Transcriptome analysis of smut fungi reveals widespread intergenic transcription and conserved antisense transcript expression
Bibliographic record
Abstract
BACKGROUND: Biotrophic fungal plant pathogens cause billions of dollars in losses to North American crops annually. The model for functional investigation of these fungi is Ustilago maydis. Its 20.5 Mb annotated genome sequence has been an excellent resource for investigating biotrophic plant pathogenesis. Expressed-sequence tag libraries and microarray hybridizations have provided insight regarding the type of transcripts produced by U. maydis but these analyses were not comprehensive and there were insufficient data for transcriptome comparison to other smut fungi. To improve transcriptome annotation and enable comparative analyses, comprehensive strand-specific RNA-seq was performed on cell-types of three related smut species: U. maydis (common smut of corn), Ustilago hordei (covered smut of barley), and Sporisorium reilianum (head smut of corn). RESULTS: In total, >1 billion paired-end sequence reads were obtained from haploid cell, dikaryon and teliospore RNA of U. maydis, haploid cell RNA of U. hordei, and haploid and dikaryon cell RNA of S. reilianum. The sequences were assembled into transfrags using Trinity, and updated gene models were created using PASA and categorized with Cufflinks Cuffcompare. Representative genes that were predicted for the first time with these RNA-seq analyses and genes with novel annotation features were independently assessed by reverse transcriptase PCR. The analyses indicate hundreds more predicted proteins, relative to the previous genome annotation, could be produced by U. maydis from altered transcript forms, and that the number of non-coding RNAs produced, including transcribed intergenic sequences and natural antisense transcripts, approximately equals the number of mRNAs. This high representation of non-coding RNAs appears to be a conserved feature of the smut fungi regardless of whether they have RNA interference machinery. Approximately 50% of the identified NATs were conserved among the smut fungi. CONCLUSIONS: Overall, these analyses revealed: 1) smut genomes encode a number of transcriptional units that is twice the number of annotated protein-coding genes, 2) a small number of intergenic transcripts may encode proteins with characteristics of fungal effectors, 3) the vast majority of intergenic and antisense transcripts do not contain ORFs, 4) a large proportion of the identified antisense transcripts were detected at orthologous loci among the smut fungi, and 5) there is an enrichment of functional categories among orthologous loci that suggests antisense RNAs could have a genome-wide, non-RNAi-mediated, influence on gene expression in smut fungi.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".