Male factor infertility affects one-sixth of couples worldwide, and non-obstructive azoospermia (NOA) is one of the most severe forms. Our previous genome-wide association study (GWAS) identified three susceptibility loci for NOA in Han Chinese men. Here we test promising associations in an extended three-stage validation using 3,608 NOA cases and 5,909 controls to identify additional risk loci. We find strong evidence of three NOA susceptibility loci (P<5.0 × 10−8) at 6p21.32 (rs7194, P=3.76 × 10−19), 10q25.3 (rs7099208, P=6.41 × 10−14) and 6p12.2 (rs13206743, P=3.69 × 10−8), as well as one locus approaching genome-wide significance at 1q42.13 (rs3000811, P=7.26 × 10−8). In addition, we investigate the phenotypic effect of the related gene (gek, orthologous to CDC42BPA) at 1q42.13 on male fertility using a Drosophila model. These results advance our understanding of the genetic susceptibility to NOA and provide insights into its pathogenic mechanism.

Initiation of the first wave of spermatogenesis in the neonatal mouse testis is characterized by differentiation of a transient population of germ cells called gonocytes in the center of the seminiferous tubules. After resuming mitotic activity, gonocytes relocate on the basement membrane, giving rise to spermatogonial stem cells (SSCs). These processes begin from birth in mice, and differentiated type A spermatogonia first appear by day 6 postpartum. During these processes, Sertoli cells within the seminiferous tubules and Leydig cells in the interstitial tissue form the stem cell “niche,” and influence SSC fate decisions. Thus, we collected whole mouse testis tissues during the first wave of spermatogenesis at specific time points (days 0.5, 1.5, 2.5, 3.5, 4.5, and 5.5 postpartum) and constructed a comparative proteomic profile. We identified 252 differentially expressed proteins classified into three clusters based on expression, and bioinformatics analysis correlated each protein pattern to specific cell processes. Expression patterns of nine selected proteins were verified via Western blot, and cellular localizations of three proteins with little known information in testes were further investigated during spermatogenesis. Taken together, the results provide an important reference profile of a functional proteome during neonatal mouse gonocyte and SSC maturation and differentiation.

Ovarian physiology and pathology are important areas of scientific research. Efforts have been made to identify the ovary-related transcriptomes in different species. However, the proteomic studies are limited. The rhesus monkey is very similar to humans, and it is widely used in the study of reproductive biology and medicine. In this study, using an optimized proteomics platform, we successfully identified 5723 rhesus ovarian proteins, of which 4325 proteins were consistently identified in all three replicates and with at least 2 unique peptides. The 4325 proteins were chosen for further analysis. Through gene ontology and pathway analyses, we obtained a preliminary understanding of the function of these proteins. A random immunohistochemistry analysis was used to determine the expression of proteins in various cell types. By comparing the genes identified in this study with genes that were reported to have relatively high levels of expression in human oocytes, we obtained genes that were predicted to play roles in maintenance of normal ovarian physiology. Searching the identified genes from this study against the MGI database gave us a list of proteins those exist in the rhesus monkey ovary and are important for female mouse reproduction as well. The overlap of genes in this study and the genes whose abnormal expression or dysfunction were reported to be associated with human polycystic ovary syndrome (PCOS) and premature ovarian failure (POF) prompted us to use the rhesus monkey to study these two common causes of female infertility. This study may provide a basis for future studies of human reproductive disorders using the rhesus monkey as a model.

Non-obstructive azoospermia (NOA) is a complex and severe condition whose etiology remains largely unknown. In a genome-wide association study (GWAS) of NOA in Chinese men, few loci reached genome-wide significance, although this might be a result of genetic heterogeneity. Single nucleotide polymorphisms (SNPs) without genome-wide significance may also indicate genes that are essential for fertility, and multiple stage validation can lead to false-negative results. To perform large-scale functional screening of the genes surrounding these SNPs, we used in vivo RNA interference (RNAi) in Drosophila, which has a short maturation cycle and is suitable for high-throughput analysis. The analysis found that 7 (31.8%) of the 22 analyzed orthologous Drosophila genes were essential for male fertility. These genes corresponded to nine loci. Of these genes, leukocyte-antigen-related-like (Lar) is primarily required in germ cells to sustain spermatogenesis, whereas CG12404, doublesex-Mab-related 11E (dmrt11E), CG6769, estrogen-related receptor (ERR) and sulfateless (sfl) function in somatic cells. Interestingly, ERR and sfl are also required for testis morphogenesis. Our study thus demonstrates that SNPs without genome-wide significance in GWAS may also provide clues to disease-related genes and therefore warrant functional analysis.

Seminal plasma is a mixture of secretions from several male accessory glands. The seminal plasma contains many secreted proteins which are important for sperm function and male fertility. In this study, we employed N‐linked glycosylated peptide enrichment, combined with LC–MS/MS analysis, and establish the first large scale N‐linked glycoproteome of human seminal plasma. Combined with the results of five biological replicates, a total of 720 N‐glycosylated sites on 372 proteins were identified. Analysis of variations among five individuals revealed similar compositions of N‐glycosylated proteins in seminal plasma. The N‐linked glycoproteome could help us understanding the biological functions of human seminal plasma. The data set could also be a resource for further screening of biomarkers for male diseases including cancer and infertility at the level of N‐glycosylation. For example, N‐glycosylated prostate‐specific antigen is known to be an efficient biomarker that can distinguish benign prostate hyperplasia from prostate cancer. All MS data have been deposited in the ProteomeXchange with identifier PXD000959 (http://proteomecentral.proteomexchange.org/dataset/PXD000959).