Insight into the Complexity of Male Infertility: a Multi-Omics Review

SYSTEMS BIOLOGY IN REPRODUCTIVE MEDICINE(2024)

引用 0|浏览0
摘要
Male infertility is a reproductive disorder, accounting for 40-50% of infertility.Currently, in about 70% of infertile men, the cause remains unknown.With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging.The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, noncoding RNA, proteins, and metabolites worth further exploring.Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping.A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics.A GO enrichment analysis was performed using the Enrichr tool.We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies.Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent.With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.
更多
查看译文
关键词
Genomics,epigenomics,transcriptomics,proteomics,male infertility
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn