08SG2/OsBAK1 regulates grain size and number, and functions differently in Indica and Japonica backgrounds in rice
Bibliographic record
Abstract
BACKGROUND: Both grain size and grain number are significant for rice yield. In the past decade, a number of genes related to grain size and grain number have been documented, however, the regulatory mechanisms underlying them remains ambiguous. RESULTS: population. We focused on the linkage region on chromosome 8, and named this locus as 08sg2. One of three SNPs identified in the linkage region was located in an exon of OsBAK1, leading to a nonsynonymous mutation in the kinase domain. The plant harboring the mutant version 08sg2 locus exhibited a decreased grain size, grain number and plant height. Cytological analysis indicated that 08SG2 regulated spikelet hull development by affecting cell proliferation. The grain size and number of knockout mutants of OsBAK1 in the japonica background were significantly decreased, but less so than in 08sg2, supporting the idea that the SNP in OsBAK1 was responsible for the 08sg2 phenotype, but that 08SG2/OsBAK1 function differently in indica and japonica backgrounds. 08sg2 was insensitive to 24-epiBL, and the expression of BR-related genes was obviously altered in 08sg2. The proportionally decreased grain length when 08sg2 and GS3 were combined indicate that 08SG2 and GS3 regulate grain length independently. CONCLUSIONS: Our work shows that 08SG2/OsBAK1 is important for rice yield in both indica and japonica backgrounds, by regulating grain size and grain number, and the function of 08SG2/OsBAK1 is obviously affected by genetic background. The amino acid substituted in 08sg2 is highly conserved among different species, supporting the idea that it is important for the molecular function of 08SG2/OsBAK1. Together, our work is helpful for fully understanding the function of 08SG2/OsBAK1.
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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) | 0.001 | 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".