Method to isolate polyribosomal mRNA from scarce samples such as mammalian oocytes and early embryos
Bibliographic record
Abstract
BACKGROUND: Although the transcriptome of minute quantities of cells can be profiled using nucleic acid amplification techniques, it remains difficult to distinguish between active and stored messenger RNA. Transcript storage occurs at specific stages of gametogenesis and is particularly important in oogenesis as stored maternal mRNA is used to sustain de novo protein synthesis during the early developmental stages until the embryonic genome gets activated. In many cases, stored mRNA can be several times more abundant than mRNA ready for translation. In order to identify active mRNA in bovine oocytes, we sought to develop a method of isolating very small amounts of polyribosome mRNA. RESULTS: The proposed method is based on mixing the extracted oocyte cytoplasm with a preparation of polyribosomes obtained from a non-homologous source (Drosophila) and using sucrose density gradient ultracentrifugation to separate the polyribosomes. It involves cross-linking the non-homologous polyribosomes and neutralizing the cross-linking agent. Using this method, we show that certain stages of oocyte maturation coincide with changes in the abundance of polyribosomal mRNA but not total RNA or poly(A). We also show that the abundance of selected sequences matched changes in the corresponding protein levels. CONCLUSIONS: We report here the successful use of a method to profile mRNA present in the polyribosomal fraction obtained from as little as 75 mammalian oocytes. Polyribosomal mRNA fractionation thus provides a new tool for studying gametogenesis and early development with better representation of the underlying physiological status.
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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".