Towards the development of the PCR-based InDel markers associated with fruit skin quality traits in melon (<i>Cucumis melo</i> L.) using bulked segregant analysis
Bibliographic record
Abstract
Melon's fruit skin quality is an agriculturally important and consumer-appealing trait. To identify molecular markers associated with fruit skin qualities, including reticulation and color, a total of 1200 Insertion/Deletion (InDel) markers randomly selected from the whole genome re-sequencing data of melon were combined with bulk segregant analysis to analyze a panel of melon genetic resources presenting reticulated- and smooth-skinned fruits as well as varying fruit skin colors. Four DNA bulks, including reticulated skin DNA bulk, smoothed skin DNA bulk, green skin DNA bulk, as well as white skin and light yellow skin DNA bulks, were developed. Four DNA pools were created by combining the DNA of 12 representative plants from each DNA bulk for polymorphism analysis, and 200 polymorphic InDel markers were selected. These polymorphic markers were used to characterize typical genetic bands within each DNA bulk. Two InDel markers, MC8-52 and MC4-7, were discovered to be related to fruit surface patterning (reticulated- and smooth-skinned fruits) and fruit color (green and white–light yellow fruits), respectively. These markers offer a high degree of detection accuracy. InDel marker MC8-52 on chromosome 8 achieved detection accuracies of 78.33% and 90.56%, whereas marker MC4-7 on chromosome 4 displayed detection accuracies of 92.92% and 83.35%, respectively. However, these markers were seen as a likely means of identifying strongly related markers for these traits. Hence, a high-resolution map of genomic regions carrying them is required for the development of highly linked markers for these traits.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".