QTL Identification for Brace‐Root Traits of Maize in Different Generations and Environments
Bibliographic record
Abstract
Elucidating the correlations among maize ( Zea mays L.) brace‐root traits and identifying the quantitative trait loci (QTL) that control the traits are important for genetic improvement of brace‐root traits. Two maize inbred lines, Yi17 (well‐developed root system) and Yi16 (poorly developed root system), an F 2 population derived from their cross containing 276 individuals, and an F 2:3 population containing 241 families were used to analyze the correlations among brace‐root traits and determine the QTL for brace‐root traits at Xiema and Hechuan in 2014 and 2015. All brace‐root traits were highly significantly correlated with each other. In particular, brace‐root diameter was highly correlated with brace‐root fresh weight ( r = 0.730), brace‐root dry weight ( r = 0.729), root fresh weight ( r = 0.734), and root dry weight ( r = 0.754). A total of 212 simple sequence repeat (SSR) markers were used to develop a genetic map based on the F 2 population. The total length of the genetic map was 1558.9 cM, with a mean interval of 7.35 cM between adjacent markers. Ninety‐three QTL controlling the brace‐root traits were detected in generations F 2 at Xiema in 2014 and F 2:3 at Xiema and Hechuan in 2015. However, only two consistent major QTL were identified in F 2:3 generation—qBRTN8b for brace‐root tier number and qBRD8b for brace‐root diameter. The qBRTN8b was located in the mmc0181 to bnlg1031 interval (bin 8.06) on chromosome 8, which explained 32.64% (at Xiema) and 16.18% (at Hechuan) of phenotypic variation. The qBRD8b was mapped in the umc2367 to umc1846 interval (bin 8.05) on chromosome 8, which explained 14.28% (at Xiema) and 10.41% (at Hechuan) of phenotypic variation. Moreover, three new important chromosomal regions harboring QTL for brace‐root traits were detected—bins 5.04, 6.06, and 8.05 to 8.06. These results could provide a very important reference for evaluating root traits under field conditions and for fine mapping QTL of brace‐root traits in maize.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".