Development of microsatellite markers for common bean (<i>Phaseolus vulgaris</i>L.) based on screening of non-enriched, small-insert genomic libraries
Bibliographic record
Abstract
Microsatellite markers are useful genetic tools for a wide array of genomic analyses although their development is time-consuming and requires the identification of simple sequence repeats (SSRs) from genomic sequences. Screening of non-enriched, small-insert libraries is an effective method of SSR isolation that can give an unbiased picture of motif frequency. Here we adapt high-throughput protocols for the screening of plasmid-based libraries using robotic colony picking and filter preparation. Seven non-enriched genomic libraries from common bean genomic DNA were made by digestion with four frequently cutting restriction enzymes, double digestion with a frequently cutting restriction enzyme and a less frequently cutting restriction enzyme, or sonication. Library quality was compared and three of the small-insert libraries were selected for further analysis. Each library was plated and picked into 384-well plates that were used to create high-density filter arrays of over 18 000 clones each, which were screened with oligonucleotide probes for various SSR motifs. Positive clones were found to have low redundancy. One hundred SSR markers were developed and 80 were tested for polymorphism in a standard parental survey. These microsatellite markers derived from non-SSR-enriched libraries should be useful additions to previous markers developed from enriched libraries.
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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 | 0.000 | 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 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".