Variations in <scp><i>CYP</i></scp><i>78</i><scp><i>A</i></scp><i>13</i> coding region influence grain size and yield in rice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Grain size is one of the most important determinants of crop yield in cereals. Here, we identified a dominant mutant, big grain2 (bg2-D) from our enhancer-trapping population. Genetic analysis and SiteFinding PCR (polymerase chain reaction) revealed that BG2 encodes a cytochrome P450, OsCYP78A13. Sequence search revealed that CYP78A13 has a paralogue Grain Length 3.2 (GL3.2, LOC_Os03g30420) in rice with distinct expression patterns, analysis of transgenic plants harbouring either CYP78A13 or GL3.2 showed that both can promote grain growth. Sequence polymorphism analysis with 1529 rice varieties showed that the nucleotide diversity at CYP78A13 gene body and the 20 kb flanking region in the indica varieties were markedly higher than those in japonica varieties. Further, comparison of the genomic sequence of CYP78A13 in the japonica cultivar Nipponbare and the indica cultivar 9311 showed that there were three InDels in the promoter region and eight SNPs (single nucleotide polymorphism) in its coding sequence. Detailed examination of the transgenic plants with chimaeric constructs suggested that variation in CYP78A13 coding region is responsible for the variation of grain yield. Taken together, our results suggest that the variations in CYP78A13 in the indica varieties hold potential in rice breeding for application of grain yield improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 it