Comprehensive histochemical profiles of histone modification in male germline cells during meiosis and spermiogenesis: Comparison of young and aged testes in mice
Bibliographic record
Abstract
Human epidemiological studies have shown that paternal aging as one of the risk factors for neurodevelopmental disorders, such as autism, in offspring. A recent study has suggested that factors other than de novo mutations due to aging can influence the biology of offspring. Here, we focused on epigenetic alterations in sperm that can influence developmental programs in offspring. In this study, we qualitatively and semiquantitatively evaluated histone modification patterns in male germline cells throughout spermatogenesis based on immunostaining of testes taken from young (3 months old) and aged (12 months old) mice. Although localization patterns were not obviously changed between young and aged testes, some histone modification showed differences in their intensity. Among histone modifications that repress gene expression, histone H3 lysine 9 trimethylation (H3K9me3) was decreased in the male germline cells of the aged testis, while H3K27me2/3 was increased. The intensity of H3K27 acetylation (ac), an active mark, was lower/higher depending on the stages in the aged testis. Interestingly, H3K27ac was detected on the putative sex chromosomes of round spermatids, while other chromosomes were occupied by a repressive mark, H3K27me3. Among other histone modifications that activate gene expression, H3K4me2 was drastically decreased in the male germline cells of the aged testis. In contrast, H3K79me3 was increased in M-phase spermatocytes, where it accumulates on the sex chromosomes. Therefore, aging induced alterations in the amount of histone modifications and in the differences of patterns for each modification. Moreover, histone modifications on the sex chromosomes and on other chromosomes seems to be differentially regulated by aging. These findings will help elucidate the epigenetic mechanisms underlying the influence of paternal aging on offspring development.
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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 | 0.000 | 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".