New evidence on the relationship between Microsporidia and Fungi: a genome-wide analysis by DarkHorse software
Bibliographic record
Abstract
Microsporidia are a group of obligate intracellular eukaryotic parasites that infect a wide variety of species, including humans. Phylogenetic analysis indicates a relationship between the Microsporidia and the Fungi. However, most results are based on the analysis of relatively few genes. DarkHorse analysis involves the transformation of BLAST results into a lineage probability index (LPI) value and allows for the comparison of genes for an entire genome with those of other genomes. Thus, we can see which genes from the microsporidia score most closely based on the LPI with other eukaryotic organisms. In this analysis, we calculated the LPI for each gene from the genomes of 7 Microsporidia, Antonospora locustae, Enterocytozoon bieneusi, Encephalitozoon cuniculi, Encephalitozoon intestinalis, Nosema bombycis, Nosema ceranae, and Nematocida parisii, to analyze the genetic relationships between Microsporidia and other species. It was found that many (91%) genes were most closely correlated with genes from other microsporidial genomes and had the highest mean LPI (0.985), indicating a monophyletic origin of the Microsporidia. In a subsequent analysis, we excluded the other Microsporidia from the analysis to look for relationships before the divergence of Microsporidia, and found that 43% of the microsporidial genes scored highest with fungal genes, and a higher mean LPI was found with Fungi than with other kingdoms, suggesting that Microsporidia is closely related to Fungi at the genomic level. Microsporidial genes were functionally clustered based on the KOG (Eukaryotic COG) database, and the possible lineages for each gene family were discussed in concert with the DarkHorse results.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".