High-resolution analyses of human sperm dynamic methylome reveal thousands of novel age-related epigenetic alterations
Notice bibliographique
Résumé
BACKGROUND: Children of aged fathers are at a higher risk of developing mental disorders. Alterations in sperm DNA methylation have been implicated as a potential cause. However, age-dependent modifications of the germ cells' epigenome remain poorly understood. Our objective was to assess the DNA methylation profile of human spermatozoa during aging. RESULTS: We used a high throughput, customized methylC-capture sequencing (MCC-seq) approach to characterize the dynamic DNA methylation in spermatozoa from 94 fertile and infertile men, who were categorized as young, 48 men between 18-38 years or old 46 men between 46-71 years. We identified more than 150,000 age-related CpG sites that are significantly differentially methylated among 2.65 million CpG sites covered. We conducted machine learning using our dataset to predict the methylation age of subjects; the age prediction accuracy based on our assay provided a more accurate prediction than that using the 450 K chip approach. In addition, we found that there are more hypermethylated (62%) than hypomethylated (38%) CpG sites in sperm of aged men, corresponding to 798 of total differential methylated regions (DMRs), of which 483 are hypermethylated regions (HyperDMR), and 315 hypomethylated regions (HypoDMR). Moreover, the distribution of age-related hyper- and hypomethylated CpGs in sperm is not random; the CpG sites that were hypermethylated with advanced age were frequently located in the distal region to genes, whereas hypomethylated sites were near to gene transcription start sites (TSS). We identified a high density of age-associated CpG changes in chromosomes 4 and 16, particularly HyperDMRs with localized clusters, the chr4 DMR cluster overlaps PGC1α locus, a protein involved in metabolic aging and the chr16 DMR cluster overlaps RBFOX1 locus, a gene implicated in neurodevelopmental disease. Gene ontology analysis revealed that the most affected genes by age were associated with development, neuron projection, differentiation and recognition, and behaviour, suggesting a potential link to the higher risk of neurodevelopmental disorders in children of aged fathers. CONCLUSION: We identified thousands of age-related and sperm-specific epigenetic alterations. These findings provide novel insight in understanding human sperm DNA methylation dynamics during paternal aging, and the subsequently affected genes potentially related to diseases in offspring.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».