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Record W2596341518 · doi:10.1093/biolreprod/83.s1.240

How to Isolate Polysomal RNA to Study Mammalian Early Development.

2010· article· en· W2596341518 on OpenAlexaff
Sara Scantland, Claude Robert, Marie-Hélène Desrochers, Edward W. Khandjian, Marc‐André Sirard

Bibliographic record

VenueBiology of Reproduction · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBiologyPolysomeRNABlastocystMessenger RNACell biologyOocyteTranslation (biology)EmbryoPopulationRibosomeTranscriptomeComputational biologyEmbryogenesisGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

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)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.008

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.

Opus teacher head0.010
GPT teacher head0.270
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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