Genetic overlap of QTL associated with low-temperature tolerance at germination and seedling stage using BILs in soybean
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Bibliographic record
Abstract
Zhang, W.-B., Jiang, H.-W., Qiu, P.-C., Liu, C.-Y., Chen, F.-L., Xin, D.-W., Li, C.-D., Hu, G.-H. and Chen, Q.-S. 2012. Genetic overlap of QTL associated with low-temperature tolerance at germination and seedling stage using BILs in soybean. Can. J. Plant Sci. 92: 1381-1388. Low temperature is one of the critical environmental factors that limit agricultural production worldwide. In northeast China soybean frequently suffers low temperature stress, especially at germination stage and seedling stage. The most effective way to solve this problem is to breed cultivars with low-temperature tolerance. A set of advanced backcross introgression lines was constructed with Hongfeng 11 as recurrent parent, which was a local variety in Heilongjiang province, and Harosoy as donor parent, which was introduced from Canada. Their BC2F4 lines were screened in low-temperature condition at the two stages, and 41 transgressive lines were selected out at germination stage and 45 lines at seedling stage. Sixty-four and fifty-one pairs of simple sequence repeat primers with fine polymorphism were used for genotyping the selected population and random population at the two stages, respectively. Related quantitative trait loci (QTL) were obtained by chi-test and ANOVA analysis with genotypic and phenotypic data. Finally, 25 QTL at germination stage and 13 QTL at seedling stage were mapped. Among them, 10 QTL overlapped between two stages, which showed a partial genetic crossover on low-temperature tolerance stages in soybean. This would play an important role in marker-assisted selection for breeding elite variety with low-temperature tolerance at both stages.
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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 it