Ultra-low input transcriptomics reveal the spore functional content and phylogenetic affiliations of poorly studied arbuscular mycorrhizal fungi
Why this work is in the frame
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Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) are a group of soil microorganisms that establish symbioses with the vast majority of land plants. To date, generation of AMF coding information has been limited to model genera that grow well axenically; Rhizoglomus and Gigaspora. Meanwhile, data on the functional gene repertoire of most AMF families is non-existent. Here, we provide primary large-scale transcriptome data from eight poorly studied AMF species (Acaulospora morrowiae, Diversispora versiforme, Scutellospora calospora, Racocetra castanea, Paraglomus brasilianum, Ambispora leptoticha, Claroideoglomus claroideum and Funneliformis mosseae) using ultra-low input ribonucleic acid (RNA)-seq approaches. Our analyses reveals that quiescent spores of many AMF species harbour a diverse functional diversity and solidify known evolutionary relationships within the group. Our findings demonstrate that RNA-seq data obtained from low-input RNA are reliable in comparison to conventional RNA-seq experiments. Thus, our methodology can potentially be used to deepen our understanding of fungal microbial function and phylogeny using minute amounts of RNA material.
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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 | 0.001 | 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 | 0.001 | 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 it