Nucleotide diversity, natural variation, and evolution of <i>Flexible culm-1</i> and <i>Strong culm-2</i> lodging resistance genes in rice
Bibliographic record
Abstract
Lodging resistance is one of the vital traits in yield improvement and sustainability. Culm wall thickness, diameter, and strength are different traits that can govern the lodging resistance in rice. The genes SCM2 and FC1 have been isolated for culm thickness, strength, and flexibility, but their functional nucleotide variations were still unknown. We used a 13× deep sequence of 795 diverse genotypes to present the functional variation and SNP diversity in SCM2 and FC1. The major functional variant for the SCM2 gene was at position 27480181 and for the FC1 gene at position 31072992. Haplotype analysis of both genes provided their various allelic differences among haplotypes. SCM2 alleles further presented the evolution of Oryza sativa L. subsp. indica and subsp. japonica genomes from common parent in different geographical zones, while the haplotypes of FC1 suggested their evolution from different strains of the common parent Oryza rufipogon. SCM2 showed purifying selection and functional associations with rare alleles, while FC1 displayed balanced selection favored by multiple heterozygous alleles. Genotypes with an allelic combination of SCM2-3 and FC1-2 in japonica background exhibited striking resistance against lodging, which can be used in further breeding programs.
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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 | 0.001 | 0.001 |
| 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 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".