Transcriptome Analysis during Human Trophectoderm Specification Suggests New Roles of Metabolic and Epigenetic Genes
Bibliographic record
Abstract
In humans, successful pregnancy depends on a cascade of dynamic events during early embryonic development. Unfortunately, molecular data on these critical events is scarce. To improve our understanding of the molecular mechanisms that govern the specification/development of the trophoblast cell lineage, the transcriptome of human trophectoderm (TE) cells from day 5 blastocysts was compared to that of single day 3 embryos from our in vitro fertilization program by using Human Genome U133 Plus 2.0 microarrays. Some of the microarray data were validated by quantitative RT-PCR. The TE molecular signature included 2,196 transcripts, among which were genes already known to be TE-specific (GATA2, GATA3 and GCM1) but also genes involved in trophoblast invasion (MUC15), chromatin remodeling (specifically the DNA methyltransferase DNMT3L) and steroid metabolism (HSD3B1, HSD17B1 and FDX1). In day 3 human embryos 1,714 transcripts were specifically up-regulated. Besides stemness genes such as NANOG and DPPA2, this signature included genes belonging to the NLR family (NALP4, 5, 9, 11 and 13), Ret finger protein-like family (RFPL1, 2 and 3), Melanoma Antigen family (MAGEA1, 2, 3, 5, 6 and 12) and previously unreported transcripts, such as MBD3L2 and ZSCAN4. This study provides a comprehensive outlook of the genes that are expressed during the initial embryo-trophectoderm transition in humans. Further understanding of the biological functions of the key genes involved in steroidogenesis and epigenetic regulation of transcription that are up-regulated in TE cells may clarify their contribution to TE specification and might also provide new biomarkers for the selection of viable and competent blastocysts.
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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 | 0.000 | 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) | 0.001 | 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 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".