Identifying Fertility Biomarkers Using Omics Approach
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".
Deadline for manuscript submissions: 10 October 2026 | Viewed by 882
Special Issue Editor
Special Issue Information
Dear Colleagues,
Infertility is a growing global concern affecting millions of couples around the world. According to the WHO (2023), nearly 17.5% of the adult population experience infertility worldwide. This complex medical condition arises from various factors, including molecular, cellular, genetic and environmental influences. Despite considerable advancements in reproductive science and its clinical applications, nearly 30% of couples unable to conceive are diagnosed with unexplained infertility.
Omics technology is a high-throughput approach utilized to identify and analyze numerous biological molecules, providing comprehensive insights into biological pathways, regulatory networks, and functional interactions in various health conditions. Omics-based approaches have become integral for reproductive science, enabling high-throughput, system-wide analyses of molecular factors involved in fertility. Genomic, transcriptomic, proteomic, metabolomic, lipidomic and epigenomic studies have facilitated the identification of key genes, regulatory RNAs, proteins, metabolites, and post-translational modifications associated with gamete quality, embryo survivability, and endometrial receptivity. Using omics technologies to determine biomarkers of infertility provides a deeper understanding of the molecular mechanisms underlying infertility, shedding light on idiopathic infertility cases and improving success rates in assisted reproductive technologies.
This Special Issue aims to compile studies on the discovery of fertility-related biomarkers in both males and females through the application of omics and multi-omics approaches in human or mouse models. We will consider original research papers, review papers, and short communications for publication.
Dr. Muhammet Rasit Ugur
Guest Editor
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Keywords
- fertility
- infertility
- biomarker
- omics
- multi-omics
- genomics
- transcriptomics
- proteomics
- metabolomics
- epigenomics
- lipidomic
- microbiomics
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