SPATA16 promoter hypermethylation and downregulation in male infertility.

Spermatogenesis associated 16 (SPATA16) gene plays an important role in acrosome formation. In this study, we analysed SPATA16 promoter methylation in 29 oligozoospermic infertile and 16 normozoospermic fertile sperm samples and in testicular biopsy from 16 non-obstructive azoospermic and 2 obstructive azoospermic individuals. Next, we analysed SPATA16 level in sperm from 8 oligozoospermic infertile, 6 normozoospermic fertile, 9 IVF failed normozoospermic and 10 IVF successful normozoospermic samples by immunoblotting. This was followed by the analysis of SPATA16 expression in testicular biopsy from azoospermic individuals (n = 8) in comparison to normozoospermic individuals (n = 2). Oligozoospermic infertile sperm samples showed significantly higher methylation in the SPATA16 promoter region. Similarly, testicular biopsy from azoospermic men also showed significantly higher level of DNA methylation. Sub-group analysis of infertile sperm and testicular biopsy samples showed a direct correlation between DNA methylation and the degree of spermatogenic impairment. Oligozoospermic infertile samples and IVF failed samples showed reduced SPATA16 expression in comparison to normozoospermic fertile and IVF successful samples, respectively. Human biopsy analysis showed a significant decrease in SPATA16 expression in hypospermatogenesis, maturation arrest and Sertoli cell only syndrome. In conclusion, hypermethylation in SPATA16 promoter shows a highly significant correlation with infertility, which is consistent with its down-regulation in infertility.

Increased DNA methylation in the spermatogenesis-associated (SPATA) genes correlates with infertility.

BACKGROUND: Spermatogenesis-associated (SPATA) family of genes plays important roles in spermatogenesis, sperm maturation or fertilization. The knockout studies in mice have demonstrated that SPATA genes are crucial for fertility. Gene expression and genetic polymorphism studies have further suggested their correlation with infertility; however, methylation analysis of SPATA genes in human male infertility has not yet been undertaken. OBJECTIVES: To analyze the methylation status of SPATA4, SPATA5 and SPATA6 genes in oligozoospermic male infertility. MATERIALS AND METHODS: In the present study, we have analyzed DNA methylation pattern in the promoter regions of SPATA4, SPATA5 and SPATA6 genes in oligozoospermic patients and compared it with normozoospermic fertile controls. Semen samples were obtained from 30 oligozoospermic infertile and 19 normozoospermic fertile controls, and DNA methylation levels of the target gene promoters were analyzed by amplicon based deep sequencing methylation analysis using MiSeq. RESULTS: SPATA4 (P < 0.0008), SPATA5 (P = 0.009) and SPATA6 (Promoter, P < 0.0005; Exon 1, P = 0.0128) genes were significantly hypermethylated in oligozoospermic patients in comparison to controls. This is the first study reporting a higher methylation in the promoters of SPATA4, SPATA5 and SPATA6 in oligozoospermic infertile individuals in comparison to the normozoospermic fertile controls. DISCUSSION: Altered methylation of SPATA genes would affect pathways involved in sperm production or affect various processes linked to sperm fertility. CONCLUSION: In conclusion, hypermethylation in the SPATA4, SPATA5 and SPATA6 genes correlates with oligozoospermic infertility.

Array-based DNA methylation profiling reveals peripheral blood differential methylation in male infertility.

OBJECTIVE: To study peripheral blood DNA differential methylation in oligozoospermic infertile men in comparison with normozoospermic fertile controls. DESIGN: Case-control study. SETTING: Reproductive biology laboratory. PATIENTS(S): Azoospermic and oligozoospermic infertile patients (n = 6) and normozoospermic fertile controls (n = 6) in the discovery phase, and oligo/asthenozoospermic infertile men (n = 11) and normozoospermic fertile controls (n = 10) in the validation phase. INTERVENTION(S): Blood samples drawn from all participants, DNA isolation and methylation analysis. MAIN OUTCOME MEASURE(S): DNA methylation values analyzed using genomewide methylation 450K BeadChip array, followed by deep sequencing of selected regions for methylation analysis in the neighborhood regions of differentially methylated CpGs. RESULT(S): We found 329 differentially methylated CpG spots, out of which 245 referred to the genes, representing 170 genes. Deep-sequencing analysis confirmed the methylation pattern suggested by 450K array. A thorough literature search suggested that 38 genes play roles in spermatogenesis (PDHA2, PARP12, FHIT, RPTOR, GSTM1, GSTM5, MAGI2, BCAN, DDB2, KDM4C, AGPAT3, CAMTA1, CCR6, CUX1, DNAH17, ELMO1, FNDC3B, GNRHR, HDAC4, IRS2, LIF, SMAD3, SOD3, TALDO1, TRIM27, GAA, PAX8, RNF39, HLA-C, HLA-DRB6), are testis enriched (NFATC1, NMNAT3, PIAS2, SRPK2, WDR36, WWP2), or show methylation differences between infertile cases and controls (PTPRN2, RPH3AL). CONCLUSION(S): We found a statistically significant correlation between peripheral blood DNA methylation and male infertility, raising the hope that epigenome-based blood markers can be used for screening male infertility risk. The study also identified new candidates for spermatogenesis and fertility.

Genome-wide differential methylation analyses identifies methylation signatures of male infertility.

STUDY QUESTION: Do methylation changes in sperm DNA correlate with infertility? STUDY ANSWER: Loss of spermatogenesis and fertility was correlated with 1680 differentially-methylated CpGs (DMCs) across 1052 genes. WHAT IS KNOWN ALREADY: Methylation changes in a number of genes have been correlated with reduced sperm count and motility. STUDY DESIGN, SIZE, DURATION: This case-control study used spermatozoal DNA from 38 oligo-/oligoastheno-zoospermic infertile patients and 26 normozoospermic fertile men. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: Genome-wide methylation analysis was undertaken using 450 K BeadChip on spermatozoal DNA from six infertile and six fertile men to identify DMCs. This was followed by deep sequencing of spermatozoal DNA from 32 infertile patients and 20 fertile controls. MAIN RESULTS AND THE ROLE OF CHANCE: A total of 1680 DMCs were identified, out of which 1436 were hypermethylated and 244 were hypomethylated. Classification of DMCs according to the genes identified BCAN, CTNNA3, DLGAP2, GATA3, MAGI2 and TP73 among imprinted genes, SPATA5, SPATA7, SPATA16 and SPATA22 among spermatogenesis-associated genes, KDM4C and JMJD1C, EZH2 and HDAC4 among genes which regulate methylation and gene expression, HLA-C, HLA-DRB6 and HLA-DQA1 among complementation and immune response genes, and CRISPLD1, LPHN3 and CPEB2 among other genes. Genes showing significant differential methylation in deep sequencing, i.e. HOXB1, GATA3, EBF3, BCAN and TCERG1L, are strong candidates for further investigations. The role of chance was ruled out by deep sequencing of select genes. LARGE-SCALE DATA: N/A. LIMITATIONS, REASON FOR CAUTION: Genome-wide analyses are fairly accurate, but may not be exactly validated in replication studies across all DMCs. We used the 't' test in the genome-wide methylation analysis, whereas other tests could provide a more robust and powerful analysis. WIDER IMPLICATIONS OF THE FINDINGS: DMCs can serve as markers for inclusion in infertility screening panels, particularly those in the genes showing differential methylation consistent with previous studies. The genes validated by deep sequencing are strong candidates for investigations of their roles in spermatogenesis. STUDY FUNDING/COMPETING INTEREST(S): The study was funded by the Council of Scientific and Industrial Research (CSIR), Govt. of India with grant number BSC0101 awarded to Rajender Singh. None of the authors has any competing interest to declare.