Development, characterization, and comparative analysis of polymorphism at common bean SSR loci isolated from genic and genomic sources
Bibliographic record
Abstract
Microsatellites or SSRs (single sequence repeats) have been used to construct and integrate genetic maps in crop species, including Phaseolus vulgaris. In the present study, 3 cDNA libraries generated by the Bean EST project (http://lgm.esalq.usp.br/BEST/), comprising a unigene collection of 3126 sequences and a genomic microsatellite-enriched library, were analyzed for the presence of SSRs. A total of 219 expressed sequence tags (ESTs) were found to carry 240 SSRs (named EST-SSR), whereas 714 genomic sequences contained 471 SSRs (named genomic-SSR). A subset of 80 SSRs, 40 EST-SSRs, and 40 genomic-SSRs were evaluated for molecular polymorphism in 23 genotypes of cultivated beans from the Mesoamerican and Andean genetic pools, including Brazilian cultivars and 2 related species. Of the common bean genotypes, 31 EST-SSR loci were polymorphic, yielding 2-12 alleles as compared with 26 polymorphic genomic-SSRs, accounting for 2-7 alleles. Cluster analysis from data using both genic and genomic-SSR revealed a clear separation between Andean and Mesoamerican beans. The usefulness of these loci for distinguishing bean genotypes and genetic mapping is discussed.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".