A highly effective and versatile technology for the isolation of RNAs from grapevines and other woody perennials for use in virus diagnostics
Bibliographic record
Abstract
BACKGROUND: Isolation of pure RNA from woody perennials, especially fruit crops such as grapevine rich in complex secondary metabolites, has remained very challenging. Lack of effective RNA isolation technology has resulted in difficulties in viral diagnosis and discovery as well as studies on many biological processes of these highly important woody plants. It is imperative to develop and refine methodologies with which large amounts of pure nucleic acids can be readily isolated from woody perennials. METHODS: We compared five commonly used RNA isolation kits in isolating total RNA from twelve species of woody perennials. We made modifications to select RNA isolation systems to simplify and improve their efficiency in RNA isolation. The yield and quality of isolated RNAs were assessed via gel electrophoresis and spectrophotometric measurement. We also performed RT-PCR and RT-qPCR to detect several major viruses from grapevines. RESULTS: Two of the kits were shown to be the best in both the yield and quality of the isolated RNA from all twelve woody species. Using disposable extraction bags for tissue homogenization not only improved the yield without affecting quality, but also made the RNA isolation technology simpler, less costly, and suitable for adoption by many potential users with facility limitations. This system was successfully applied to a wide range of woody plants, including fruit crops, ornamentals and timber trees. Inclusion of polyvinylpyrrolidone in the extraction buffer drastically improved the performance of the system in isolating total RNA from old grapevine leaves collected later in the season. This modification made our system highly effective in isolating quality RNA from grapevine leaves throughout the entire growing season. We further demonstrated that the resulting nucleic acid preparations are suitable for detection of several major grapevine viruses with RNA or DNA genomes using PCR, RT-PCR and qPCR as well as for assays on plant microRNAs. CONCLUSIONS: This improved RNA isolation system would have wide applications in viral diagnostics and discovery, studies on gene expression and regulation, transcriptomics, and small RNA biology in grapevines. We believe this system will also be useful in diverse applications pertaining to research on many other woody perennials and recalcitrant plant species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".