Identification and analysis of genes expressed in the <i>Ustilago maydis</i> dikaryon: uncovering a novel class of pathogenesis genes
Bibliographic record
Abstract
The released genome sequence of Ustilago maydis provided immense insight into this pathogen's genetic structure; however, thorough annotation of the genome requires data from many sources. Information from 4425 expressed sequence tags from the filamentous dikaryon provided an excellent resource for genome annotation. This allowed confirmation and correction of gene models, as well as the documentation of transcript structural features. The depth of coverage provided by the normalized dikaryon cDNA library contributed to the discovery of new candidate pathogenesis genes and enabled the identification of U. maydis antisense and noncoding RNAs. Candidate pathogenesis genes were identified based on their representation in the dikaryon library only or in the dikaryon and diploid cDNA libraries, followed by comparative analysis with the genome sequences of other plant pathogens. Six genes that were conserved only among pathogenic fungi and six genes unique to U. maydis were confirmed to be expressed in planta using reverse-transcriptase PCR. The transcript level of three of these genes varied during the transition from filamentous dikaryotic growth to the formation of the teliospore. This discovery provides representative genes that can be used to begin dissecting the control of gene expression during this transition in pathogenic development. Many of the newly identified U. maydis noncoding RNAs were differentially represented among cDNA libraries, suggesting potential functional roles in different U. maydis cell types. The deletion of one such ncRNA in a solopathogenic strain reduced virulence, revealing a new type of pathogenesis gene in fungi.
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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".