DNA methylation, an epigenetic mode of gene expression regulation in reproductive science

Keywords: DNA methylation, epigenetics, reproduction, placenta, sperm, infertility, medically assisted reproduction, imprinted genes. Current Pharmaceutical Design Title:DNA Methylation, An Epigenetic Mode of Gene Expression Regulation in Reproductive Science Volume: 20 Issue: 11 Author(s): Rosamaria Calicchio, Ludivine Doridot, Francisco Miralles, Celine Mehats and Daniel Vaiman Affiliation:

DNA methylation, epigenetics, reproduction, placenta, sperm, infertility, medically assisted reproduction, imprinted genes.

DNA methylation is an important part of the epigenetic code governing gene expression. In human reproductive diseases, recent studies have shown the existence of deviations from the normal methylation profile at various genome loci. In this review, this type of epigenetic alterations is explored in pathological spermatogenesis, ovarian diseases, placental syndromes, such as preeclampsia and Intra- Uterine Growth Restriction, uterine diseases such as endometriosis, and putative pathophysiological effects of Assisted Reproductive Technologies. We review the notion of epigenetics, the technical methods available to analyze methylation, and the known associations between reproductive diseases and DNA methylation, focusing on human pathologies and on animal models when available. We show that imprinted genes control regions (ICRs) are a prominent and frequent target of methylation anomalies in reproductive disorders, but such alterations also affect non-imprinted genes. The mechanistic aspects of gene regulation in response to methylation anomalies are also discussed in this review when they have been investigated. Export Options About this article Cite this article as: Calicchio Rosamaria, Doridot Ludivine, Miralles Francisco, Mehats Celine and Vaiman Daniel, DNA Methylation, An Epigenetic Mode of Gene Expression Regulation in Reproductive Science, Current Pharmaceutical Design 2014; 20 (11) . https://dx.doi.org/10.2174/13816128113199990517 | DOI https://dx.doi.org/10.2174/13816128113199990517 | Print ISSN 1381-6128 | | Publisher Name Bentham Science Publishers | Online ISSN 1873-4286 | Call for Papers in Thematic Issues Accelerating Cancer Drug Discovery Using Artificial Intelligence and In Silico Methods Artificial intelligence and in silico methods speed up cancer drug discovery, transforming how new treatments are developed. 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