Mapping of QTLs Controlling Grain Shape and Populations Construction Derived from Related Residual Heterozygous Lines in Rice
Bibliographic record
Abstract
Grain shape is usually characterized by grain length (GL), grain width (GW), grain thickness (GT) and length to width ratio (LWR), and controlled by quantitative trait locus (QTL). In this paper, QTL analysis was performed using an F2 population and an F8 recombinant inbred line (RIL) population from a cross Xiang743/Katy. A total of 38 QTLs for grain shape were detected and eight of them were repeatedly identified in both populations. Seven for GL, five for GW, five for GT, and eight for LWR were detected in F2 population, explaining totally phenotypic variance of 94.51%, 61.52%, 54.33% and 91.84%, respectively. Five for GL, three for GW, and five for LWR were detected in RILpopulation, explaining totally phenotypic variance of 39.83%, 37.52% and 36.71%, respectively. Many QTLs were located in similar intervals, contributing to complicated trait correlation. A few QTLs were mapped in intervals coincided with previously cloned genes associated with grain size. Two residual heterozygous lines (RHLs) were selected out on the basis of newly identified loci, populations derived from RHLs were constructed for fine mapping QTLs associated with grain shape.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".