Development and characterization of genic SSR markers in<i>Medicago truncatula</i>and their transferability in leguminous and non-leguminous species
Bibliographic record
Abstract
Expressed sequence tag (EST)-derived simple sequence repeat (eSSR) markers are important resources for gene discovery and comparative mapping aimed at crop improvement. In this study, we developed eSSR markers for Medicago truncatula and assessed their cross-species transferability. We detected 36,847 non-redundant sequences ("unigenes") from 198,642 M. truncatula EST sequences. Mining of microsatellites from the 36,847 unigene sequences (representing approximately 25.8 Mb) revealed 14,637 eSSRs in 11,750 SSR-containing ESTs, and primer pairs were successfully designed for 4,636 (39.5%). Of the 14 637 eSSRs, 82.6% were mononucleotide repeats and the rest (in descending order of abundance) were tri-, di-, penta-, and tetranucleotide repeats. When less stringent SSR detection criteria were used, the frequency of dinucleotide repeat motifs increased more than twofold, and the frequencies of di- (11%) and trinucleotide motifs (10.6%) were almost equal. This demonstrates that the eSSR frequency and distribution were related to the choice of search criteria. Forty-one randomly selected primer pairs were validated, and their transferability in three leguminous and three non-leguminous species was assessed. The markers showed a high level of transferability in the leguminous (53%-71%) and non-leguminous (33%-44%) species. The validation studies thus demonstrate the utility of the Medicago eSSRs in assessing genomic relationships in both leguminous and non-leguminous species.
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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".