Nuclear Genome Sequence and Gene Expression of an Intracellular Fungal Endophyte Stimulating the Growth of Cranberry Plants
Bibliographic record
Abstract
Ericaceae thrive in poor soil, which we postulate is facilitated by microbes living inside those plants. Here, we investigate the growth stimulation of the American cranberry (Vaccinium macrocarpon) by one of its fungal endosymbionts, EC4. We show that the symbiont resides inside the epidermal root cells of the host but extends into the rhizosphere via its hyphae. Morphological classification of this fungus is ambiguous, but phylogenetic inference based on 28S rRNA identifies EC4 as a Codinaeella species (Chaetosphaeriaceae, Sordariomycetes, Ascomycetes). We sequenced the genome and transcriptome of EC4, providing the first ‘Omics’ information of a Chaetosphaeriaceae fungus. The 55.3-Mbp nuclear genome contains 17,582 potential protein-coding genes, of which nearly 500 have the capacity to promote plant growth. For comparing gene sets involved in biofertilization, we annotated the published genome assembly of the plant-growth-promoting Trichoderma hamatum. The number of proteins involved in phosphate transport and solubilization is similar in the two fungi. In contrast, EC4 has ~50% more genes associated with ammonium, nitrate/nitrite transport, and phytohormone synthesis. The expression of 36 presumed plant-growth-promoting EC4 genes is stimulated when the fungus is in contact with the plant. Thus, Omics and in-plantae tests make EC4 a promising candidate for cranberry biofertilization on nutrient-poor soils.
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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".