Transcription Factor Expression Patterns in Bovine In Vitro-Derived Embryos Prior to Maternal-Zygotic Transition1
Bibliographic record
Abstract
Maternal-zygotic transition (MZT) is a complex phenomenon characterized by the initiation of transcription in the embryo and the replacement of maternal mRNA with embryonic mRNA. In order for this to occur, transcriptional activation requires various factors and conditions. Our hypothesis is that the lack of transcription in the bovine pre-MZT embryo is due, in part, to an incomplete or dormant transcriptional apparatus. Therefore, in accordance with this hypothesis, functioning transcriptional mechanisms should appear in the eight-cell bovine embryo to facilitate embryonic transcription during the MZT. With this in mind, we examined the presence of selected transcription factors during preimplantation embryo development to establish how their transcript levels change in bovine pre-MZT embryos. To achieve this goal, real-time reverse transcription-polymerase chain reaction was used to quantify the mRNA level of several different transcription factors (YY1, HMGA1, RY-1, P300, CREB, YAP65, HMGN1, HMGB1, NFAR, OCT-4, TEAD2, ATF-1, HMGN2, MSY2, and TBP) in germinal vesicle (GV) and metaphase II (MII) bovine oocytes and in two-, four-, eight-cell, and blastocyst stage embryos produced in vitro. Our results demonstrate that all genes examined can be grouped into five different categories according to their mRNA expression patterns at the developmental stages observed. To summarize, all transcription factors studied were present in pre-MZT embryos and the expression pattern of many of them suggest a potential role in MZT.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".