Increased transcriptome variation and localised DNA methylation changes in oocytes from aged mice revealed by parallel single‐cell analysis
Bibliographic record
Abstract
Advancing maternal age causes a progressive reduction in fertility. The decline in developmental competence of the oocyte with age is likely to be a consequence of multiple contributory factors. Loss of epigenetic quality of the oocyte could impair early developmental events or programme adverse outcomes in offspring that manifest only later in life. Here, we undertake joint profiling of the transcriptome and DNA methylome of individual oocytes from reproductively young and old mice undergoing natural ovulation. We find reduced complexity as well as increased variance in the transcriptome of oocytes from aged females. This transcriptome heterogeneity is reflected in the identification of discrete sub-populations. Oocytes with a transcriptome characteristic of immature chromatin configuration (NSN) clustered into two groups: one with reduced developmental competence, as indicated by lower expression of maternal effect genes, and one with a young-like transcriptome. Oocytes from older females had on average reduced CpG methylation, but the characteristic bimodal methylation landscape of the oocyte was preserved. Germline differentially methylated regions of imprinted genes were appropriately methylated irrespective of age. For the majority of differentially expressed transcripts, the absence of correlated methylation changes suggests a post-transcriptional basis for most age-related effects on the transcriptome. However, we did find differences in gene body methylation at which there were corresponding changes in gene expression, indicating age-related effects on transcription that translate into methylation differences. Interestingly, oocytes varied in expression and methylation of these genes, which could contribute to variable competence of oocytes or penetrance of maternal age-related phenotypes in offspring.
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 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".