Characterization of new polymorphic functional markers for sugarcane
Bibliographic record
Abstract
Expressed sequence tags (ESTs) offer the opportunity to exploit single, low-copy, conserved sequence motifs for the development of simple sequence repeats (SSRs). The authors have examined the Sugarcane Expressed Sequence Tag database for the presence of SSRs. To test the utility of EST-derived SSR markers, a total of 342 EST-SSRs, which represent a subset of over 2005 SSR-containing sequences that were located in the sugarcane EST database, could be designed from the nonredundant SSR-positive ESTs for possible use as potential genic markers. These EST-SSR markers were used to screen 18 sugarcane (Saccharum spp.) varieties. A high proportion (65.5%) of the above EST-SSRs, which gave amplified fragments of foreseen size, detected polymorphism. The number of alleles ranged from 2 to 24 with an average of 7.55 alleles per locus, while polymorphism information content values ranged from 0.16 to 0.94, with an average of 0.73. The ability of each set of EST-SSR markers to discriminate between varieties was generally higher than the polymorphism information content analysis. When tested for functionality, 82.1% of these 224 EST-SSRs were found to be functional, showing homology to known genes. As the EST-SSRs are within the expressed portion of the genome, they are likely to be associated to a particular gene of interest, improving their utility for genetic mapping; identification of quantitative trait loci, and comparative genomics studies of sugarcane. The development of new EST-SSR markers will have important implications for the genetic analysis and exploitation of the genetic resources of sugarcane and related species and will provide a more direct estimate of functional diversity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".