Development and characterization of EST-derived simple sequence repeat (SSR) markers for pasture grass endophytes
Bibliographic record
Abstract
Fungal endophytes of the genus Neotyphodium are common in temperate pasture grass species and confer both beneficial and deleterious agronomic characteristics to their hosts. The aim of this study was to develop molecular markers based on simple sequence repeat (SSR) loci for the identification and assessment of genetic diversity among Neotyphodium endophytes in grasses. Expressed sequence tags (ESTs) from both Neptyphodium coenophialum and Neotyphodium lolii were examined, and unique SSR loci were identified in 9.7% of the N. coenophialum sequences and 6.3% of the N. lolii sequences. A variety of SSRs were present, although perfect trinucleotide repeat arrays were the most common. Primers were designed to 50 SSR loci from N. coenophialum and 57 SSR loci from N. lolii and were evaluated using 20 Neotyphodium and Epichloë isolates. A high proportion of the N. coenophialum and N. lolii primers produced amplification products from the majority of isolates and most of these primers detected genetic variation. SSR markers from both N. coenophialum and N. lolii detected high levels of polymorphism between Neotyphodium and Epichloë species, and low levels of polymorphism within N. coenophialum and N. lolii. SSR markers may be used in appropriate combinations to discriminate between species. Comparison with amplified fragment length polymorphism (AFLP) data demonstrated that the SSR markers were informative for the assessment of genetic variation within and between endophyte species. These markers may be used to identify endophyte taxa and to evaluate intraspecific population diversity, which may be correlated with variation for endophyte-derived agronomic traits.
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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 | 0.000 | 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 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".