Allelic divergence and cultivar-specific SSR alleles revealed by capillary electrophoresis using fluorescence-labeled SSR markers in sugarcane
Bibliographic record
Abstract
Though sugarcane cultivars (Saccharum spp. hybrids) are complex aneupolyploid hybrids, genetic evaluation and tracking of clone- or cultivar-specific alleles become possible through capillary electrophoresis (CE) using fluorescence-labeled SSR markers. Twenty-four sugarcane cultivars, 12 each from India and the USA, were genetically assessed using 21 fluorescence-labeled polymorphic SSR markers. These markers primed the amplification of 213 alleles. Of these alleles, 161 were common to both Indian and US cultivars, 25 were specific to the Indian cultivars, and 27 were observed only in the US cultivars. Only 10 alleles were monomorphic. A high level of heterozygosity was observed in both Indian (82.4%) and US (91.1%) cultivars resulting in average polymorphism information content (PIC) values of 0.66 and 0.77 and marker index (MI) values of 5.07 and 5.58, respectively. Pearson correlation between PIC and MI was significant in both sets of cultivars (r = 0.58 and 0.69). UPGMA clustering separated cultivars into three distinct clusters at 59% homology level. These results propose the potential utility of six Indian cultivar-specific SSR alleles (mSSCIR3_182, SMC486CG_229, SMC36BUQ_125, mSSCIR74_216, SMC334BS_154, and mSSCIR43_238) in sugarcane breeding, vis a vis transporting CE-based evaluation in clone or variety identity testing, cross fidelity assessments, and genetic relatedness among species of the genus Saccharum and related genera.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".