Maintenance of Mest imprinted methylation in blastocyst-stage mouse embryos is less stable than other imprinted loci following superovulation or embryo culture
Bibliographic record
Abstract
Assisted reproductive technologies are fertility treatments used by subfertile couples to conceive their biological child. Although generally considered safe, these pregnancies have been linked to genomic imprinting disorders, including Beckwith–Wiedemann and Silver–Russell Syndromes. Silver–Russell Syndrome is a growth disorder characterized by pre- and post-natal growth retardation. The Mest imprinted domain is one candidate region on chromosome 7 implicated in Silver–Russell Syndrome. We have previously shown that maintenance of imprinted methylation was disrupted by superovulation or embryo culture during pre-implantation mouse development. For superovulation, this disruption did not originate in oogenesis as a methylation acquisition defect. However, in comparison to other genes, Mest exhibits late methylation acquisition kinetics, possibly making Mest more vulnerable to perturbation by environmental insult. In this study, we present a comprehensive evaluation of the effects of superovulation and in vitro culture on genomic imprinting at the Mest gene. Superovulation resulted in disruption of imprinted methylation at the maternal Mest allele in blastocysts with an equal frequency of embryos having methylation errors following low or high hormone treatment. This disruption was not due to a failure of imprinted methylation acquisition at Mest in oocytes. For cultured embryos, both the Fast and Slow culture groups experienced a significant loss of maternal Mest methylation compared to in vivo-derived controls. This loss of methylation was independent of development rates in culture. These results indicate that Mest is more susceptible to imprinted methylation maintenance errors compared to other imprinted genes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".