Bioinformatics and multi-omics approaches in male infertility: implications for diagnosis and assisted reproduction

Male infertility accounts for approximately 40-50% of infertility cases worldwide and represents a complex, multifactorial condition influenced by genetic, epigenetic, transcriptomic, proteomic, and metabolic alterations. Despite advances in clinical evaluation, including semen analysis and hormonal profiling, nearly one-third of cases remain classified as idiopathic, highlighting the limitations of conventional diagnostic approaches. In this context, bioinformatics has emerged as a central discipline for integrating and interpreting large-scale biological data generated by high-throughput sequencing and multi-omics technologies. This review provides a comprehensive overview of current bioinformatic applications in male infertility research, encompassing genomic analyses, transcriptomic profiling, epigenetic regulation, proteomic and metabolomic signatures, and artificial intelligence-based approaches. We discuss how integrative multi-omics strategies and computational pipelines enable the identification of novel candidate genes, molecular pathways, and clinically relevant biomarkers associated with impaired spermatogenesis and sperm dysfunction. Furthermore, the translational impact of bioinformatics in assisted reproductive technologies, including sperm and embryo selection, preimplantation genetic testing, and clinical decision support, is highlighted. Collectively, this review underscores the pivotal role of bioinformatics in advancing mechanistic understanding, improving diagnostic precision, and paving the way toward personalized approaches in the management of male infertility.