Epigenetic regulation of reproduction in human and in animal models
Notice bibliographique
Résumé
Historically, epigenetics has referred to chemical modifications made to DNA that regulate gene expression without changing DNA sequence. These modifications are mitotically heritable and are passed from parent cell to daughter cell. The definition of epigenetics has expanded to include not only modifications made to DNA but also post-translational modifications to histones and chromatin structure. In the reproduction field, epigenetic research has mostly focused around epigenetic reprogramming, genomic imprinting, epigenomic changes related to pathology, and more recently cell-type composition, and epigenetic aging. DNA methylation is the most extensively studied epigenetic mark, particularly in reproductive biology, but an expanding epigenetics toolkit has also begun to provide methods for understanding the roles of chromatin accessibility and histone modifications (Table I). New published work is available on chromatin accessibility relating to the placenta (Domcke et al., 2020) as well as reproductive tissue cancers as reviewed recently (Ramarao-Milne et al., 2021). There is still much to learn mechanistically about the integration of DNA methylation, histone modifications and chromatin accessibility in reproductive tissues. It is of great interest to the reproductive health community to advance understanding of how the epigenetic modifications in gametes, embryos, placentae and associated tissues change in response to a myriad of conditions, such as assisted reproductive techniques (ART), pathology, stress, and paternal age. To study epigenetic changes that are associated with human health and disease, it is also important to establish a nuanced understanding of epigenetic variability that exists in healthy tissues and cells. Previous work by M.H.R. highlighted innovative studies in cell-type specific gene expression through the ‘Single cell analysis in development’ special issue. M.H.R. now aims to provide a unique resource to the reproduction field by publishing a special collection of reproductive epigenetics articles (Barratt, 2016) . Overall, a large knowledgebase has established that epigenetic regulation plays a critical role in developmental origins of health and disease (DoHaD) (Barker, 2007), but reproductive medicine has yet to develop ways to harness the potential that epigenetic mechanisms may have in the treatment of disease. Comparative study of human health and disease, animal models, and in vitro systems is crucial to support the investigation of hypothesized mechanisms of epigenetic regulation. To support the advancement of this field, M.H.R. is currently accepting original research and review articles in consideration of a special collection on reproductive epigenetics. A comprehensive, integrated understanding of tissue-specific and cell type-specific epigenetic mechanisms in normal, disease, and aging contexts is needed to provide building blocks for the development of new biomarkers and therapeutic approaches, such as those used in fertility preservation following chemotherapy (Szymanska et al., 2020). The M.H.R. ‘Human and Animal Model Reproductive Epigenetics’ collection will serve as a platform for discussion and collaboration by recognizing emerging innovative breakthroughs and significant accomplishments. In the sections below, we elaborate further on some of the specific focus areas that are of interest within the field of reproductive epigenetics. Epigenetic reprogramming events occur during early embryonic development and gametogenesis, such as the recently uncovered epigenetic regulation of N6-methyladenosine mRNA modifications (Fang et al., 2021). Prior to gametogenesis, global demethylation, which is loss of DNA methylation at most genomic regions, occurs in uncommitted primordial germ cells (Canovas et al., 2017). Primary imprinted regions are the one exception, retaining their DNA methylation status (Manku and Culty, 2015). During fertilization, paternal chromatin proteins termed protamines are removed by maternal factors and equipped with new histones (Fraser and Lin, 2016). After fertilization, epigenetic mechanisms play central roles in early developmental events including preservation of maternal mRNA messages in the subcortical maternal complex (Mahadevan et al., 2017), zygotic genome activation (Hug and Vaquerizas, 2018), x-inactivation (Jeon et al., 2012), and genomic imprinting (Barlow and Bartolomei, 2014; Marcho et al., 2015). Epigenetic regulation also plays a critical role in restricting cell potency with lineage commitment as growth and development progress. The recruitment of chromatin-modifying enzymes that alter chromatin dynamics is a phenomenon observed in close association with development. Furthermore, after fetal development is complete, developmental mechanisms may still be reactivated in response to injury or disease. In the immune system, epigenetic regulation of dendritic cells is crucial to maintain the heterogeneity needed to constitute complex innate and adaptive immunity (Tian et al., 2017). Maternal genotype has also been shown to influence the immunocompetency of offspring. For example, wildtype mice produced through surrogacy with immunodeficient NOD SCID (NS) female mice display altered adaptive and innate immune responsiveness as well as adiposity which persisted in mature offspring (Gerlinskaya et al., 2019). Epigenetic events have also been observed in association with aging. Loss of DNA methylation has emerged as a specific hallmark of organismal aging. The DNA methylation landscape of an organism undergoes epigenetic changes with age, termed an epigenetic shift, in which some loci lose or gain genomic DNA methylation in a predictable manner. These loci have garnered interest as potential biomarkers of age, known as epigenetic clocks (Horvath, 2013; Mayne et al., 2017; Lee et al., 2019). Epigenetic clocks can predict chronological age with high sensitivity (Mitteldorf, 2015; Jylhävä et al., 2017; Horvath and Raj, 2018). Mayne et al. showed accelerated epigenetic age in early-onset preeclampsia placentas however, Lee et al. did not reproduce that finding (Mayne et al., 2017; Lee et al., 2019). Interestingly, Brockway et al. (2021) recently reported changes in DNA methylation in spontaneous preterm birth placentas and suggested that accelerated aging may play a role in the pathogenesis (Brockway et al., 2021). Current data are insufficient to understand how age-associated epigenetic shift is regulated at the molecular level in specific tissues. More work is needed to determine clinical use of DNA methylation as a biomarker of disease in the reproduction field (Fransquet et al., 2019). Further research is warranted to evaluate the potential for clinical application of DNA methylation as a biomarker for developmental origins of disease, including placental syndromes. Genomic imprinting, epigenetic inheritance, inter-generational, and trans-generational mechanisms of transmission have been proposed to influence developmental phenotypes and organismal health which was recently reviewed in (Skvortsova et al., 2018). The phenomenon of genomic imprinting, for example, was first recognized in part due to the distinct placenta phenotypes that emerged from the generation of embryos with two maternal or two paternal genomes (Barlow and Bartolomei, 2014). More recently, a strong association has been observed between the maternal milieu and developmental phenotypes of offspring. Hypertensive disorders of pregnancy have been associated with altered placental DNA methylation patterns (Leavey et al., 2018; Wilson et al., 2018) as well as altered neonatal DNA methylation patterns (Kazmi et al., 2019). Placental DNA methylation patterns are associated with maternal adaptations to pregnancy, such as development of insulin resistance which is critical for normal fetal growth (Hivert et al., 2020). Interestingly, methylated genes associated with insulin sensitivity were enriched for targets of miRNA (Hivert et al., 2020), suggesting that epigenetic mechanisms may underlie metabolic adaptations to pregnancy. Epigenetic regulation at the IGF1 locus in the placenta has also been associated with fetal programming (Álvarez-Nava and Lanes, 2017). Maternal nutrition during gestation is correlated with altered epigenetic control of peroxisome proliferator-activated receptors (PPAR) in the placenta and can exert long-term influences on the PPAR DNA methylation pattern in offspring organs (Lendvai et al., 2016). Molecular mechanisms underlying trans-generational effects of one’s experiences, which may reflect a form of Lamarckian inheritance or Darwin’s theory of pangenesis, have not yet been fully elucidated. Studies performed on stress have identified traits transmitted through the maternal lineage (Bronson and Bale, 2016; Yehuda and Lehrner, 2018), but the majority of studies so far have focused on paternal transmission. For example, environmentally induced changes in small noncoding RNA content in sperm have been implicated in altering phenotypes in offspring, presumably by influence their development (Rodgers et al., 2015). The Feig lab has driven innovation in this field by investigating the trans-generational consequences of adolescent male exposure to chronic social instability stress prior to mating (Saavedra-Rodríguez and Feig, 2013) which leads to female-specific behavioral changes in offspring across multiple generations. The results of this study implicated stress-induced alterations in the levels of sperm-specific miRNAs that persist in early embryos (Saavedra-Rodríguez and Feig, 2013). The same sperm miRNAs were also altered in men raised in abusive and/or dysfunctional families (Dickson et al., 2018). These changes could be an epigenetic response to stress or evidence of a paternal trans-generational DNA methylation pattern transmission phenomenon that is conserved in humans. Mechanistically, epididymis-derived exosomes termed epididymosomes are poised to influence transgenerational effects through the transfer of protein and RNA cargo during sperm maturation (Nejabati et al., 2021). Future research on mechanisms of intergenerational and transgenerational inheritance in humans is needed. Epigenetic modifications can be perpetuated through errors that may influence gene gene is a epigenetic that has been suggested to lineage cell and cell growth et al., 2017). gene is of factors at gene loci that in cells following cell et al., 2017). 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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 |
| 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 ».