Expansion and Conservation of Biosynthetic Gene Clusters in Pathogenic Pyrenophora spp.
Bibliographic record
Abstract
Pyrenophora is a fungal genus responsible for a number of major cereal diseases. Although fungi produce many specialised or secondary metabolites for defence and interacting with the surrounding environment, the repertoire of specialised metabolites (SM) within Pyrenophora pathogenic species remains mostly uncharted. In this study, an in-depth comparative analysis of the P. teres f. teres, P teres f. maculata and P. tritici-repentis potential to produce SMs, based on in silico predicted biosynthetic gene clusters (BGCs), was conducted using genome assemblies from PacBio DNA reads. Conservation of BGCs between the Pyrenophora species included type I polyketide synthases, terpene synthases and the first reporting of a type III polyketide synthase in P teres f. maculata. P. teres isolates exhibited substantial expansion of non-ribosomal peptide synthases relative to P. tritici-repentis, hallmarked by the presence of tailoring cis-acting nitrogen methyltransferase domains. P. teres isolates also possessed unique non-ribosomal peptide synthase (NRPS)-indole and indole BGCs, while a P. tritici-repentis phytotoxin BGC for triticone production was absent in P. teres. These differences highlight diversification between the pathogens that reflects their different evolutionary histories, host adaption and lifestyles.
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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".