Loss of Genomic Imprinting in Mouse Embryos with Fast Rates of Preimplantation Development in Culture1
Bibliographic record
Abstract
Currently, the stage of embryo development has been proposed as one of many criteria for identifying healthy embryos in infertility clinics with the fastest embryos being highlighted as the healthiest. However the validity of this as an accurate criterion with respect to genomic imprinting is unknown. Given that embryo development in culture generally requires an extra day compared to in vivo development, we hypothesized that loss of imprinting correlates with slower rates of embryonic development. To evaluate this, embryos were recovered at the 2-cell stage, separated into four groups based on morphological stage at two predetermined time points, and cultured to blastocysts. We examined cell number, embryo volume, embryo sex, imprinted Snrpn and H19 methylation, imprinted Snrpn, H19, and Cdkn1c expression, and expression of genes involved in embryo metabolism-Atp1a1, Slc2a1, and Mapk14-all within the same individual embryo. Contrary to our hypothesis, we observed that faster developing embryos exhibited greater cell numbers and embryo volumes as well as greater perturbations in genomic imprinting and metabolic marker expression. Embryos with slower rates of preimplantation development were most similar to in vivo derived embryos, displaying similar cell numbers, embryo volumes, Snrpn and H19 imprinted methylation, H19 imprinted expression, and Atp1a1 and Slc2a1 expression. We conclude that faster development rates in vitro are correlated with loss of genomic imprinting and aberrant metabolic marker expression. Importantly, we identified a subset of in vitro cultured embryos that, according to the parameters evaluated, are very similar to in vivo derived embryos and thus are likely most suitable for embryo transfer.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".