Genome expansion and lineage-specific genetic innovations in the forest pathogenic fungi Armillaria
Bibliographic record
Abstract
Armillaria species are both devastating forest pathogens and some of the largest terrestrial organisms on Earth. They forage for hosts and achieve immense colony sizes via rhizomorphs, root-like multicellular structures of clonal dispersal. Here, we sequenced and analysed the genomes of four Armillaria species and performed RNA sequencing and quantitative proteomic analysis on the invasive and reproductive developmental stages of A. ostoyae. Comparison with 22 related fungi revealed a significant genome expansion in Armillaria, affecting several pathogenicity-related genes, lignocellulose-degrading enzymes and lineage-specific genes expressed during rhizomorph development. Rhizomorphs express an evolutionarily young transcriptome that shares features with the transcriptomes of both fruiting bodies and vegetative mycelia. Several genes show concomitant upregulation in rhizomorphs and fruiting bodies and share cis-regulatory signatures in their promoters, providing genetic and regulatory insights into complex multicellularity in fungi. Our results suggest that the evolution of the unique dispersal and pathogenicity mechanisms of Armillaria might have drawn upon ancestral genetic toolkits for wood-decay, morphogenesis and complex multicellularity.
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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 | 0.000 |
| 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".