Fine Mapping of Carbon Assimilation Rate 8, a Quantitative Trait Locus for Flag Leaf Nitrogen Content, Stomatal Conductance and Photosynthesis in Rice
Bibliographic record
Abstract
Increasing the rate of leaf photosynthesis is one important approach for increasing grain yield in rice (Oryza sativa). Exploiting the natural variation in CO2 assimilation rate (A) between rice cultivars using quantitative genetics is one promising means to identify genes contributing to higher photosynthesis. In this study, we determined precise location of Carbon Assimilation Rate 8 (CAR8) by crossing a high-yielding indica cultivar with a Japanese commercial cultivar. Fine mapping suggested that CAR8 encodes a putative Heme Activator Protein 3 (OsHAP3) subunit of a CCAAT-box-binding transcription factor called OsHAP3H. Sequencing analysis revealed that the indica allele of CAR8 has a 1-bp deletion at 322 bp from the start codon, resulting in a truncated protein of 125 amino acids. In addition, CAR8 is identical to DTH8/Ghd8/LHD1, which was reported to control rice flowering date. The increase of A is largely due to an increase of RuBP regeneration rate via increased leaf nitrogen content, and partially explained by reduced stomatal limitation via increased stomatal conductance relative to A. This allele also increases hydraulic conductivity, which would promote higher stomatal conductance. This indicates that CAR8 affects multiple physiological aspects relating to photosynthesis. The detailed analysis of molecular functions of CAR8 would help to understand the association between photosynthesis and flowering and demonstrate specific genetic mechanisms that can be exploited to improve photosynthesis in rice and potentially other crops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".