sRNAs as possible regulators of retrotransposon activity in Cryptococcus gattii VGII
Bibliographic record
Abstract
Background: The absence of Argonaute genes in the fungal pathogen Cryptococcus gattii R265 and other VGII strains indicates that yeasts of this genotype cannot have a functional RNAi pathway, an evolutionarily conserved gene silencing mechanism performed by small RNAs. The success of the R265 strain as a pathogen that caused the Pacific Northwest and Vancouver Island outbreaks may imply that RNAi machinery loss could be beneficial under certain circumstances during evolution. As a result, a hypermutant phenotype would be created with high rates of genome retrotransposition, for instance. This study therefore aimed to evaluate in silicio the effect of retrotransposons and their control mechanisms by small RNAs on genomic stability and synteny loss of C. gattii R265 through retrotransposons sequence comparison and orthology analysis with other 16 C. gattii genomic sequences available. Results: Retrotransposon mining identified a higher sequence count to VGI genotype compared to VGII, VGIII, and VGIV. However, despite the lower retrotransposon number, VGII exhibited increased synteny loss and genome rearrangement events. RNA-Seq analysis indicated highly expressed retrotransposons as well as sRNA production. Conclusions: Genome rearrangement and synteny loss may suggest a greater retrotransposon mobilization caused by RNAi pathway absence, but the effective presence of sRNAs that matches retrotransposon sequences means that an alternative retrotransposon silencing mechanism could be active in genomic integrity maintenance of C. gattii VGII strains.
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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 | 0.001 |
| 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".