Genome‐wide identification of pathogenicity, conidiation and colony sectorization genes in <i>Metarhizium robertsii</i>
Bibliographic record
Abstract
Metarhizium robertsii occupies a wide array of ecological niches and has diverse lifestyle options (saprophyte, insect pathogen and plant symbiont), that renders it an unusually effective model for studying genetic mechanisms for fungal adaptation. Here over 20,000 M. robertsii T-DNA mutants were screened in order to elucidate genetic mechanism by which M. robertsii replicates and persists in diverse niches. About 287 conidiation, colony sectorization or pathogenicity loci, many of which have not been reported in other fungi were identified. By analysing a series of conidial pigmentation mutants, a new fungal pigmentation gene cluster, which contains Mr-Pks1, Mr-EthD and Mlac1 was identified. A conserved conidiation regulatory pathway containing Mr-BrlA, Mr-AbaA and Mr-WetA regulates expression of these pigmentation genes. During conidiation Mr-BlrA up-regulates Mr-AbaA, which in turn controls Mr-WetA. It was found that Hog1-MAPK regulates fungal conidiation by controlling the conidiation regulatory pathway, and that all three pigmentation genes exercise feedback regulation of conidiation. This work provided the foundation for deeper understanding of the genetic processes behind M. robertsii adaptive phenotypes, and advances our insights into conidiation and pigmentation in this fungus.
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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 | 0.000 | 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) | 0.001 | 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".