Identification and potential value of candidate genes in patients with non-obstructive azoospermia

Unraveling the genetic basis of azoospermia: transcriptome profiling analyses in a Greek population

OBJECTIVE

To investigate whether idiopathic nonobstructive azoospermia (iNOA) has its own transcriptomic signature.

DESIGN

Testicular tissue biopsies were retrieved, processed, and prepared for ribonucleic acid (RNA) extraction from 26 consented patients diagnosed with iNOA. Samples were grouped into four pools based on the presence of testicular spermatozoa: two replicate pools for "No presence" (Null-spz-1 and Null-spz-2 pools), one for "High presence" (High-spz pool), and one for "Rare presence" (Rare-spz pool). A second set of replicate pools (CF-1 and CF-2) were used from patients with obstructive azoospermia (OA) and served as controls. RNA sequencing (RNA-seq) and comparative transcriptomics analysis were performed, followed by differential gene expression analysis focused on protein-coding genes only. Differentially expressed genes (DEGs) exclusively upregulated or downregulated were further analyzed using the Gene Ontology (GO), STRING, and Kyoto Encyclopedia of Genes and Genome bioinformatic platforms.

SUBJECTS

Males in whom iNOA was diagnosed.

EXPOSURE

Testicular biopsies from men in whom iNOA was diagnosed.

MAIN OUTCOME MEASURES

Protein-coding DEGs.

RESULTS

A significantly altered transcriptomic profile of protein-coding genes was identified in the testicular tissues from men with iNOA. A total of 3,858 genes exhibited dysregulated expression, with 1,994 genes being exclusively downregulated and 1,734 upregulated. Biological processes such as male gamete generation (GO:0048232) and meiotic cycle (GO:0051321) were significantly enriched by the downregulated DEGs whereas the upregulated DEGs enriched BPs such as regulation of cell death (GO:0010941), regulation of cell adhesion (GO:0030155), and defense response (GO:0006952). Interactome analysis identified hub genes among the downregulated DEGs, including PCNA, PLK1, MCM4, CDK1, CCNB1, AURKA, CCNA2, and CDC6, and among the upregulated DEGs, including EGFR, RELA, CTNNB1, MYC, JUN, SMAD3, STAT3 NFKB1, TGFB1, and ACTB. In addition, Kyoto Encyclopedia of Genes and Genome analysis demonstrated that pathways such as cell cycle (hsa04110) and oocyte meiosis (hsa04114) are primarily affected by the downregulated genes, whereas the upregulated genes mainly affected pathways such as the focal adhesion (hsa04510) and the PI3-Akt signaling pathway (hsa04151).

CONCLUSION

A distinct messenger RNA expression profile and altered transcriptomic activity were identified in the testicular tissues of men with iNOA.

CLINICAL TRIAL REGISTRATION NUMBER

University of Thessaly 1, 15.04.2016 and the Greek National Authority 701/15.9.2017.

Possible involvement of a MEG3-miR-21-SPRY1-NF-κB feedback loop in spermatogenic cells proliferation, autophagy, and apoptosis

Non-obstructive azoospermia (NOA) is the most incurable form of male infertility with a complex etiology. Long non-cording RNAs (lncRNAs) were associated with regulating spermatogenesis. Herein, differentially expressed lncRNAs between NOA and control male were screened by RNA-seq analysis. MEG3 was upregulated in NOA tissues and inhibited cell proliferation and promoted cell autophagy and apoptosis in vitro. Through RNA immunoprecipitation (RIP), biotin pull-down assays, and dual-luciferase reporter assays, MEG3 was proved to act as a competing endogenous RNA of microRNA (miR)-21 and thus influenced the SPRY1/ERK/mTOR signaling pathway. Additionally, bioinformatic prediction and chip assay revealed that MEG3 was possibly regulated by nuclear factor κB (NF-κB) and SPRY1/NF-κB/MEG3 formed a feedback loop. Seminiferous tubule microinjection further investigated the effects of MEG3 on testes in vivo. These findings demonstrated that MEG3-miR-21-SPRY1-NF-κB probably acted as a feedback loop leading to azoospermia. Our study might provide a target and theoretical basis for diagnosing and treating NOA.

Differential abundance of microRNAs in seminal plasma extracellular vesicles (EVs) in Sahiwal cattle bull related to male fertility

Sahiwal cattle, known for their high milk yield, are propagated through artificial insemination (AI) using male germplasm, largely contingent on semen quality. Spermatozoa, produced in the testes, carry genetic information and molecular signals essential for successful fertilization. Seminal plasma, in addition to sperm, contains nano-sized lipid-bound extracellular vesicles (SP-EVs) that carry key biomolecules, including fertility-related miRNAs, which are essential for bull fertility. The current study focused on miRNA profiling of SP-EVs from high-fertile (HF) and low-fertile (LF) Sahiwal bulls. SP-EVs were isolated using size exclusion chromatography (SEC) and characterized by dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA). Western blotting detected the EV-specific protein markers TSG101 and CD63. The DLS analysis showed SP-EV sizes of 170-180 nm in HF and 130-140 nm in LF samples. The NTA revealed particle concentrations of 5.76 × 1010 to 5.86 × 1011 particles/mL in HF and 5.31 × 1010 to 2.70 × 1011 particles/mL in LF groups, with no significant differences in size and concentration between HF and LF. High-throughput miRNA sequencing identified 310 miRNAs in SP-EVs from both groups, with 61 upregulated and 119 downregulated in HF bull. Further analysis identified 41 miRNAs with significant fold changes and p-values, including bta-miR-1246, bta-miR-195, bta-miR-339b, and bta-miR-199b, which were analyzed for target gene prediction. Gene Ontology (GO) and KEGG pathway analyses indicated that these miRNAs target genes involved in transcription regulation, ubiquitin-dependent endoplasmic reticulum-associated degradation (ERAD) pathways, and signalling pathways. Functional exploration revealed that these genes play roles in spermatogenesis, motility, acrosome reactions, and inflammatory responses. qPCR analysis showed that bta-miR-195 had 80% higher expression in HF spermatozoa compared to LF, suggesting its association with fertility status (p < 0.05). In conclusion, this study elucidates the miRNA cargoes in SP-EVs as indicators of Sahiwal bull fertility, highlighting bta-miR-195 as a potential fertility factor among the various miRNAs identified.

CEP112 coordinates translational regulation of essential fertility genes during spermiogenesis through phase separation in humans and mice

Spermiogenesis, the complex transformation of haploid spermatids into mature spermatozoa, relies on precise spatiotemporal regulation of gene expression at the post-transcriptional level. The mechanisms underlying this critical process remain incompletely understood. Here, we identify centrosomal protein 112 (CEP112) as an essential regulator of mRNA translation during this critical developmental process. Mutations in CEP112 are discovered in oligoasthenoteratospermic patients, and Cep112-deficient male mice recapitulate key phenotypes of human asthenoteratozoospermia. CEP112 localizes to the neck and atypical centrioles of mature sperm and forms RNA granules during spermiogenesis, enriching target mRNAs such as Fsip2, Cfap61, and Cfap74. Through multi-omics analyses and the TRICK reporter assay, we demonstrate that CEP112 orchestrates the translation of target mRNAs. Co-immunoprecipitation and mass spectrometry identify CEP112's interactions with translation-related proteins, including hnRNPA2B1, EEF1A1, and EIF4A1. In vitro, CEP112 undergoes liquid-liquid phase separation, forming condensates that recruit essential proteins and mRNAs. Moreover, variants in patient-derived CEP112 disrupt phase separation and impair translation efficiency. Our results suggest that CEP112 mediates the assembly of RNA granules through liquid-liquid phase separation to control the post-transcriptional expression of fertility-related genes. This study not only clarifies CEP112's role in spermatogenesis but also highlights the role of phase separation in translational regulation, providing insights into male infertility and suggesting potential therapeutic targets.

Oxidative Stress Biomarkers in Male Infertility: Established Methodologies and Future Perspectives

Male fertility can be affected by oxidative stress (OS), which occurs when an imbalance between the production of reactive oxygen species (ROS) and the body's ability to neutralize them arises. OS can damage cells and influence sperm production. High levels of lipid peroxidation have been linked to reduced sperm motility and decreased fertilization ability. This literature review discusses the most commonly used biomarkers to measure sperm damage caused by ROS, such as the high level of OS in seminal plasma as an indicator of imbalance in antioxidant activity. The investigated biomarkers include 8-hydroxy-2-deoxyguanosine acid (8-OHdG), a marker of DNA damage caused by ROS, and F2 isoprostanoids (8-isoprostanes) produced by lipid peroxidation. Furthermore, this review focuses on recent methodologies including the NGS polymorphisms and differentially expressed gene (DEG) analysis, as well as the epigenetic mechanisms linked to ROS during spermatogenesis along with new methodologies developed to evaluate OS biomarkers. Finally, this review addresses a valuable insight into the mechanisms of male infertility provided by these advances and how they have led to new treatment possibilities. Overall, the use of biomarkers to evaluate OS in male infertility has supplied innovative diagnostic and therapeutic approaches, enhancing our understanding of male infertility mechanisms.

Integrated molecular-network analysis reveals infertility-associated key genes and transcription factors in the non-obstructive azoospermia

BACKGROUND

Male infertility is a multifactorial reproductive health problem with complex causes. Non-obstructive azoospermia (NOA) is characterized by failure of spermatogenesis, leading to the absence of spermatozoa in ejaculates. The molecular mechanism underlying the NOA is still not well understood.

OBJECTIVES

This study aims to identify the key genes involved in male infertility that could be a potential biomarker in the diagnosis and prognosis of azoospermia.

STUDY DESIGN

The microarray expression profiles dataset GSE45885 and GSE45887 were downloaded from the NCBI's Gene Expression Omnibus (GEO) database and analyzed for male infertility-associated differentially expressed genes (DEGs) using the GEO2R tool. The common DEGs between the two datasets were combined and their protein-protein interaction (PPI) network was constructed using Cytoscape to reveal the hub genes by topology and module analysis. In addition, transcription factors (TFs) and protein kinases regulating the hub genes were identified using the X2K tool. Then, the expression of the hub genes was validated by analyzing the GSE190752 microarray dataset. Further, the PPI network was screened for biological roles and enriched pathways using DAVID software.

RESULTS

About 256 DEGs associated with NOA were identified and constructed the PPI network to find the infertility-associated proteins. The biological processes linked with these proteins were spermatogenesis, cell differentiation, flagellated sperm motility, and spermatid development. The topology and module analysis of the infertility-associated protein network identified the hub genes TEX38, FAM71F, PRR30, FAM166A, LYZL6, TPPP2, ARMC12, SPACA4, and FAM205A, which were found to be upregulated in the non-obstructive azoospermia. In addition, a total of 23 transcription factors and 3 protein kinases that are regulating these key hub genes were identified. Further these hub genes expression was validated using the microarray data and found that their expression was increased in the testicular biopsies obtained from NOA subjects, compared to healthy individuals.

CONCLUSION

The identified key genes and its associated transcription factors are known to regulate the infertility-related processes in the non-obstructive azoospermia. Also, the clinical sample-based microarray data validation for the expression of these key hub genes indicates their potentiality to develop them as diagnostic or prognostic biomarkers for NOA.

Harnessing male germline epigenomics for the genetic improvement in cattle

Sperm is essential for successful artificial insemination in dairy cattle, and its quality can be influenced by both epigenetic modification and epigenetic inheritance. The bovine germline differentiation is characterized by epigenetic reprogramming, while intergenerational and transgenerational epigenetic inheritance can influence the offspring's development through the transmission of epigenetic features to the offspring via the germline. Therefore, the selection of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers. We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.

Aberrant Gene Expression Profiling in Men With Sertoli Cell-Only Syndrome

Sertoli cell-only syndrome (SCOS) is the most severe and common pathological type of non-obstructive azoospermia. The etiology of SCOS remains largely unknown to date despite a handful of studies reported in this area. According to the gene expression of testicular tissue samples in six datasets from the Gene Expression Omnibus, we detected 1441 differentially expressed genes (DEGs) between SCOS and obstructive azoospermia (OA) testicular tissue samples. Enriched GO terms and KEGG pathways for the downregulated genes included various terms and pathways related to cell cycle and reproduction, while the enrichment for the upregulated genes yielded many inflammation-related terms and pathways. In accordance with the protein-protein interaction (PPI) network, all genes in the most critical module belonged to the downregulated DEGs, and we obtained nine hub genes, including CCNB1, AURKA, CCNA2, BIRC5, TYMS, UBE2C, CDC20, TOP2A, and OIP5. Among these hub genes, six were also found in the most significant SCOS-specific module obtained from consensus module analysis. In addition, most of SCOS-specific modules did not have a consensus counterpart. Based on the downregulated genes, transcription factors (TFs) and kinases within the upstream regulatory network were predicted. Then, we compared the difference in infiltrating levels of immune cells between OA and SCOS samples and found a significantly higher degree of infiltration for most immune cells in SCOS than OA samples. Moreover, CD56bright natural killer cell was significantly associated with six hub genes. Enriched hallmark pathways in SCOS had remarkably more upregulated pathways than the downregulated ones. Collectively, we detected DEGs, significant modules, hub genes, upstream TFs and kinases, enriched downstream pathways, and infiltrated immune cells that might be specifically implicated in the pathogenesis of SCOS. These findings provide new insights into the pathogenesis of SCOS and fuel future advances in its theranostics.