Identification and characterization of microRNAs from in vitro-grown pear shoots infected with Apple stem grooving virus in response to high temperature using small RNA sequencing
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miRNAs) have functions in diverse biological processes such as growth, signal transduction, disease resistance, and stress responses in plants. Thermotherapy is an effective approach for elimination of viruses from fruit trees. However, the role of miRNAs in this process remains elusive. Previously, we showed that high temperature treatment reduces the titers of Apple stem grooving virus (ASGV) from the tips of in vitro-grown Pyrus pyrifolia plants. In this study, we identified high temperature-altered pear miRNAs using the next generation sequencing technology, and futher molecularly characterized miRNA-mediated regulaton of target gene expression in the meristem tip and base tissues of in vitro-grown, ASGV-infected pear shoots under different temperatures. RESULTS: Using in vitro-grown P. pyrifolia shoot meristem tips infected with ASGV, a total of 22,592,997 and 20,411,254 clean reads were obtained from Illumina high-throughput sequencing of small RNA libraries at 24 °C and 37 °C, respectively. We identified 149 conserved and 141 novel miRNAs. Seven conserved miRNAs and 77 novel miRNAs were differentially expressed at different temperatures. Target genes for differentially expressed known and novel miRNAs were predicted and functionally annotated. Gene Ontology (GO) analysis showed that high-ranking miRNA target genes were involved in metabolic processes, responses to stress, and signaling, indicating that these high temperature-responsive miRNAs have functions in diverse gene regulatory networks. Spatial expression patterns of the miRNAs and their target genes were found to be expressed in shoot tip and base tissues by qRT-PCR. In addition, high temperature reduced viral titers in the shoot meristem tip, while negatively regulated miRNA-mediated target genes related to resistance disease defense and hormone signal transduction pathway were up-regulated in the P. pyrifolia shoot tip in response to high temperature. These results suggested that miRNAs may have important functions in the high temperature-dependent decrease of ASGV titer in in vitro-grown pear shoots. CONCLUSIONS: This is the first report of miRNAs differentially expressed at 24 °C and 37 °C in the meristem tip of pear shoots infected with ASGV. The results of this study provide valuable information for further exploration of the function of high temperature-altered miRNAs in suppressing viral infections in pear and other fruit trees.
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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 | 0.000 |
| 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".