Genome Wide Identification and Functional Prediction of Long Non-Coding RNAs Responsive to Sclerotinia sclerotiorum Infection in Brassica napus
Bibliographic record
Abstract
Sclerotinia stem rot caused by Sclerotinia sclerotiorum affects canola production worldwide. Emerging evidence suggests that long non-coding RNAs (lncRNAs) play important roles in the regulation of gene expression in plants, in response to both abiotic and biotic stress. So far, identification of lncRNAs has been limited to a few model plant species, and their roles in mediating responses to biotic stresses are yet to be characterized in Brassica napus. The present study reports the identification of novel lncRNAs responsive to S. sclerotiorum infection in B. napus at two time points after infection (24 hpi and 48 hpi) using a stranded RNA-Sequencing technique and a detection pipeline for lncRNAs. Of the total 3,181 lncRNA candidates, 2,821 lncRNAs were intergenic, 111 were natural antisense transcripts, 76 possessed exonic overlap with the reference coding transcripts while the remaining 173 represented novel lnc- isoforms. Forty one lncRNAs were identified as the precursors for microRNAs (miRNAs) including miR156, miR169 and miR394, with significant roles in mediating plant responses to fungal phytopathogens. A total of 931 differentially expressed lncRNAs were identified in response to S. sclerotiorum infection and the expression of 12 such lncRNAs was further validated using qRT-PCR. B. napus antisense lncRNA, TCONS_00000966, having 90% overlap with a plant defensin gene, showed significant induction at both infection stages, suggesting its involvement in the transcriptional regulation of defense responsive genes under S. sclerotiorum infection. Additionally, nine lncRNAs showed overlap with cis-regulatory regions of differentially expressed genes of B. napus. Quantitative RT-PCR verification of a set of S. sclerotiorum responsive sense/antisense transcript pairs revealed contrasting expression patterns, supporting the hypothesis that steric clashes of transcriptional machinery may lead to inactivation of sense promoter. Our findings highlight the potential contributions of lncRNAs in regulating expression of plant genes that respond to biotic stress.
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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 | 0.000 | 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, 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".