Differential analysis and genome-wide association analysis of stomata density of maize inbred lines leaves at ear position
Bibliographic record
Abstract
The stomatal complex on the surface of maize leaves is closely related to photosynthesis and transpiration, and the study of maize stomatal phenotypes and the discovery of their regulatory genes are of great importance for the breeding of high-quality and high-yielding maize. In this study, rapid scanning electron microscopy was used to obtain images of the abaxial stomata of 457 maize inbred lines with extensive genetic variation, and stomata density was obtained by counting. The results of correlation showed that stomata density was significantly correlated with leaf width, and Analysis of variance found that there were significant differences ( P value < 0.05) in stomata density among different leaf width and 100-grain weight. The highest stomata density was found in the inbred lines with wide and short leaves and higher 100-grain weight. Furthermore, genome-wide association analysis was performed using a mixed linear model. It showed that eight SNPs significantly associated with stomata density were obtained, which could explain 35.507% of the phenotypic variation. Among these, four SNPs on chromosome 5 were tightly linked, mainly formatting two haplotypes, CTTA (0.636) and TCCG (0.330). Twelve genes with functional annotation were identified within 100 kb upstream and downstream of the eight SNPs. One gene, GRMZM2G068277, which had been shown to be involved in plant mitotic processes and exhibited high expression at the leaf base, was therefore the most likely candidate gene for stomata density. The results presented here could provide references for further cloning of functional genes related to stomata density.
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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 | 0.001 |
| 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) | 0.001 | 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".