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Record W1881770522 · doi:10.1071/rdv17n2ab218

218 SELECTIVE REDUCTION OF p66shc mRNA IN BOVINE OOCYTES/EMBRYOS BY RNA INTERFERENCE

2004· article· en· W1881770522 on OpenAlexaff
Laura A. Favetta, Gabriela F. Mastromonaco, Elizabeth J. St. John, W.A. King, Dean H. Betts

Bibliographic record

VenueReproduction Fertility and Development · 2004
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversity of Guelph
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoNemzeti Kutatási és Technológiai HivatalPfizerFundação de Amparo à Pesquisa do Estado de Minas GeraisDeutsche ForschungsgemeinschaftU.S. Department of Agriculture
KeywordsRNA interferenceEmbryoGerminal vesicleBiologyMessenger RNAEmbryogenesisAndrologyCell biologyGene silencingOocyteMolecular biologyRNAGeneGenetics

Abstract

fetched live from OpenAlex

High embryo loss occurs during the first week of in vitro bovine embryo development with a high percentage of embryo death and arrest. These early stages of development are regulated by stored maternal mRNAs that accumulate in the oocyte cytoplasm during its growth phase. In our in vitro production (IVP) system approximately 13.5% of embryos arrest at the 2–4-cell stage, displaying no characteristics of apoptosis. We hypothesized that these arrested embryos enter an oxidative stress-induced senescence-like state. We previously showed that elevated levels of reactive oxygen species and increased levels of the stress-adaptor protein p66shc were associated with this early embryonic arrest. The aim of this study was to selectively down-regulate p66shc mRNA levels in bovine oocytes, using post-transcriptional gene silencing by RNA interference (RNAi), to study the effects of p66shc mRNA “knock-down” on early arrest of IVP bovine embryos. Approximately 12,000 short hairpin (sh) RNAi molecules specific for p66shc were microinjected into bovine germinal vesicle (GV) oocytes. Experiments consisted of a control group undergoing IVF alone, and two groups microinjected with and without p66shc shRNAi molecules. Quantification of p66shc mRNA by real-time PCR was used to assure down-regulation of p66shc mRNA in 2-cell embryos collected at 35 hours post-insemination (hpi). The amount of p66shc mRNA detected in control IVF, vehicle-injected, and p66shc RNAi-injected groups was 0.92 ± 0.02 × 10-5 pg, 1.2 ± 0.20 × 10-5 pg, and 0.46 ± 0.06 × 10-5 pg, respectively. This statistically significant (P < 0.001) reduction in p66shc mRNA levels by 54% upon p66shc shRNAi microinjection was selective for p66shc mRNA, as both histone H2a and p53 mRNA levels were not altered. Percentage of 2–4-cell arrest was evaluated at Day 8 post-insemination and related to p66shc mRNA down-regulation. While there were no significant differences in the percentage of 2–4-cell arrested embryos between the control (13.3 ± 0.8%) and vehicle-microinjected (10.8 ± 0.7%) embryos, there was a significant decrease (P < 0.001) in the incidence of arrest in p66shc shRNAi-microinjected embryos (0.9 ± 0.9%). Quantification by real time PCR in blastocysts from the three groups showed no significant differences in p66shc mRNA levels (P = 0.314) among control IVF, vehicle, or p66shc hairpin RNAi microinjected at 0.59 ± 0.1 × 10-5 pg, 0.57 ± 0.2 × 10-5 pg, and 0.51 ± 0.2 × 10-5 pg, respectively. This suggests that p66shc down-regulation by RNAi might be temporary. Thus, using this novel approach of RNAi and microinjection of oocytes at the GV stage, we were able to selectively down-regulate the expression of p66shc mRNA and correlate this down-regulation with a significant decrease in 2–4 cell arrest. These data reinforce our hypothesis that p66shc is involved in a stress-induced pathway that executes a senescent-like embryonic arrest at the 2–4-cell stage, thereby postulating the possible role of p66shc as a new molecular marker for developmental competence. Statistics performed using ANOVA with Fisher LSD test for multiple comparisons. This work was funded by NSERC, CIHR, OGS, and OMAFRA.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.269
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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