Evidence of mRNA-Mediated Intron Loss in the Human-Pathogenic Fungus <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
Introns are a defining feature of eukaryotic genomes, though the mechanism of intron gain or loss is not well understood. Reverse transcription of mRNA followed by homologous recombination with the genome has been posited as a mechanism of intron loss, though little direct evidence of recent loss events has been described to support this model. We find supporting evidence for an mRNA-mediated mechanism of loss through comparative genome analyses that revealed a recent loss of 10 adjacent introns in a 22-exon gene in the human-pathogenic fungus Cryptococcus neoformans. We surveyed the gene structures of the entire genomes of Cryptococcus gattii, which diverged from the C. neoformans lineage 37 million years ago (Mya), and C. neoformans var. grubii and var. neoformans, which diverged 18 Mya. Our comparison revealed greater than 99.9% intron conservation, with evidence from 20 genes showing evidence of intron loss, but no convincing evidence of intron gain. Our findings confirm that Cryptococcus introns have been quite stable over recent evolutionary time, with occasional mRNA-mediated intron loss events.
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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 | 0.000 | 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) | 0.001 | 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".