthesis is an important strategy for greater crop productivity. Here we show that the quantitative trait locus GPS (GREEN FOR PHOTOSYNTHESIS) in rice (Oryza sativa L.) controls photosynthesis rate by regulating carboxylation efficiency. Map-based cloning revealed that GPS is identical to NAL1 (NARROW LEAF1), a gene previously reported to control lateral leaf growth. The high-photosynthesis allele of GPS was found to be a partial loss-of-function allele of NAL1. This allele increased mesophyll cell number between vascular bundles, which led to thickened leaves, and it pleiotropically enhanced photosynthesis rate without the detrimental side effects observed in previously identified nal1 mutants, such as dwarf plant stature. Furthermore, pedigree analysis suggested that rice breeders have repeatedly selected the high-photosynthesis allele in high-yield breeding programs. The identification and utilization of NAL1 (GPS) can enhance future high-yield breeding and provides a new strategy for increasing rice productivity.
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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) | 0.001 | 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 | 0.001 |
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".