How to Isolate Polysomal RNA to Study Mammalian Early Development.
Bibliographic record
Abstract
Pre-hatching development, which encompasses oocyte maturation until blastocyst escape from the zona pellucidae, can be boldly described as two distinct developmental windows, according to the transcriptional potential of the cells. The first window is characterized by transcriptional silence, where cells support protein synthesis by recruiting stored maternal RNAs, whereas in the second interval, the embryonic genome is active and thus capable of producing de novo mRNAs. The presence of large amounts of stored transcripts destined to be either transcribed later on during development or simply sent for decay creates a large background noise that hinders the potential to gain relevant knowledge on the making of pre-hatching development, either through low (real-time RT-PCR) or high throughput (microarray, deep sequencing) methods. We believe that the study of mRNAs in the process of being translated might offer a better perspective of the making of an early embryo. Consequently, we developed a method that enables the isolation of messenger RNAs found to be bound to ribosomes using sucrose gradient fractionation. The main constraint to achieve such an objective is the small amount of starting material. Here, we present the development of a reliable method that enables the survey of the sub-population of mRNAs found in the polysomal fraction using as little as 100 oocytes or embryos. The method utilizes carrier polysomes prepared from a distant species to provide a confirmation of the polysomal nature of the isolated mRNAs. With such an approach, a method is required to eliminate the contribution of carrier RNA on downstream steps. To do so, ribonucleoprotein complexes are cross-linked and the phylogenetic distance between the carrier and the species of interest was proven to almost completely prevent the potential contribution of the carrier on microarray results. The method was tested to confirm its high repeatability by performing a survey of GV stage polysomal mRNAs using microarray hybridization. The mean correlation value between technical replicates was 0.95. We tested the method in a physiological context by comparing the mRNAs found in the polysomal fractions of GV, GVBD and MII stage bovine oocytes. Survey of the identity of the mRNA found in the polysomal fractions was conducted using microarray and quantitative RT-PCR. Translation behaviour of candidates studied by quantitative RT-PCR (C-Mos, Cyclin B1 and CDK1) is correlated with the underlying physiology of oocyte maturation. Polysomal RNA abundance was shown not to correlate with the corresponding protein levels as polysomal synthesis is supplementary to the initial protein content. To our knowledge, this is the first successful isolation of mRNA confirmed to be of polysomal nature and allowing specific candidate studies. Polysomal fractionation provides a novel angle to study early development that may be more insightful than the study of the entire mRNA content. (poster)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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".