Selection of reference genes for expression analysis of plant-derived microRNAs in Plutella xylostella using qRT-PCR and ddPCR
Bibliographic record
Abstract
The establishment of an expression quantification system that can be easily applied for the comparison of microRNAs (miRNAs) from biological samples is an important step toward understanding functional mechanisms in organisms. However, there is lack of attention on the selection of reference genes for miRNA expression profiling in insect herbivores. Here, we explored the candidate reference genes in a notorious pest of cruciferous crops, Plutella xylostella, for normalization of miRNA expression in developmental stages and tissues and in response to a change of food source from artificial diet to host plant Arabidopsis thaliana. We first compared the expression levels and stability of eight small RNAs using qRT-PCR, and found that miR11 was the most suitable reference gene for expression quantification of the miRNAs. We then confirmed this finding using digital droplet PCR and further validated with a well-studied cross-kingdom miRNA derived from A. thaliana (ath-miR159a). However, none of the reference genes was applicable for all experimental conditions, and multiple reference genes were sometimes required within the same experiment. Our work provides a method for the selection of reference genes for quantification of plant-derived miRNAs, which paves the way for unveiling their roles in the insect-plant coevolution.
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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".