Small RNA sequencing reveals a role for sugarcane miRNAs and their targets in response to Sporisorium scitamineum infection
Bibliographic record
Abstract
BACKGROUND: Sugarcane smut caused by Sporisorium scitamineum leads to a significant reduction in cane yield and sucrose content. MicroRNAs (miRNAs) play an important role in regulating plant responses to biotic stress. The present study was the first to use two sugarcane genotypes, YA05-179 (smut-resistant) and ROC22 (smut-susceptible), to identify differentially expressed miRNAs in sugarcane challenged with S. scitamineum by using high-throughput sequencing. RESULTS: The predicted target gene number corresponding to known differentially expressed miRNAs in YA05-179 was less than that in ROC22, however most of them were in common. Expression of differential miRNAs under S. scitamineum challenge was mostly downregulated, with similar trends in the two varieties. Gene ontology (GO) analysis showed that the target gene classification of known miRNAs was similar to that of the newly identified miRNAs. These were mainly associated with cellular processes and metabolic processes in the biological process category, as well as combination and catalytic activity in the molecular function category. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these predicted target genes involved in a series of physiological and biochemical pathways or disease resistance-related physiological metabolism and signal transduction pathways, suggesting that the molecular interaction mechanism between sugarcane and S. scitamineum was a complex network system. These findings also showed certain predicted target genes of miR5671, miR5054, miR5783, miR5221, and miR6478 play roles in the mitogen-activated protein kinase (MAPK) signaling pathway, plant hormone signal transduction, and plant-pathogen interaction. Quantitative real-time PCR (qRT-PCR) analysis showed that majority of the known miRNAs and its predicted target genes followed a negatively regulated mode. Seven out of eight predicted target genes showed identical expression after 12 h treatment and reached the highest degree of matching at 48 h, indicating that the regulatory role of miRNAs on the target genes in sugarcane was maximized at 48 h after S. scitamineum challenge. CONCLUSIONS: Taken together, our findings serve as evidence for the association of miRNA expression with the molecular mechanism underlying the pathogenesis of sugarcane smut, particularly on the significance of miRNA levels in relation to the cultivation of smut-resistant sugarcane varieties.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".