RGS14 binding to GNAI3 regulates human SSC proliferation and apoptosis through PLPP2, and abnormalities in these genes are associated with azoospermia

RGS14 binding to GNAI3 regulates human SSC proliferation and apoptosis through PLPP2, and abnormalities in these genes are associated with azoospermia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article RGS14 binding to GNAI3 regulates human SSC proliferation and apoptosis through PLPP2, and abnormalities in these genes are associated with azoospermia Dai Zhou, Bang Liu, Lvjun Liu, Lin peng, Xiaowen Liu, Fang Zhu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5770052/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Non-obstructive azoospermia (NOA) is a severe form of male infertility characterized by the absence of sperm in the ejaculate due to impaired spermatogenesis. Spermatogonial stem cells (SSCs) play a crucial role in maintaining male fertility by ensuring continuous sperm production. However, the molecular mechanisms regulating SSC fate and their involvement in NOA remain largely unknown. Results In this study, we utilized single-cell RNA sequencing to analyze gene expression profiles in normal and NOA testes, revealing a significant downregulation of RGS14 in SSCs of NOA patients. We found that RGS14 interacts with GNAI3 and modulates SSC proliferation and apoptosis by regulating the expression of PLPP2 and the MAPK signaling pathway. Knockdown of RGS14 significantly inhibited SSC proliferation and increased apoptosis, effects that were partially rescued by overexpression of PLPP2. Additionally, both PLPP2 and GNAI3 were found to be significantly downregulated in NOA patients, correlating with the expression pattern of RGS14. Conclusions Our findings provide novel insights into the molecular mechanisms underlying SSC dysfunction in NOA. The dysregulation of RGS14, GNAI3, and PLPP2 may contribute to the pathogenesis of NOA. These results not only elucidate the role of RGS14 in SSC fate determination but also identify potential therapeutic targets for male infertility. RGS14 GNAI3 PLPP2 spermatogonial stem cells NOA proliferation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Reproductive health is a fundamental right of human beings and an important component of social development. However, the infertility rate in China has been increasing annually due to environmental pollution, high levels of urban living pressure, delayed marriage and childbearing age, and other reasons. By 2020, the infertility rate had approached 18%, with approximately 50% of cases caused by male factors[ 1 , 2 ]. A sharp decline in sperm quantity and concentration, as well as genetic mutations leading to sperm developmental disorders, are important causes of infertility[ 3 , 4 ]. Spermatogonial stem cells (SSCs) are the foundation for continuous sperm production and the maintenance of male fertility[ 5 ]. SSCs possess the characteristics of self-maintenance, renewal, and differentiation[ 6 , 7 ]. Studying their developmental and differentiation mechanisms will provide important breakthroughs for clinically activating and utilizing SSCs to treat male infertility. The formation and development of mouse SSCs is a complex and precise process involving multiple developmental events and signaling pathways. During embryonic days E8.5–10.5 in mice, primordial germ cells (PGCs) migrate to the gonadal ridge and form the testis with somatic cells. During this process, PGCs undergo rapid proliferation and differentiate into M-prospermatogonia (M-proSg) on day E12[ 8 ]. Subsequently, around embryonic day E15, M-proSg cells exit mitosis and arrest at the G0 phase, becoming T1-prospermatogonia (T1-proSg)[ 9 ]. It is not until approximately 2 days after birth (P2) that T1-proSg resumes mitosis and transforms into actively dividing (P2-P3) T2-prospermatogonia (T2-proSg), which then (P4-P6) further develop into spermatogonia[ 10 , 11 ]. Current research on SSCs has focused mainly on the mechanisms of maintenance and self-renewal in adult mouse testes. The PI3K/AKT and Src pathways are currently identified as core signaling pathways involved in the process of SSC self-renewal[ 12 ]. Glial cell line-derived neurotrophic factor (GDNF) secreted by Sertoli cells can activate the PI3K/AKT and Src pathways through the receptors GFRA1 and c-Ret within SSCs[ 13 ], initiating a series of genes and transcription factors related to SSC maintenance and self-renewal, such as Etv5 , Bcl6b and Lhx1 [ 14 , 15 ]. Fibroblast growth factor (FGF) secreted by Sertoli cells not only activates the Src pathway but also acts synergistically with colony stimulating factor 1 (CSF1) secreted by interstitial cells to regulate SSCs through cooperation with GDNF[ 16 , 17 ]. Additionally, promyelocytic leukemia zinc finger protein (PLZF) is currently recognized as a crucial transcription factor necessary for SSC maintenance and self-renewal, promoting SSC maintenance and self-renewal by relieving mTORC1 pathway inhibition of the GDNF receptors GFRA1 and c-Ret, whereas SALL4 can antagonize the function of PLZF[ 18 – 20 ]. However, the aforementioned studies were all conducted in mice. The cell types and biochemical phenotypes of human spermatogonial stem cells are different from those of rodent stem cells[ 21 , 22 ]. Therefore, the molecular regulatory mechanisms governing the fate determination of human spermatogonial stem cells and rodent spermatogonial stem cells may differ. Several studies have investigated human SSC proliferation, self-renewal, and apoptosis. microRNA-1908-3p promotes SSC proliferation by degrading KLF2[ 23 ]. FGF5 stimulates human SSC proliferation through the activation of AKT and ERK[ 24 ]. We previously demonstrated that ASB9[ 25 ], TCF3[ 26 ], MAGEB2[ 27 ], SPOCD1[ 28 ] and PTN[ 29 ] are specifically expressed in human SSCs and regulate their self-renewal, proliferation, and apoptosis. At present, the fate determination of human spermatogonial stem cells and the molecular mechanisms underlying spermatogenic disorders have not been fully elucidated. Regulator of G-protein signaling 14 (RGS14) is a multifunctional protein that integrates the G protein and H-Ras signaling pathways[ 30 ]. It possesses an RGS domain that binds to active Gαi/o-GTP subunits, promoting GTP hydrolysis, and a G protein regulatory (GPR) motif that selectively binds inactive Gαi1/3-GDP subunits, forming a stable heterodimer at cellular membranes[ 31 ]. RGS14 also contains two tandem Ras/Rap-binding domains (RBDs) that interact with H-Ras, preferentially binding activated H-Ras-GTP in live cells to increase H-Ras cellular activity[ 32 ]. This interaction is regulated by inactive Gαi1-GDP and G protein-coupled receptors (GPCRs), highlighting the role of RGS14 as a key regulator of signal transduction, particularly in hippocampal-based learning and memory[ 33 ]. However, whether RGS14 plays a role in SSC fate determination and spermatogenesis remains unknown. In this study, we analyzed the scRNA-seq profiles of NOA and normal testes, revealing a significant reduction in SSCs in NOA and a marked downregulation of the RGS14 gene in these cells. Knockdown of RGS14 in a human SSC line notably inhibited cell proliferation and downregulated the expression of proteins associated with self-renewal while increasing apoptosis. RNA sequencing revealed a significant decrease in PLPP2 gene expression following RGS14 knockdown, and overexpression of PLPP2 mitigated the cellular phenotypic defects induced by RGS14 downregulation. Through database predictions and experiments such as protein immunoprecipitation, GNAI3 was confirmed to be a molecular partner in RGS14-mediated regulation of SSC function. Additionally, we observed significant downregulation of both PLPP2 and GNAI3 in NOA testes. These findings provide novel insights into the molecular mechanisms underlying SSC dysfunction in NOA and potential therapeutic targets for male infertility. Materials and methods Ethical Statement and Sample Collection The study was approved by the ethics committee of CITIC-Xiangya (LL-SC-2021-025), and all participants provided signed informed consent. Testicular tissues were collected from 15 patients aged 25–46 years who underwent testicular biopsy, with approximately 25 mg of tissue from each patient. To eliminate blood cells, the samples were thoroughly rinsed with sterile PBS on at least three occasions. The samples were subsequently preserved in liquid nitrogen or treated with 4% PFA or Bouin's fixative solution. scRNA-seq analysis of normal and NOA testes Single-cell sequencing data were analyzed primarily via the Seurat 4 R package ( https://github.com/satijalab/Seurat )[ 34 ]. The Read10x function was used to import the scRNA-seq datasets GSE149512[ 35 ] (3 NOA testicular samples) and GSE112013 [ 36 ] (3 normal testicular samples) into R, generating the Seurat object. Gene expression data were then filtered, retaining cells with gene expression values ranging from 500–7500 and less than 20% of genes related to mitochondria. All the mitochondrial and ribosomal genes were removed on the basis of their nomenclature. Duplicate entries were detected and eliminated via the DoubletFinder R package ( https://github.com/chris-mcginnis-ucsf/DoubletFinder )[ 37 ]. The NormalizeData and FindVariableFeatures functions were applied to each Seurat object. All the Seurat objects were combined via the FindIntegrationAnchors and IntegrateData functions. Data clustering was performed after the default UMAP technique was used, and cell types were subsequently determined by evaluating the expression of cellular markers. The plot1 cell R package ( https://github.com/HumphreysLab/plot1 cell) was used to plot graphs after identifying and clustering the cells[ 38 ]. Transcriptional data of SSCs were analyzed via the clusterProfiler R package ( https://github.com/YuLab-SMU/clusterProfiler ) for differentially expressed genes and Gene Ontology (GO) analysis[ 39 ]. To investigate the expression of RGS14 during SSC development, data from SSCs were collected, reclustered via Seurat, and then imported into the Monocle3 R package ( https://cole-trapnell-lab.github.io/monocle3/ ) to create developmental trajectories for SSCs[ 40 ]. All the dot, line, and violin plots were created and modified via ggplot2 ( https://github.com/tidyverse/ggplot2 ) in R[ 41 ]. Culture of human SSC lines The human SSC line was established by introducing the large T antigen into GPR125-positive undifferentiated spermatogonia from humans[ 42 ]. This human SSC line retains several characteristics and markers of primary SSCs, including GFRA1, RET, and PLZF, but does not express testicular endosomal cell markers such as SOX9. The immortalized human SSCs were cultured at 34°C with a 5% CO2 concentration in DMEM/F12 (Gibco, Carlsbad, CA, USA) supplemented with 10% FBS (Gibco). The cells were subcultured every 48 to 72 hours with 0.5 grams per liter of trypsin and 0.53 millimoles per liter of EDTA from Invitrogen. The process of extracting total RNA, performing reverse transcription PCR, and conducting quantitative PCR Following the manufacturer's instructions, we extracted total RNA from isolated cells using RNAiso Plus reagent (Takara, Tokyo, Japan). The quality and concentration of the extracted RNA were evaluated using a Nanodrop spectrophotometer from Thermo Fisher Scientific. Commercial kits (Roche, Basel, Switzerland) were used for the reverse transcription of cDNA. In accordance with the manufacturer's instructions, we performed qPCR using the ABI Prism 7700 system from Applied Biosystems. To determine the relative levels of mRNA, we employed the 2-ΔΔCt method, with β-actin serving as an internal reference. After thoroughly analyzing each sample, we conducted three replicates and calculated the average results. All primers were obtained from PrimerBank ( https://pga.mgh.harvard.edu/primerbank/ ), and their sequences are listed in Table S1 . Immunohistochemistry and immunofluorescence of tissue sections The testicular sections were deparaffinized with xylene and rehydrated with graded ethanol for immunohistochemistry. Heat-induced antigen retrieval was then performed by immersing the samples in 0.01 mol/L sodium citrate buffer and heating them at 98°C for 18 minutes. After cooling and washing, the sections were incubated with 3% hydrogen peroxidase (Zsbio, Beijing, China) to block endogenous peroxidase activity. Following three rinses with PBS, the tissue sections were treated with 0.25% Triton X-100 (Sigma, St. Louis, MO, USA) for 15 minutes to increase their permeability. Nonspecific antigens were blocked by incubating the sections in 5% bovine serum albumin at room temperature for one hour. The sections were then incubated overnight at 4°C with the primary antibodies listed in Table S2 . After three rinses with PBS, the sections were treated with horseradish peroxidase-conjugated goat anti-rabbit secondary antibody and incubated at room temperature for one hour. Color development was achieved using the use of a 3,3’-diaminobenzidine chromogen kit (Dako, Glostrup, Denmark). The nuclei were stained with hematoxylin for 7 minutes at room temperature. For immunofluorescence, the primary antibody was incubated at 4°C for 16 hours, followed by chromogenic development using an Alexa Fluor-conjugated secondary antibody. The cell nuclei were counterstained with DAPI. Microscopy images of the testicular sections were captured and analyzed via a Zeiss microscope (Carl Zeiss, Jena, Germany). Protein extraction, Western blotting and co-immunoprecipitation Protein extraction, Western blotting and co-immunoprecipitation Testicular tissue and cells were lysed via RIPA buffer (Thermo Fisher Scientific, Waltham, MA, USA) on ice for 15 minutes. After centrifugation at 12,000 × g for 15 minutes, the supernatants were collected for total protein extraction and Western blot analysis. The overall protein concentration was determined using the BCA Kit according to the manufacturer's instructions. Each sample was analyzed using sodium dodecyl sulfate‒polyacrylamide gel electrophoresis and Western blot analysis, following a previously described method, with 20 micrograms of total protein. The antibodies used are listed in Table S2 . To visualize the protein bands, a chromogenic solution with enhanced chemiluminescence (Thermo Fisher Scientific) was used, and the resulting chemiluminescent signals were captured and analyzed via Fusion FX (Vilber Lourmat). For the co-immunoprecipitation assay, cell lysates were prepared using RIPA buffer supplemented with protease and phosphatase inhibitors. The protein concentration was determined using the Bradford assay. Equal amounts of protein were incubated with specific antibodies against the target proteins overnight at 4°C with gentle rotation. Subsequently, protein A/G magnetic beads were added and incubated for 2 hours at 4°C. The immune complexes were washed, eluted, and analyzed by Western blotting to detect the interacting proteins. All the samples were analyzed three times, and the average results were calculated. siRNA and plasmid transfection Zorin (Shanghai, China) designed and synthesized RGS14 siRNAs, while PLPP2 overexpression plasmids were prepared by SinoBiological (Beijing, China). The immortalized human SSCs were transfected with either 100 nmol/L of siRNAs or 2.5 µg of plasmids using Lipofectamine 3000 (Life Technologies) following the manufacturer's instructions. The cells were collected 48 hours post-transfection to extract protein and RNA for PCR and Western blot analysis. Cell viability assay A CCK-8 Kit (Dojindo, Kumamoto, Japan) was used to assess the viability of the SSCs, adhering strictly to the protocols stipulated by the manufacturer. Next, the cells were subjected to a three-hour incubation period in culture medium enriched with 100 mL/L CCK-8 reagents. The absorbance at 450 nm was subsequently determined using a microplate reader from Thermo Fisher Scientific. EdU incorporation assay An EdU labeling kit (RiboBio, Guangzhou, China) was used to detect DNA synthesis. Human SSCs were seeded into 96-well plates at a density of 5000 cells per well in culture medium supplemented with 50 µmol/L EdU. Following a 12 h incubation, the cells were washed with DMEM and fixed with 40 g/L PFA. Glycine (2 mg/ml) neutralized the cells, which were then permeabilized with 5 mL/L Triton X-100 for 10 minutes at room temperature. The Apollo staining reaction buffer was used to detect EdU, and the cell nuclei were stained with DAPI. Microscopy images of the EdU-positive cells were captured and analyzed using a Zeiss fluorescence microscope. A minimum of 500 cells were evaluated in each sample. Cell apoptosis assay Following 48 hours of transfection with siRNA, the cells were subjected to trypsin/EDTA treatment and subsequently rinsed twice with ice-cold PBS. A minimum of 10^6 cells were then resuspended in Annexin V binding buffer (BD Biosciences, San Jose, CA, USA) and incubated with 5 µL of APC-labeled Annexin V for 15 minutes at room temperature. The cells were subsequently treated with 10 µL of PI and incubated for an additional 10 minutes prior to the assay. The degree of cell apoptosis was assessed via a BD Biosciences C6 flow cytometer. An In Situ Cell Death Detection Kit (Roche) was used to examine the influence of plasmids on the apoptosis of the human SSC line. The cells were treated with proteinase K (20 mg/mL) for 15 minutes at room temperature and then incubated for one hour with dUTP labeling/terminal deoxynucleotidyl transferase (TdT) enzyme buffer in the absence of light. The cell nuclei were counterstained with DAPI. At least 500 cells per sample were analyzed via a Zeiss fluorescence microscope. RNA-seq Total RNA from cells was isolated via a TRIzol reagent kit (Invitrogen, Carlsbad, CA, USA). Personalbio (Shanghai, China) conducted RNA sequencing and preliminary analysis, with the detailed procedures outlined in our prior research[ 25 ]. The ClusterGVis R package ( https://github.com/junjunlab/ClusterGVis ) facilitated trend and Gene Ontology (GO) enrichment analyses, whereas the ClusterProfiler R package enabled Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, the plot1 cell R package was used to generate dot plots. Statistical analysis The R programming language employed the dplyr package for data analyses ( https://dplyr.tidyverse.org )[ 43 ]. Each experiment was replicated at least three times. The data are presented as the means ± standard deviations. Variances among groups were evaluated using a t test. A significance level of < 0.05 indicated statistical significance. Results Single-cell transcriptomic atlas of normal and NOA testes To investigate the developmental process of SSCs and their role in NOA, we reintegrated and analyzed scRNA data from three NOA cases (GSE149512)[ 35 ] and three normal testis samples (GSE119013)[ 36 ]. After eliminating low-quality cells, we categorized 29,686 cells from six testes into 13 distinct clusters through UMAP clustering. These clusters encompass various cell types: spermatogonial stem cell (SSC), Differentiating spermatogonia (Diffing.spg), leptotene spermatocytes (L), zygotene spermatocytes (Z), pachytene spermatocytes (P), diplotene spermatocytes (D), round spermatids (RS), elongating spermatids (ES), Sertoli cells (SC), Leydig cells (LC), peritubular myoid cells (PMC), epithelial cells (EC) and macrophages (Mø). The markers associated with these clusters are illustrated in Fig. 1 A and include ID4 , KIT , MEIOB , SPO11 , OVOL2 , SIRPG , SUN5 , PRM1 , WT1 , INSL3 , MYH11 , VWF , and CD68 . Figure 1 A depicts three concentric rings: the outermost ring symbolizes distinct clusters; the middle ring indicates the proportion of different groups within each cluster; and the inner ring represents the percentage of individual samples in each cluster. Upon quantifying germ cells in each sample, we observed a significant reduction in all germ cells within the NOA samples. Notably, the SSCs, which were our primary focus, also exhibited a substantial decrease (Fig. 1 B). We subsequently extracted the data pertaining to all the SSCs and conducted a more in-depth analysis to identify the DEGs and associated signaling pathways. Our findings indicated that, in NOA samples, 534 genes were significantly downregulated, whereas 272 genes were significantly upregulated (Fig. 1 C). The majority of the downregulated genes were predominantly involved in the AKT and MAPK signaling pathways (Fig. 1 D), which are known to play crucial roles in SSC proliferation and self-renewal. Within the group of downregulated genes, RGS14 , which displayed a notable reduction across all NOA samples, attracted particular attention. These findings suggest that RGS14 might play a critical role in the process of spermatogenesis (Fig. 1 E). A more thorough analysis revealed that RGS14 is predominantly localized in normal SSC samples (Fig. 1 F). By utilizing Monocle3, these SSCs can be classified into five distinct subgroups. Following this classification, we designated these subgroups sequentially from stage 1 to stage 5, according to their developmental progress (Fig. 1 G). Importantly, as development progresses, the expression level of RGS14 consistently decreases (Fig. 1 H). These results indicate that RGS14 is localized primarily in SSCs and that its expression is downregulated in NOA, potentially contributing to the dysregulation of spermatogenesis. The expression of RGS14 in normal and NOA testicular tissues To validate the results of the scRNA-seq analysis, we examined the distribution of RGS14 in OA (normal spermatogenesis) and NOA via immunohistochemistry. The number of RGS14-positive cells was significantly reduced in the NOA samples (Fig. 2 A and 2 B). The western blot data also revealed a significant reduction in the overall level of RGS14 protein in the NOA (Fig. 2 C and 2 D). Additionally, we analyzed the localization of RGS14 in normal spermatogonia via immunofluorescence. The results indicated that approximately 75% of the SSCs (GFRA1 positive) expressed RGS14, whereas only approximately 25% of the differentiated spermatogonia (KIT positive) expressed RGS14 (Fig. 2 E and 2 F). These findings are consistent with the bioinformatics results, which suggest that RGS14 is downregulated in NOA and predominantly expressed in spermatogonial stem cells. The effects of RGS14 on SSC proliferation and apoptosis To investigate the regulatory effects of RGS14 on human SSCs, a human SSC line was utilized. Using siRNA, we knocked down RGS14 in the SSC line and observed that RGS14-KD3 had the best inhibitory effect, as evidenced by both qPCR and Western blot assays (Fig. 3 A to 3 C). Following the knockdown of RGS14, we examined cell proliferation via a CCK8 assay and found that it was significantly reduced from the third to the fifth day after RGS14-KD3 transfection (Fig. 3 D). We also examined the expression of PLZF, GFRA1, and PCNA, which are proteins related to SSC self-renewal, and found that their overall levels were significantly reduced (Fig. 3 E and 3 F). The results of an EdU assay indicated that the reduction in RGS14 resulted in attenuated DNA synthesis (Fig. 3 G and 3 H). However, the TUNEL assay results revealed an increase in DNA breaks and a significant increase in the overall percentage of apoptotic cells (Fig. 3 I and 3 J ) . RGS14 is implicated in the regulation of MAPK signaling, a pathway that contributes to SSC proliferation and self-renewal[ 12 , 44 ]. Consequently, we investigated the phosphorylation status of MEK and ERK 1/2, which are pivotal molecules in the MAPK signaling cascade. The results revealed that RGS14 downregulation inhibited the phosphorylation of both ERK1/2 and MEK, suggesting that MAPK signaling was attenuated (Fig. 3 K and 3 L ) . These results suggest that knockdown of RGS14 leads to a significant reduction in proliferation and promotes apoptosis in SSC lines. Downstream target screening of RGS14 via RNA sequencing To elucidate the downstream targets of RGS14, we conducted RNA sequencing on cells 48 hours post transfection. After filtering out genes with low expression and unidentifiable sequences, we identified a total of 14109 genes. Among these genes, 365 genes were significantly downregulated, 38 were significantly upregulated, and 13706 genes exhibited no significant changes ( Table S3 ). The distribution of all genes is depicted in the volcano plot shown in Fig. 4 A. To confirm the RNA sequencing results, we randomly selected six DEGs for further validation via qPCR. The findings revealed that GABRR2 , MNS1 , and HMGN5 were significantly upregulated, whereas NBL1 , MFSD3 , and SNAI3 were significantly downregulated, which aligns with the RNA sequencing data (Fig. 4 B). On the basis of the gene expression data from each sample set, we performed expression trend analysis. All the genes were categorized into four clusters; cluster 2 primarily contained genes whose expression tended to increase, whereas clusters 3 and 4 predominantly consisted of genes whose expression tended to decrease. We conducted GO enrichment analysis on the genes within each cluster and discovered that processes such as RNA splicing were upregulated, whereas processes such as cytoplasmic translation and autophagy were significantly downregulated (Fig. 4 C). Additionally, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the significantly downregulated genes, revealing that pathways such as oxidative phosphorylation was significantly downregulated. This finding was consistent with the GO enrichment results from the trend analysis (Fig. 4 D). Furthermore, we screened certain genes potentially associated with SSC proliferation and apoptosis, including genes such as PLPP2 , SLC25A10 , and CD14 , and examined their expression in normal testes via scRNA-seq data. Notably, we found that PLPP2 , NBL1 , FTH1 , and CRIP2 were primarily localized in SSCs (Fig. 4 E). We subsequently confirmed that the genes localized to SSCs were significantly downregulated at both the mRNA and protein levels. The results indicated that PLPP2 was significantly downregulated at both the mRNA and protein levels (Fig. 4 F), whereas no significant changes in other genes at the protein level were detected (data not shown). These findings suggest that RGS14 knockdown leads to significant downregulation of genes such as PLPP2 and impacts signaling pathways such as oxidative phosphorylation. PLPP2 alleviates phenotypic defects caused by RGS14 knockdown To elucidate the role of PLPP2 in RGS14-mediated SSC proliferation and apoptosis, we conducted phenotypic rescue experiments. We engineered a plasmid for PLPP2 overexpression (PLPP2-OE) and validated its efficacy via western blot analysis. The data revealed that the PLPP2-OE plasmid significantly elevated PLPP2 protein expression post-transfection (Fig. 5 A and 5 B). We subsequently co-transfected both RGS14-KD3 and PLPP2-OE cells to assess cell proliferation and apoptosis. CCK8 assays revealed that PLPP2 overexpression enhanced cell proliferation on the fourth- and fifth-days post-transfection, whereas concurrent transfection of RGS14-KD3 and PLPP2-OE mitigated the decrease in cell proliferation induced by RGS14 knockdown (Fig. 5 C). The expression levels of proteins involved in SSC proliferation and self-renewal, including PLZF, GFRA1, and PCNA, were also restored upon PLPP2 overexpression (Fig. 5 D and 5 E). Comparable outcomes were observed in the EdU assays, where PLPP2 overexpression notably augmented cellular DNA synthesis and counteracted the phenotypic anomalies associated with RGS14 knockdown (Fig. 5 F and 5 G). Moreover, apoptosis detection via flow cytometry demonstrated that PLPP2 also reversed the changes in apoptosis triggered by RGS14 (Fig. 5 H and 5 I). Collectively, these findings suggest that PLPP2 overexpression ameliorates the phenotypic deficits induced by RGS14 knockdown, suggesting that PLPP2 is a downstream target of RGS14. RGS14 interacts with GNAI3 and affects SSC proliferation RGS14, characterized as a scaffold protein, orchestrates intracellular signaling pathways. Using the STRING, GeneMania, and HitPredict databases, we predicted potential interaction partners of RGS14 and identified GNAI3, GNAI1, and RAP1A as candidates through an intersection of the prediction results (Fig. 6 A). Subsequent analysis of the scRNA-seq landscape revealed robust expression of RGS14, GNAI3, and GNAI1 in SSCs, whereas RAP1A was virtually absent, diminishing its ability to interact with RGS14 in SSCs (Fig. 6 B). Co-immunoprecipitation assays confirmed significant interactions between RGS14 and GNAI3 (Fig. 6 C), with negligible evidence of interaction with GNAI1 (data not shown). The immunofluorescence results further demonstrated substantial colocalization of RGS14 and GNAI3 in the testes (Fig. 6 D and 6 E). Additionally, the knockdown of RGS14 coincided with the downregulation of GNAI3 expression (Fig. 6 F). We then examined the role of GNAI3 in RGS14-mediated SSC proliferation. The overexpression of GNAI3 in the SSC lines partially restored the protein expression of PLZF and PLPP2, which was diminished upon RGS14 knockdown (Fig. 6 G- 6 J). CCK8 assays also revealed that GNAI3 overexpression mitigated the decrease in cell proliferation triggered by RGS14 knockdown (Fig. 6 K). Collectively, these findings underscore GNAI3 as a molecular partner in RGS14-mediated regulation of SSC function. PLPP2 and GNAI3 expression was downregulated in NOA testes To explore the potential roles of PLPP2 and GNAI3 in NOA, we assessed their expression profiles in testes. In the scRNA-seq landscape, PLPP2 was primarily localized to SSCs, whereas GNAI3 exhibited a broader expression profile and was present in spermatogonia through early spermatocytes. Notably, both were downregulated in NOA testes (Fig. 7 A). The immunohistochemical results revealed a significant reduction in the number of PLPP2- and GNAI3-positive cells in the NOA, with a marked decrease in the mean optical density (Fig. 7 B and 7 C). Concurrently, Western blot analysis of total protein levels revealed a pronounced decrease in the protein expression of both PLPP2 and GNAI3 in NOA testes (Fig. 7 D and 7 E). These findings suggest that the significant reduction in PLPP2 and GNAI3 and their dysregulation in conjunction with RGS14 may be involved in the pathogenesis of NOA. Discussion NOA represents the most severe form of spermatogenesis disorder, affecting approximately 1% of the male population, primarily because of nongenetic factors[ 45 ]. The limited understanding of the etiology and progression of NOA has resulted in a scarcity of treatment options. SSCs are pivotal for spermatogenesis in adult males, as they initiate and sustain sperm production throughout life[ 46 , 47 ]. In mouse models, genes such as Plzf [ 18 ], Foxo1 [ 48 ], and Dot1l [ 49 ] have been identified as crucial regulators of SSC self-renewal and proliferation. Disruption of these genes leads to an inability to maintain SSCs, culminating in germ cell loss and a testicular phenotype analogous to human NOA. While no single SSC gene mutation directly linked to NOA has been identified, the results of mouse experiments suggest that dysfunction of numerous SSC genes can lead to Sertoli cell-only syndrome (SCOS), a severe manifestation of NOA[ 50 ]. These findings underscore the significant role of SSCs in the development of NOA. In our study, we analyzed single-cell transcriptional data from NOA and normal spermatogenesis testes. We found that a reduction in germ cell number occurred in almost all NOA samples, and further analysis of the differentially expressed genes from SSCs confirmed a significant reduction in RGS14. In fact, the number of spermatogonia was also drastically reduced, and our study did not explore spermatogonia or testicular somatic cell factors in NOA. In addition, many SSC genes, such as PEG3 and MYH10 , are downregulated in NOA, and many genes whose expression is upregulated remain to be further investigated. RGS14, a multifunctional scaffold protein that integrates the G protein and H-Ras/MAPK signaling pathways, is enriched in CA2 hippocampal neurons in the brain[ 44 ]. This is where most of the previous research on RGS14 originated. The hippocampus is important for spatial learning and memory; however, RGS14 appears to be a negative regulator that may inhibit synaptic plasticity through MAPK signaling[ 30 ]. RGS14 knockout (RGS14-KO) mice learn to navigate water mazes and locate underwater escape platforms faster, suggesting that the loss of RGS14 significantly improves the acquisition rate of spatial learning[ 33 ]. However, the results of these studies appear to differ from our data. Our data suggest that RGS14 is predominantly distributed in male germline stem cells, whereas CA2 hippocampal neurons are terminally differentiated[ 32 ]. Furthermore, RGS14 plays a negative regulatory role in hippocampal neurons[ 33 ], whereas it is significantly reduced in testes with dysgenic spermatogenesis, and its downregulation significantly inhibits SSC proliferation. Considering that RGS14 is a scaffolding protein, there may be differences in its intercalating proteins in stem cells and differentiated cells, leading to different roles of RGS14. Notably, RGS14 has been reported to interact with both GNAI1 and GNAI3[ 51 ]. However, our co-IP experiments revealed a significant interaction only with GNAI3. This discrepancy may arise from the low specificity of the antibodies used. We will subsequently investigate potential interactions via pull-down assays and the yeast two-hybrid system. The formation and development of SSCs is a complex process that involves multiple developmental events and signaling pathways. Although the underlying mechanisms are still unclear, SSC formation may involve several stages, including the migration of PGCs, the differentiation of PGCs into prospermatogonia (proSg), and the transformation of prospermatogonia into SSCs[ 11 ]. RGS14 has been reported to be expressed in zygotes and is required to complete the first mitotic division of the mouse embryo[ 52 ]. Our data suggest that in adult testes, RGS14 is predominantly expressed in SSCs. Whether RGS14 is expressed in PGCs and proSgs and influences the process of SSC formation at an earlier stage is not known. We will investigate this by analyzing data from embryonic testes and by constructing RGS14 knockout mice. Although we explored the downstream target genes of RGS14 via RNA-seq and confirmed the role of PLPP2 in RGS14-mediated SSC proliferation, whether other downregulated genes also play a role is unclear, and we do not know whether RGS14 is directly involved in the transcriptional regulation of PLPP2 or indirectly affects its level via other pathways. In addition, as RGS14 is a scaffolding molecule, we will study the reciprocal molecules of RGS14 in combination with protein immunoprecipitation and mass spectrometry experiments in the future to elucidate the detailed mechanism of its role. By performing scRNA-seq analysis and cellular experiments, we discovered that RGS14 is downregulated in patients with NOA, which impacts SSC proliferation. However, conclusive evidence linking the dysregulation of RGS14 to NOA is still lacking. Despite conducting whole-exome sequencing on numerous NOA patients, no pertinent mutation sites were identified. Given that RGS14 expression commences at the zygote stage and is linked to the embryo's first division, mutations in RGS14 could be lethal, which might explain why we failed to detect any deleterious mutations in RGS14. In future studies, we plan to expand our screening of NOA samples and consider epigenetic factors to further explore the correlation between RGS14 and the occurrence of NOA. Additionally, creating a mouse model with conditional knockout of RGS14 in the testes will be crucial for understanding the role of RGS14 in male fertility and spermatogenesis. Conclusion In our study, a systematic analysis of gene expression alterations in SSCs from NOA and normal testes was conducted through scRNA-seq. It was discovered that within SSCs, RGS14 forms a complex with GNAI3, which modulates the MAPK signaling pathway and the expression of PLPP2. This, in turn, affects cell viability and self-renewal. The dysregulation of these molecules may underlie the pathogenesis of NOA. Our findings elucidate the molecular mechanisms underlying the dysfunction of SSCs in NOA and may provide novel insights for the diagnosis and therapeutic strategies for this condition. Abbreviations NOA Non-obstructive azoospermia SSCs Spermatogonial stem cells RGS14 Regulator of G-protein signaling 14 GNAI3 G protein subunit alpha i3 PLPP2 Phospholipid phosphatase 2 MAPK Mitogen-activated protein kinase scRNA-seq Single-cell RNA sequencing siRNA Small interfering RNA qPCR Quantitative polymerase chain reaction CCK-8 Cell Counting Kit-8 EdU 5-ethynyl-2'-deoxyuridine TUNEL Terminal deoxynucleotidyl transferase dUTP nick end labeling PI Propidium iodide GDNF Glial cell line-derived neurotrophic factor GFRA1 GDNF family receptor alpha 1 PLZF Promyelocytic leukemia zinc finger protein mTORC1 Mammalian target of rapamycin complex 1 SALL4 Sal-like protein 4 FGF Fibroblast growth factor CSF1 Colony stimulating factor 1 AKT Protein kinase B Src Proto-oncogene tyrosine-protein kinase Src RBDs Ras/Rap-binding domains GPCRs G protein-coupled receptors Seurat A software package for single-cell genomics UMAP Uniform manifold approximation and projection GO Gene Ontology KEGG Kyoto Encyclopedia of Genes and Genomes PFA Paraformaldehyde DAPI 4',6-diamidino-2-phenylindole PBS Phosphate-buffered saline Declarations Ethics approval and consent to participate The ethics committee of CITIC-Xiangya approved this study (LL-SC-2021-025), and all participants provided signed informed consent. Consent for publication All the authors consent to publish this manuscript. Availability of data and materials The information produced by this research can be acquired from the author in question upon a reasonable inquiry. Competing interests The authors declare that they have no competing interests. Funding This study was supported by grants from the National Natural Science Foundation for Young Scholars of China (No.82201771), the Natural Science Foundation of Hunan Province (No. 2024JJ6083, 2023JJ30064, 2023JJ40068), the Health Research Project of Hunan Provincial Health Commission (No. W20243143, W20243010), the Natural Science Foundation of Changsha (No. kq2202491, kq1701016), the National Key Research and Development Program: Establishment of a Database for Genetic Retrieval of Early Pregnancy Fetal Ultrasound Abnormal Phenotypes and Development and Promotion of Consensus Guidelines (No. 2022YFC2703305), and the Science and Technology Innovation Project of Hunan Province (No. 2021SK53204). Author contributions DZ, AMD, ZHM and SSZ were responsible for the design and funding of the experiments. DZ and BL were responsible for the bioinformatics analysis, manuscript writing and molecular experiments. LJL, LP and XWL are responsible for data statistics and graphical processing. FZ was responsible for sample collection. All the authors reviewed the manuscript. Acknowledgments We would like to extend our gratitude to Professor Zuping He from the School of Medicine at Hunan Normal University for providing the human SSC lines. The website Home for Researchers (https://www.home-for-researchers.com) is acknowledged for its provision of imaging platforms. Additionally, we express our thanks to ProMab Biotechnologies, Inc., for supplying the antibody and molecular detection platforms. References Qiao J, Wang Y, Li X, Jiang F, Zhang Y, Ma J, et al. A Lancet Commission on 70 years of women's reproductive, maternal, newborn, child, and adolescent health in China. Lancet. 2021;397(10293):2497–536. Agarwal A, Baskaran S, Parekh N, Cho CL, Henkel R, Vij S, et al. Male infertility. Lancet. 2021;397(10271):319–33. Levine H, Jørgensen N, Martino-Andrade A, Mendiola J, Weksler-Derri D, Jolles M, et al. 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Additional Declarations No competing interests reported. Supplementary Files TableS1S2.Primersandantibodies.docx TableS3.RNAsequencingdata.csv Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5770052","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398432522,"identity":"79aae0b8-4c27-4057-bb01-98307dffb887","order_by":0,"name":"Dai Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBAC+xlAgodBQo5N/vABINMCxMMPGKFajPkl2BIYGBIkiNbCkCg5g8eAOC3M0s3HJN7UWCQY3O75+Jj3h4QcP88Bxg8fc3BrYZM5liY555hEnsGds5uNeRIkjCV7G5glZ27DrYVHIsdMmodNotjgQO42aaCWxA3nGdiYefFokQBr+QdUeSDnGXFaDEBaeNskEmfOyGGDaDnbQEhLWrLl3D5gIPMcMzackwb0S8/BZrx+sZ+RfPDGm291cmzszQ8fvLGxAYZY8sEPH/FowQYYG0hTPwpGwSgYBaMAAwAAvINJFiu/1lUAAAAASUVORK5CYII=","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":true,"prefix":"","firstName":"Dai","middleName":"","lastName":"Zhou","suffix":""},{"id":398432523,"identity":"af9e7f3d-d7cb-4df9-a602-27f9ffa1646e","order_by":1,"name":"Bang Liu","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Bang","middleName":"","lastName":"Liu","suffix":""},{"id":398432524,"identity":"fcb81fae-4a54-43dc-948d-989fa676ec9e","order_by":2,"name":"Lvjun Liu","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Lvjun","middleName":"","lastName":"Liu","suffix":""},{"id":398432525,"identity":"d623b126-7d39-400f-b040-54187a9cd012","order_by":3,"name":"Lin peng","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"peng","suffix":""},{"id":398432526,"identity":"e002accf-d8a8-488a-86be-8f7ecf006cd7","order_by":4,"name":"Xiaowen Liu","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Xiaowen","middleName":"","lastName":"Liu","suffix":""},{"id":398432527,"identity":"a6bc553c-b7bb-422c-83e2-379cb3d517be","order_by":5,"name":"Fang Zhu","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Zhu","suffix":""},{"id":398432529,"identity":"ea7ef5f0-14c2-4483-b215-ca1dc2a63b1e","order_by":6,"name":"Aimin Deng","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Aimin","middleName":"","lastName":"Deng","suffix":""},{"id":398432531,"identity":"79691b68-4bb8-4fbd-b576-6332177c0e97","order_by":7,"name":"Shusheng Zhang","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Shusheng","middleName":"","lastName":"Zhang","suffix":""},{"id":398432532,"identity":"50c5ba63-58c7-40e4-8369-0c47e7e7600b","order_by":8,"name":"Zenghui Mao","email":"","orcid":"","institution":"Changsha Hospital for Maternal \u0026 Child Health Care Affiliated to Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Zenghui","middleName":"","lastName":"Mao","suffix":""}],"badges":[],"createdAt":"2025-01-06 02:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5770052/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5770052/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73315667,"identity":"a95ac183-bdea-44db-ac76-055d28dd191f","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2129016,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle-cell transcriptome analysis of normal and NOA testicular samples. \u003c/strong\u003e(A) UMAP clustering of normal and NOA testicular cells. The 26,986 cells from six samples were divided into 13 clusters, each cluster was colored sequentially, and the markerused for cell identification is shown on the right side of the image. The outermost ring symbolizes distinct clusters; the middle ring indicates the proportion of different groups within each cluster; and the inner ring representsthe percentage of individual samples in each cluster. The groups and samples are shown on the left side of the image. (B) The bar graphs show the proportion of germ cells in each sample, including the following: SSC, Diffing.spg, L, Z, P, D, RS and ES. (C) Volcano plot demonstratingthe gene distribution of SSCs in NOA and normal testicular samples. The right side of the vertical dotted line represents significantly upregulatedgenes. The left side of the vertical dashed line represents significantly downregulatedgenes. (D) KEGG analysis of genes that were differentially expressed between theNOA and normal samples of SSCs. The numbers in the bar graph represent the counts enriched in this signaling pathway. (E) Violin plots demonstrating the expression of RGS14 in the SSCsof each sample. (F) Violin plot demonstrating the expression of RGS14 in normal testicular cells. (G) Reclustering of SSCs in the normal testis. The SSC was reclassified into 5 different stages, and the arrows represent the developmental direction of the SSCs. (H) Expression levels of RGS14 along the SSC developmental trajectory. SSC: spermatogonial stem cell, Diffing.spg: differentiating spermatogonia, L: leptotene spermatocyte, Z: zygotene spermatocyte, P: pachytene spermatocyte, D: diplotene spermatocyte, RS: round spermatid.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/6353d1422c021a7461d7030c.png"},{"id":73315662,"identity":"29026140-cf67-4739-af43-4c4f20ccce39","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2496242,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression and distribution of RGS14 in NOA and normal testicular tissues. \u003c/strong\u003e(A) Immunohistochemistry was used to detect the distribution of RGS14 in NOA and normal testes. The arrowsrepresent RGS14-positive cells. Scale bar, 100 μm. (B) Bar graph demonstrating the number of RGS14-positive cells in NOA seminiferous tubules and normal seminiferous tubules. RGS14-positive cells were significantly reduced in NOA testes. (C) Western blot analysis of the overall levels of RGS14 in NOA and normal testes. (D) Bar graph demonstrating the overall levels of RGS14 in NOA and normal testicular tissues. RGS14 protein levels were significantly reduced in NOA testes. (E) Immunofluorescence detection of RGS14 localization in spermatogonia subpopulations. The green signal is RGS14, the red signals are GFRA1 (SSC marker) and KIT (differentiated spermatogonia marker), and the blue signal is DAPI. Scale bar, 50 μm. (F) Dot plots showingthe percentage of RGS14 colocalized with GFRA1 and KIT. * represents \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/756fbc6ac7810e5bf0da9652.png"},{"id":73315664,"identity":"05a416b7-fd10-42ef-88dc-6989418f5135","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1635687,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRGS14 knockdown inhibits SSC proliferation and induces apoptosis.\u003c/strong\u003e(A) Bar graph showing the mRNA levels of RGS14 after RGS14 knockdown. (B) Western blot detection of the protein levels of RGS14 after RGS14 knockdown. (C) Bar graph showing the protein levels of RGS14 after RGS14 knockdown. (D) CCK8 was used to detect cell proliferation from day 1 to day 5 after RGS14-KD3 transfection. (E) Western blot analysis ofthe expression levels of SSC self-renewal-related proteins. These genes includePLZF, GFRA1 and PCNA. (F) Bar graph showing the protein levels of PLZF, GFRA1 and PCNA in E. (G) EdU was used to detect cellular DNA synthesis. EdU signals are shown in red, and DAPI signals are shownin blue. Scale bar, 20 μm. (H) Violin plot showing the proportion of EdU-positive cells in G. Each dot represents one count. (I) TUNEL staining was used to detect cell apoptosis. The TUNEL signal is shown in red,and DAPI is shown in blue. Scale bar, 20 μm. (J) Violin plot showing the proportion of TUNEL-positive cells in I. Each dot represents one count. (K) Western blotting was usedto detect the phosphorylation of MEK and ERK 1/2 proteins. (L) Bar graph showing the protein levels of phosphorylated MEK and ERK 1/2 in K. * represents \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. ** represents \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/251bc071a84133fd34df8716.png"},{"id":73316168,"identity":"2e9a9a77-cc67-411a-8867-ad856b322fcb","added_by":"auto","created_at":"2025-01-08 20:04:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1821592,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNA sequencing analysis of downstream genes and enrichedpathways of RGS14. \u003c/strong\u003e(A) Volcano plot showing the distribution of all genes identified by RNA sequencing. Genes significantly upregulatedafter RGS14 knockdown are shown in orange, whereasgenes significantly downregulatedare shown in blue. (B) qPCR was used to verify six randomly selected DEGs according tothe RNA sequencing results. (C) Heatmap showing the expression trends of all identified genes. The scaled gene expression levels are colored according to the Z score at the upper right. All genes were categorized into 4 clusters, and genes in cluster 2 were significantly upregulatedafter RGS14 knockdown, whereas genes in clusters 3 and 4 were significantly downregulated. The top 10 DEGs are labeled. Right: GO enrichmentof genes in each cluster; the top 5 terms are shown. (D) KEGG enrichment analysis of the top 100 significantly downregulatedgenes. The numbers in the bars represent the number of downregulatedgenes that were enriched with that KEGG term. (E) Dot plots showing the expression projections of selected genes in Figure 1A single-cell transcriptome. The scaled gene expression levels are colored according to the Z score at right. The size of the dot represents the percentage of cells expressing that gene. (F) The mRNA level of PLPP2 after RGS14 knockdown was detected by qPCR. (G) Western blot detection of the PLPP2 protein after RGS14 knockdown. (H) Bar graph showing the protein levels of PLPP2 after RGS14 knockdown. # Represents a significant upregulationcompared withthe NC group, and \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05. * Represents a significant downregulationcompared withthe NC group, and \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/32e37ae1d912786960d45749.png"},{"id":73315675,"identity":"cfa17673-0f5e-4f8c-b645-37365f90d14a","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1343136,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePLPP2 alleviates phenotypic changes caused by RGS14 knockdown in SSC lines.\u003c/strong\u003e (A) Western blot analysisof protein expression after PLPP2 overexpression. (B) Bar graph showing protein levels after PLPP2 overexpression. (C) CCK8 was used to detectcell proliferation in the NC, RGS14-KD3, RGS14-KD3+PLPP2-OE, and PLPP2-OE groups from 1-5 days after transfection. (D) Western blotting was performed to detect the expression of genes related to SSC proliferation and self-renewal in these 4 groups. These genes include PLZF, GFRA1 and PCNA. (E) Bar plot showing the level of each protein relative to the NC group in D. (F) EdU was used to detectDNA synthesis in these four groups. The red color represents EdU positivity, and the nuclei were counterstained with DAPI. Scale bar, 20 μm. (G) Bar plot demonstrating the proportion of EdU-positive cells relative to that in the NC group in F. (H) Flow cytometry was used to detect the proportion of apoptotic cells in the 4 groups. (I) Bar plots showing the proportion of apoptotic cells in each group relative to that in the NC group. These includeearly apoptosis, late apoptosis and total apoptosis. # Represents a significant upregulationcompared withthe NC group, and \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05. * Represents a significant downregulationcompared withthe NC group, and \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/0bf5427c18c23112180c802e.png"},{"id":73315665,"identity":"5600eb1d-0995-4897-8154-f2bfeed91189","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1245283,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrediction and validation of RGS14-interacting proteins in human SSCs. \u003c/strong\u003e(A)\u003cstrong\u003e \u003c/strong\u003eVenn diagram showing the results of the STRING, GeneMania and HitPredict databases in predicting RGS14-interacting proteins, with GNAI3, GNAI1 and RAP1A as the intersections of the predictions. (B) Violin plots demonstrating the expression of GNAI3, GNAI1, and RAPA1 in normal human testis scRNA-seq profiles. RGS14, GNAI3, and GNAI1 are robustly expressed in SSCs, whereas RAPA1 is expressed predominantly in somatic cells. (C) Co-IP verification of the interaction between RGS14 and GNAI3. Western blot analysis revealeda clear GNAI3 band after enrichment with an RGS14 antibody. A clearRGS14 band was also detected after enrichment with the anti-GNAI3 antibody. (D) Immunofluorescence detection of RGS14 and GNAI3 in normal testes. RGS14 (green) and GNAI3 (red) are abundantly colocalizedin cells near the seminiferous tubules. The whitearrows indicate co-expressedcells. Scalebar, 50 μm. (E) The dot plot showing the proportion of co-expressed cells in D. (F) Western blot analysis revealed downregulationof GNAI3 expression after RGS14 knockdown. (G) Western blot analysis ofprotein levels after GNAI3 overexpression. (H) The bar graph showsthe relative protein levels of GNAI3 in G. (I) Western blot analysis of the levels of PLZF and PLPP2 in the NC, RGS14-KD3 and RGS14-KD3+GNAI3-OE groups. Both PLZF and PLPP2 were significantly downregulatedupon RGS14 knockdown, whereas overexpression of GNAI3 alleviated the downregulationof protein levels caused by RGS14 deficiency. (J) The bar graph showsthe relative levels of PLPP2 and PLZF in I. (K) CCK8 assay for cell proliferation in all three groups. The overexpression of GNAI3 partially rescued the downregulationof cell proliferation caused by RGS14 knockdown. * indicates \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. KD: knockdown. OE: Overexpression. ns: not significant.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/2db7e65cedd2701ced453bf4.png"},{"id":73316171,"identity":"fe122987-ab0e-4b9b-82ab-a6296373e233","added_by":"auto","created_at":"2025-01-08 20:04:05","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":3073359,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePLPP2 and GNAI3 levels in normal and NOA testes.\u003c/strong\u003e(A) Distribution of PLPP2 and GNAI3 expression in human testicular scRNA-seq profiles. Both PLPP2 and GNAI3 were significantly downregulated in NOA testes. (B) Immunohistochemical detection of PLPP2 and GNAI3 expression in OA and NOA testes. The number of positive cells in NOA testes was significantly reduced. Scalebar, 50 μm. (C) Mean optical density analysis after PLPP2 and GNAI3 staining in B. Themean optical density was significantly lower in the NOA samples. (D) Western blot detection of PLPP2 and GNAI3 levels in OA and NOA testes. (E) Bar graphs showingthe relative levels of PLPP2 and GNAI3. The expressionof PIPPL2 and GNAI3 was significantly reduced in NOA testes. * indicates \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/5bd4b9abbd2fb0cdee66d5ad.png"},{"id":73317978,"identity":"38aff942-00f9-40b9-9222-c7df91dd7475","added_by":"auto","created_at":"2025-01-08 20:28:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14053752,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/dc4ffdc8-5015-488a-b136-9ab01381647c.pdf"},{"id":73315661,"identity":"70bf60b0-244b-4cb0-baf5-15de3caf0fa5","added_by":"auto","created_at":"2025-01-08 19:56:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":22730,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1S2.Primersandantibodies.docx","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/661926d63a05724a8fe3b96a.docx"},{"id":73316167,"identity":"3acfaa76-e709-4bdf-80bc-91888f2a8792","added_by":"auto","created_at":"2025-01-08 20:04:04","extension":"csv","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1084459,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.RNAsequencingdata.csv","url":"https://assets-eu.researchsquare.com/files/rs-5770052/v1/bfbbac0a98147c1ad15acff3.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"RGS14 binding to GNAI3 regulates human SSC proliferation and apoptosis through PLPP2, and abnormalities in these genes are associated with azoospermia","fulltext":[{"header":"Background","content":"\u003cp\u003eReproductive health is a fundamental right of human beings and an important component of social development. However, the infertility rate in China has been increasing annually due to environmental pollution, high levels of urban living pressure, delayed marriage and childbearing age, and other reasons. By 2020, the infertility rate had approached 18%, with approximately 50% of cases caused by male factors[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A sharp decline in sperm quantity and concentration, as well as genetic mutations leading to sperm developmental disorders, are important causes of infertility[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpermatogonial stem cells (SSCs) are the foundation for continuous sperm production and the maintenance of male fertility[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. SSCs possess the characteristics of self-maintenance, renewal, and differentiation[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Studying their developmental and differentiation mechanisms will provide important breakthroughs for clinically activating and utilizing SSCs to treat male infertility. The formation and development of mouse SSCs is a complex and precise process involving multiple developmental events and signaling pathways. During embryonic days E8.5\u0026ndash;10.5 in mice, primordial germ cells (PGCs) migrate to the gonadal ridge and form the testis with somatic cells. During this process, PGCs undergo rapid proliferation and differentiate into M-prospermatogonia (M-proSg) on day E12[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Subsequently, around embryonic day E15, M-proSg cells exit mitosis and arrest at the G0 phase, becoming T1-prospermatogonia (T1-proSg)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It is not until approximately 2 days after birth (P2) that T1-proSg resumes mitosis and transforms into actively dividing (P2-P3) T2-prospermatogonia (T2-proSg), which then (P4-P6) further develop into spermatogonia[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrent research on SSCs has focused mainly on the mechanisms of maintenance and self-renewal in adult mouse testes. The PI3K/AKT and Src pathways are currently identified as core signaling pathways involved in the process of SSC self-renewal[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Glial cell line-derived neurotrophic factor (GDNF) secreted by Sertoli cells can activate the PI3K/AKT and Src pathways through the receptors GFRA1 and c-Ret within SSCs[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], initiating a series of genes and transcription factors related to SSC maintenance and self-renewal, such as \u003cem\u003eEtv5\u003c/em\u003e, \u003cem\u003eBcl6b\u003c/em\u003e and \u003cem\u003eLhx1\u003c/em\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Fibroblast growth factor (FGF) secreted by Sertoli cells not only activates the Src pathway but also acts synergistically with colony stimulating factor 1 (CSF1) secreted by interstitial cells to regulate SSCs through cooperation with GDNF[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Additionally, promyelocytic leukemia zinc finger protein (PLZF) is currently recognized as a crucial transcription factor necessary for SSC maintenance and self-renewal, promoting SSC maintenance and self-renewal by relieving mTORC1 pathway inhibition of the GDNF receptors GFRA1 and c-Ret, whereas SALL4 can antagonize the function of PLZF[\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the aforementioned studies were all conducted in mice. The cell types and biochemical phenotypes of human spermatogonial stem cells are different from those of rodent stem cells[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, the molecular regulatory mechanisms governing the fate determination of human spermatogonial stem cells and rodent spermatogonial stem cells may differ. Several studies have investigated human SSC proliferation, self-renewal, and apoptosis. microRNA-1908-3p promotes SSC proliferation by degrading KLF2[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. FGF5 stimulates human SSC proliferation through the activation of AKT and ERK[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. We previously demonstrated that ASB9[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], TCF3[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], MAGEB2[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], SPOCD1[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and PTN[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] are specifically expressed in human SSCs and regulate their self-renewal, proliferation, and apoptosis. At present, the fate determination of human spermatogonial stem cells and the molecular mechanisms underlying spermatogenic disorders have not been fully elucidated.\u003c/p\u003e \u003cp\u003eRegulator of G-protein signaling 14 (RGS14) is a multifunctional protein that integrates the G protein and H-Ras signaling pathways[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It possesses an RGS domain that binds to active Gαi/o-GTP subunits, promoting GTP hydrolysis, and a G protein regulatory (GPR) motif that selectively binds inactive Gαi1/3-GDP subunits, forming a stable heterodimer at cellular membranes[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. RGS14 also contains two tandem Ras/Rap-binding domains (RBDs) that interact with H-Ras, preferentially binding activated H-Ras-GTP in live cells to increase H-Ras cellular activity[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This interaction is regulated by inactive Gαi1-GDP and G protein-coupled receptors (GPCRs), highlighting the role of RGS14 as a key regulator of signal transduction, particularly in hippocampal-based learning and memory[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, whether RGS14 plays a role in SSC fate determination and spermatogenesis remains unknown.\u003c/p\u003e \u003cp\u003eIn this study, we analyzed the scRNA-seq profiles of NOA and normal testes, revealing a significant reduction in SSCs in NOA and a marked downregulation of the RGS14 gene in these cells. Knockdown of RGS14 in a human SSC line notably inhibited cell proliferation and downregulated the expression of proteins associated with self-renewal while increasing apoptosis. RNA sequencing revealed a significant decrease in PLPP2 gene expression following RGS14 knockdown, and overexpression of PLPP2 mitigated the cellular phenotypic defects induced by RGS14 downregulation. Through database predictions and experiments such as protein immunoprecipitation, GNAI3 was confirmed to be a molecular partner in RGS14-mediated regulation of SSC function. Additionally, we observed significant downregulation of both PLPP2 and GNAI3 in NOA testes. These findings provide novel insights into the molecular mechanisms underlying SSC dysfunction in NOA and potential therapeutic targets for male infertility.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003eEthical Statement and Sample Collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The study was approved by the ethics committee of CITIC-Xiangya (LL-SC-2021-025), and all participants provided signed informed consent. Testicular tissues were collected from 15 patients aged 25\u0026ndash;46 years who underwent testicular biopsy, with approximately 25 mg of tissue from each patient. To eliminate blood cells, the samples were thoroughly rinsed with sterile PBS on at least three occasions. The samples were subsequently preserved in liquid nitrogen or treated with 4% PFA or Bouin's fixative solution.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003escRNA-seq analysis of normal and NOA testes\u003c/h2\u003e \u003cp\u003eSingle-cell sequencing data were analyzed primarily via the Seurat 4 R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/satijalab/Seurat\u003c/span\u003e\u003cspan address=\"https://github.com/satijalab/Seurat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The Read10x function was used to import the scRNA-seq datasets GSE149512[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] (3 NOA testicular samples) and GSE112013 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] (3 normal testicular samples) into R, generating the Seurat object. Gene expression data were then filtered, retaining cells with gene expression values ranging from 500\u0026ndash;7500 and less than 20% of genes related to mitochondria. All the mitochondrial and ribosomal genes were removed on the basis of their nomenclature. Duplicate entries were detected and eliminated via the DoubletFinder R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/chris-mcginnis-ucsf/DoubletFinder\u003c/span\u003e\u003cspan address=\"https://github.com/chris-mcginnis-ucsf/DoubletFinder\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The NormalizeData and FindVariableFeatures functions were applied to each Seurat object. All the Seurat objects were combined via the FindIntegrationAnchors and IntegrateData functions. Data clustering was performed after the default UMAP technique was used, and cell types were subsequently determined by evaluating the expression of cellular markers. The plot1 cell R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/HumphreysLab/plot1\u003c/span\u003e\u003cspan address=\"https://github.com/HumphreysLab/plot1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e cell) was used to plot graphs after identifying and clustering the cells[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Transcriptional data of SSCs were analyzed via the clusterProfiler R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/YuLab-SMU/clusterProfiler\u003c/span\u003e\u003cspan address=\"https://github.com/YuLab-SMU/clusterProfiler\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for differentially expressed genes and Gene Ontology (GO) analysis[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. To investigate the expression of RGS14 during SSC development, data from SSCs were collected, reclustered via Seurat, and then imported into the Monocle3 R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cole-trapnell-lab.github.io/monocle3/\u003c/span\u003e\u003cspan address=\"https://cole-trapnell-lab.github.io/monocle3/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to create developmental trajectories for SSCs[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. All the dot, line, and violin plots were created and modified via ggplot2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/tidyverse/ggplot2\u003c/span\u003e\u003cspan address=\"https://github.com/tidyverse/ggplot2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in R[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCulture of human SSC lines\u003c/h3\u003e\n\u003cp\u003eThe human SSC line was established by introducing the large T antigen into GPR125-positive undifferentiated spermatogonia from humans[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This human SSC line retains several characteristics and markers of primary SSCs, including GFRA1, RET, and PLZF, but does not express testicular endosomal cell markers such as SOX9. The immortalized human SSCs were cultured at 34\u0026deg;C with a 5% CO2 concentration in DMEM/F12 (Gibco, Carlsbad, CA, USA) supplemented with 10% FBS (Gibco). The cells were subcultured every 48 to 72 hours with 0.5 grams per liter of trypsin and 0.53 millimoles per liter of EDTA from Invitrogen.\u003c/p\u003e\n\u003ch3\u003eThe process of extracting total RNA, performing reverse transcription PCR, and conducting quantitative PCR\u003c/h3\u003e\n\u003cp\u003eFollowing the manufacturer's instructions, we extracted total RNA from isolated cells using RNAiso Plus reagent (Takara, Tokyo, Japan). The quality and concentration of the extracted RNA were evaluated using a Nanodrop spectrophotometer from Thermo Fisher Scientific. Commercial kits (Roche, Basel, Switzerland) were used for the reverse transcription of cDNA. In accordance with the manufacturer's instructions, we performed qPCR using the ABI Prism 7700 system from Applied Biosystems. To determine the relative levels of mRNA, we employed the 2-ΔΔCt method, with β-actin serving as an internal reference. After thoroughly analyzing each sample, we conducted three replicates and calculated the average results. All primers were obtained from PrimerBank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pga.mgh.harvard.edu/primerbank/\u003c/span\u003e\u003cspan address=\"https://pga.mgh.harvard.edu/primerbank/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and their sequences are listed in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry and immunofluorescence of tissue sections\u003c/h3\u003e\n\u003cp\u003eThe testicular sections were deparaffinized with xylene and rehydrated with graded ethanol for immunohistochemistry. Heat-induced antigen retrieval was then performed by immersing the samples in 0.01 mol/L sodium citrate buffer and heating them at 98\u0026deg;C for 18 minutes. After cooling and washing, the sections were incubated with 3% hydrogen peroxidase (Zsbio, Beijing, China) to block endogenous peroxidase activity. Following three rinses with PBS, the tissue sections were treated with 0.25% Triton X-100 (Sigma, St. Louis, MO, USA) for 15 minutes to increase their permeability. Nonspecific antigens were blocked by incubating the sections in 5% bovine serum albumin at room temperature for one hour. The sections were then incubated overnight at 4\u0026deg;C with the primary antibodies listed in \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e. After three rinses with PBS, the sections were treated with horseradish peroxidase-conjugated goat anti-rabbit secondary antibody and incubated at room temperature for one hour. Color development was achieved using the use of a 3,3\u0026rsquo;-diaminobenzidine chromogen kit (Dako, Glostrup, Denmark). The nuclei were stained with hematoxylin for 7 minutes at room temperature. For immunofluorescence, the primary antibody was incubated at 4\u0026deg;C for 16 hours, followed by chromogenic development using an Alexa Fluor-conjugated secondary antibody. The cell nuclei were counterstained with DAPI. Microscopy images of the testicular sections were captured and analyzed via a Zeiss microscope (Carl Zeiss, Jena, Germany).\u003c/p\u003e\n\u003ch3\u003eProtein extraction, Western blotting and co-immunoprecipitation\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eProtein extraction, Western blotting and co-immunoprecipitation\u003c/div\u003e \u003cp\u003eTesticular tissue and cells were lysed via RIPA buffer (Thermo Fisher Scientific, Waltham, MA, USA) on ice for 15 minutes. After centrifugation at 12,000 \u0026times; g for 15 minutes, the supernatants were collected for total protein extraction and Western blot analysis. The overall protein concentration was determined using the BCA Kit according to the manufacturer's instructions. Each sample was analyzed using sodium dodecyl sulfate‒polyacrylamide gel electrophoresis and Western blot analysis, following a previously described method, with 20 micrograms of total protein. The antibodies used are listed in \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e. To visualize the protein bands, a chromogenic solution with enhanced chemiluminescence (Thermo Fisher Scientific) was used, and the resulting chemiluminescent signals were captured and analyzed via Fusion FX (Vilber Lourmat). For the co-immunoprecipitation assay, cell lysates were prepared using RIPA buffer supplemented with protease and phosphatase inhibitors. The protein concentration was determined using the Bradford assay. Equal amounts of protein were incubated with specific antibodies against the target proteins overnight at 4\u0026deg;C with gentle rotation. Subsequently, protein A/G magnetic beads were added and incubated for 2 hours at 4\u0026deg;C. The immune complexes were washed, eluted, and analyzed by Western blotting to detect the interacting proteins. All the samples were analyzed three times, and the average results were calculated.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003esiRNA and plasmid transfection\u003c/h2\u003e \u003cp\u003eZorin (Shanghai, China) designed and synthesized RGS14 siRNAs, while PLPP2 overexpression plasmids were prepared by SinoBiological (Beijing, China). The immortalized human SSCs were transfected with either 100 nmol/L of siRNAs or 2.5 \u0026micro;g of plasmids using Lipofectamine 3000 (Life Technologies) following the manufacturer's instructions. The cells were collected 48 hours post-transfection to extract protein and RNA for PCR and Western blot analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell viability assay\u003c/h3\u003e\n\u003cp\u003eA CCK-8 Kit (Dojindo, Kumamoto, Japan) was used to assess the viability of the SSCs, adhering strictly to the protocols stipulated by the manufacturer. Next, the cells were subjected to a three-hour incubation period in culture medium enriched with 100 mL/L CCK-8 reagents. The absorbance at 450 nm was subsequently determined using a microplate reader from Thermo Fisher Scientific.\u003c/p\u003e\n\u003ch3\u003eEdU incorporation assay\u003c/h3\u003e\n\u003cp\u003eAn EdU labeling kit (RiboBio, Guangzhou, China) was used to detect DNA synthesis. Human SSCs were seeded into 96-well plates at a density of 5000 cells per well in culture medium supplemented with 50 \u0026micro;mol/L EdU. Following a 12 h incubation, the cells were washed with DMEM and fixed with 40 g/L PFA. Glycine (2 mg/ml) neutralized the cells, which were then permeabilized with 5 mL/L Triton X-100 for 10 minutes at room temperature. The Apollo staining reaction buffer was used to detect EdU, and the cell nuclei were stained with DAPI. Microscopy images of the EdU-positive cells were captured and analyzed using a Zeiss fluorescence microscope. A minimum of 500 cells were evaluated in each sample.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell apoptosis assay\u003c/h2\u003e \u003cp\u003eFollowing 48 hours of transfection with siRNA, the cells were subjected to trypsin/EDTA treatment and subsequently rinsed twice with ice-cold PBS. A minimum of 10^6 cells were then resuspended in Annexin V binding buffer (BD Biosciences, San Jose, CA, USA) and incubated with 5 \u0026micro;L of APC-labeled Annexin V for 15 minutes at room temperature. The cells were subsequently treated with 10 \u0026micro;L of PI and incubated for an additional 10 minutes prior to the assay. The degree of cell apoptosis was assessed via a BD Biosciences C6 flow cytometer.\u003c/p\u003e \u003cp\u003eAn In Situ Cell Death Detection Kit (Roche) was used to examine the influence of plasmids on the apoptosis of the human SSC line. The cells were treated with proteinase K (20 mg/mL) for 15 minutes at room temperature and then incubated for one hour with dUTP labeling/terminal deoxynucleotidyl transferase (TdT) enzyme buffer in the absence of light. The cell nuclei were counterstained with DAPI. At least 500 cells per sample were analyzed via a Zeiss fluorescence microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRNA-seq\u003c/h2\u003e \u003cp\u003eTotal RNA from cells was isolated via a TRIzol reagent kit (Invitrogen, Carlsbad, CA, USA). Personalbio (Shanghai, China) conducted RNA sequencing and preliminary analysis, with the detailed procedures outlined in our prior research[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The ClusterGVis R package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/junjunlab/ClusterGVis\u003c/span\u003e\u003cspan address=\"https://github.com/junjunlab/ClusterGVis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) facilitated trend and Gene Ontology (GO) enrichment analyses, whereas the ClusterProfiler R package enabled Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, the plot1 cell R package was used to generate dot plots.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe R programming language employed the dplyr package for data analyses (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dplyr.tidyverse.org\u003c/span\u003e\u003cspan address=\"https://dplyr.tidyverse.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Each experiment was replicated at least three times. The data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations. Variances among groups were evaluated using a \u003cem\u003et\u003c/em\u003e test. A significance level of \u0026lt;\u0026thinsp;0.05 indicated statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSingle-cell transcriptomic atlas of normal and NOA testes\u003c/h2\u003e \u003cp\u003eTo investigate the developmental process of SSCs and their role in NOA, we reintegrated and analyzed scRNA data from three NOA cases (GSE149512)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and three normal testis samples (GSE119013)[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. After eliminating low-quality cells, we categorized 29,686 cells from six testes into 13 distinct clusters through UMAP clustering. These clusters encompass various cell types: spermatogonial stem cell (SSC), Differentiating spermatogonia (Diffing.spg), leptotene spermatocytes (L), zygotene spermatocytes (Z), pachytene spermatocytes (P), diplotene spermatocytes (D), round spermatids (RS), elongating spermatids (ES), Sertoli cells (SC), Leydig cells (LC), peritubular myoid cells (PMC), epithelial cells (EC) and macrophages (M\u0026oslash;). The markers associated with these clusters are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and include \u003cem\u003eID4\u003c/em\u003e, \u003cem\u003eKIT\u003c/em\u003e, \u003cem\u003eMEIOB\u003c/em\u003e, \u003cem\u003eSPO11\u003c/em\u003e, \u003cem\u003eOVOL2\u003c/em\u003e, \u003cem\u003eSIRPG\u003c/em\u003e, \u003cem\u003eSUN5\u003c/em\u003e, \u003cem\u003ePRM1\u003c/em\u003e, \u003cem\u003eWT1\u003c/em\u003e, \u003cem\u003eINSL3\u003c/em\u003e, \u003cem\u003eMYH11\u003c/em\u003e, \u003cem\u003eVWF\u003c/em\u003e, and \u003cem\u003eCD68\u003c/em\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA depicts three concentric rings: the outermost ring symbolizes distinct clusters; the middle ring indicates the proportion of different groups within each cluster; and the inner ring represents the percentage of individual samples in each cluster. Upon quantifying germ cells in each sample, we observed a significant reduction in all germ cells within the NOA samples. Notably, the SSCs, which were our primary focus, also exhibited a substantial decrease (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). We subsequently extracted the data pertaining to all the SSCs and conducted a more in-depth analysis to identify the DEGs and associated signaling pathways. Our findings indicated that, in NOA samples, 534 genes were significantly downregulated, whereas 272 genes were significantly upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). The majority of the downregulated genes were predominantly involved in the AKT and MAPK signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), which are known to play crucial roles in SSC proliferation and self-renewal. Within the group of downregulated genes, \u003cem\u003eRGS14\u003c/em\u003e, which displayed a notable reduction across all NOA samples, attracted particular attention. These findings suggest that RGS14 might play a critical role in the process of spermatogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). A more thorough analysis revealed that \u003cem\u003eRGS14\u003c/em\u003e is predominantly localized in normal SSC samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). By utilizing Monocle3, these SSCs can be classified into five distinct subgroups. Following this classification, we designated these subgroups sequentially from stage 1 to stage 5, according to their developmental progress (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). Importantly, as development progresses, the expression level of \u003cem\u003eRGS14\u003c/em\u003e consistently decreases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). These results indicate that \u003cem\u003eRGS14\u003c/em\u003e is localized primarily in SSCs and that its expression is downregulated in NOA, potentially contributing to the dysregulation of spermatogenesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eThe expression of RGS14 in normal and NOA testicular tissues\u003c/h2\u003e \u003cp\u003eTo validate the results of the scRNA-seq analysis, we examined the distribution of RGS14 in OA (normal spermatogenesis) and NOA via immunohistochemistry. The number of RGS14-positive cells was significantly reduced in the NOA samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The western blot data also revealed a significant reduction in the overall level of RGS14 protein in the NOA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Additionally, we analyzed the localization of RGS14 in normal spermatogonia via immunofluorescence. The results indicated that approximately 75% of the SSCs (GFRA1 positive) expressed RGS14, whereas only approximately 25% of the differentiated spermatogonia (KIT positive) expressed RGS14 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). These findings are consistent with the bioinformatics results, which suggest that RGS14 is downregulated in NOA and predominantly expressed in spermatogonial stem cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eThe effects of RGS14 on SSC proliferation and apoptosis\u003c/h2\u003e \u003cp\u003eTo investigate the regulatory effects of RGS14 on human SSCs, a human SSC line was utilized. Using siRNA, we knocked down RGS14 in the SSC line and observed that RGS14-KD3 had the best inhibitory effect, as evidenced by both qPCR and Western blot assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA to \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Following the knockdown of RGS14, we examined cell proliferation via a CCK8 assay and found that it was significantly reduced from the third to the fifth day after RGS14-KD3 transfection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). We also examined the expression of PLZF, GFRA1, and PCNA, which are proteins related to SSC self-renewal, and found that their overall levels were significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). The results of an EdU assay indicated that the reduction in RGS14 resulted in attenuated DNA synthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). However, the TUNEL assay results revealed an increase in DNA breaks and a significant increase in the overall percentage of apoptotic cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ\u003cb\u003e)\u003c/b\u003e. RGS14 is implicated in the regulation of MAPK signaling, a pathway that contributes to SSC proliferation and self-renewal[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Consequently, we investigated the phosphorylation status of MEK and ERK 1/2, which are pivotal molecules in the MAPK signaling cascade. The results revealed that RGS14 downregulation inhibited the phosphorylation of both ERK1/2 and MEK, suggesting that MAPK signaling was attenuated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eK and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL\u003cb\u003e)\u003c/b\u003e. These results suggest that knockdown of RGS14 leads to a significant reduction in proliferation and promotes apoptosis in SSC lines.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDownstream target screening of RGS14 via RNA sequencing\u003c/h2\u003e \u003cp\u003eTo elucidate the downstream targets of RGS14, we conducted RNA sequencing on cells 48 hours post transfection. After filtering out genes with low expression and unidentifiable sequences, we identified a total of 14109 genes. Among these genes, 365 genes were significantly downregulated, 38 were significantly upregulated, and 13706 genes exhibited no significant changes (\u003cb\u003eTable S3\u003c/b\u003e). The distribution of all genes is depicted in the volcano plot shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA. To confirm the RNA sequencing results, we randomly selected six DEGs for further validation via qPCR. The findings revealed that \u003cem\u003eGABRR2\u003c/em\u003e, \u003cem\u003eMNS1\u003c/em\u003e, and \u003cem\u003eHMGN5\u003c/em\u003e were significantly upregulated, whereas \u003cem\u003eNBL1\u003c/em\u003e, \u003cem\u003eMFSD3\u003c/em\u003e, and \u003cem\u003eSNAI3\u003c/em\u003e were significantly downregulated, which aligns with the RNA sequencing data (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). On the basis of the gene expression data from each sample set, we performed expression trend analysis. All the genes were categorized into four clusters; cluster 2 primarily contained genes whose expression tended to increase, whereas clusters 3 and 4 predominantly consisted of genes whose expression tended to decrease. We conducted GO enrichment analysis on the genes within each cluster and discovered that processes such as RNA splicing were upregulated, whereas processes such as cytoplasmic translation and autophagy were significantly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Additionally, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the significantly downregulated genes, revealing that pathways such as oxidative phosphorylation was significantly downregulated. This finding was consistent with the GO enrichment results from the trend analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Furthermore, we screened certain genes potentially associated with SSC proliferation and apoptosis, including genes such as \u003cem\u003ePLPP2\u003c/em\u003e, \u003cem\u003eSLC25A10\u003c/em\u003e, and \u003cem\u003eCD14\u003c/em\u003e, and examined their expression in normal testes via scRNA-seq data. Notably, we found that \u003cem\u003ePLPP2\u003c/em\u003e, \u003cem\u003eNBL1\u003c/em\u003e, \u003cem\u003eFTH1\u003c/em\u003e, and \u003cem\u003eCRIP2\u003c/em\u003e were primarily localized in SSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). We subsequently confirmed that the genes localized to SSCs were significantly downregulated at both the mRNA and protein levels. The results indicated that PLPP2 was significantly downregulated at both the mRNA and protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), whereas no significant changes in other genes at the protein level were detected (data not shown). These findings suggest that RGS14 knockdown leads to significant downregulation of genes such as \u003cem\u003ePLPP2\u003c/em\u003e and impacts signaling pathways such as oxidative phosphorylation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePLPP2 alleviates phenotypic defects caused by RGS14 knockdown\u003c/h2\u003e \u003cp\u003eTo elucidate the role of PLPP2 in RGS14-mediated SSC proliferation and apoptosis, we conducted phenotypic rescue experiments. We engineered a plasmid for PLPP2 overexpression (PLPP2-OE) and validated its efficacy via western blot analysis. The data revealed that the PLPP2-OE plasmid significantly elevated PLPP2 protein expression post-transfection (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We subsequently co-transfected both RGS14-KD3 and PLPP2-OE cells to assess cell proliferation and apoptosis. CCK8 assays revealed that PLPP2 overexpression enhanced cell proliferation on the fourth- and fifth-days post-transfection, whereas concurrent transfection of RGS14-KD3 and PLPP2-OE mitigated the decrease in cell proliferation induced by RGS14 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The expression levels of proteins involved in SSC proliferation and self-renewal, including PLZF, GFRA1, and PCNA, were also restored upon PLPP2 overexpression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Comparable outcomes were observed in the EdU assays, where PLPP2 overexpression notably augmented cellular DNA synthesis and counteracted the phenotypic anomalies associated with RGS14 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Moreover, apoptosis detection via flow cytometry demonstrated that PLPP2 also reversed the changes in apoptosis triggered by RGS14 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). Collectively, these findings suggest that PLPP2 overexpression ameliorates the phenotypic deficits induced by RGS14 knockdown, suggesting that PLPP2 is a downstream target of RGS14.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eRGS14 interacts with GNAI3 and affects SSC proliferation\u003c/h2\u003e \u003cp\u003eRGS14, characterized as a scaffold protein, orchestrates intracellular signaling pathways. Using the STRING, GeneMania, and HitPredict databases, we predicted potential interaction partners of RGS14 and identified GNAI3, GNAI1, and RAP1A as candidates through an intersection of the prediction results (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Subsequent analysis of the scRNA-seq landscape revealed robust expression of RGS14, GNAI3, and GNAI1 in SSCs, whereas RAP1A was virtually absent, diminishing its ability to interact with RGS14 in SSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Co-immunoprecipitation assays confirmed significant interactions between RGS14 and GNAI3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), with negligible evidence of interaction with GNAI1 (data not shown). The immunofluorescence results further demonstrated substantial colocalization of RGS14 and GNAI3 in the testes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Additionally, the knockdown of RGS14 coincided with the downregulation of GNAI3 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). We then examined the role of GNAI3 in RGS14-mediated SSC proliferation. The overexpression of GNAI3 in the SSC lines partially restored the protein expression of PLZF and PLPP2, which was diminished upon RGS14 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). CCK8 assays also revealed that GNAI3 overexpression mitigated the decrease in cell proliferation triggered by RGS14 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK). Collectively, these findings underscore GNAI3 as a molecular partner in RGS14-mediated regulation of SSC function.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePLPP2 and GNAI3 expression was downregulated in NOA testes\u003c/h2\u003e \u003cp\u003eTo explore the potential roles of PLPP2 and GNAI3 in NOA, we assessed their expression profiles in testes. In the scRNA-seq landscape, PLPP2 was primarily localized to SSCs, whereas GNAI3 exhibited a broader expression profile and was present in spermatogonia through early spermatocytes. Notably, both were downregulated in NOA testes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). The immunohistochemical results revealed a significant reduction in the number of PLPP2- and GNAI3-positive cells in the NOA, with a marked decrease in the mean optical density (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Concurrently, Western blot analysis of total protein levels revealed a pronounced decrease in the protein expression of both PLPP2 and GNAI3 in NOA testes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). These findings suggest that the significant reduction in PLPP2 and GNAI3 and their dysregulation in conjunction with RGS14 may be involved in the pathogenesis of NOA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNOA represents the most severe form of spermatogenesis disorder, affecting approximately 1% of the male population, primarily because of nongenetic factors[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The limited understanding of the etiology and progression of NOA has resulted in a scarcity of treatment options. SSCs are pivotal for spermatogenesis in adult males, as they initiate and sustain sperm production throughout life[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In mouse models, genes such as \u003cem\u003ePlzf\u003c/em\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], \u003cem\u003eFoxo1\u003c/em\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and \u003cem\u003eDot1l\u003c/em\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] have been identified as crucial regulators of SSC self-renewal and proliferation. Disruption of these genes leads to an inability to maintain SSCs, culminating in germ cell loss and a testicular phenotype analogous to human NOA. While no single SSC gene mutation directly linked to NOA has been identified, the results of mouse experiments suggest that dysfunction of numerous SSC genes can lead to Sertoli cell-only syndrome (SCOS), a severe manifestation of NOA[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These findings underscore the significant role of SSCs in the development of NOA.\u003c/p\u003e \u003cp\u003eIn our study, we analyzed single-cell transcriptional data from NOA and normal spermatogenesis testes. We found that a reduction in germ cell number occurred in almost all NOA samples, and further analysis of the differentially expressed genes from SSCs confirmed a significant reduction in RGS14. In fact, the number of spermatogonia was also drastically reduced, and our study did not explore spermatogonia or testicular somatic cell factors in NOA. In addition, many SSC genes, such as \u003cem\u003ePEG3\u003c/em\u003e and \u003cem\u003eMYH10\u003c/em\u003e, are downregulated in NOA, and many genes whose expression is upregulated remain to be further investigated.\u003c/p\u003e \u003cp\u003eRGS14, a multifunctional scaffold protein that integrates the G protein and H-Ras/MAPK signaling pathways, is enriched in CA2 hippocampal neurons in the brain[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This is where most of the previous research on RGS14 originated. The hippocampus is important for spatial learning and memory; however, RGS14 appears to be a negative regulator that may inhibit synaptic plasticity through MAPK signaling[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. RGS14 knockout (RGS14-KO) mice learn to navigate water mazes and locate underwater escape platforms faster, suggesting that the loss of RGS14 significantly improves the acquisition rate of spatial learning[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, the results of these studies appear to differ from our data. Our data suggest that RGS14 is predominantly distributed in male germline stem cells, whereas CA2 hippocampal neurons are terminally differentiated[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, RGS14 plays a negative regulatory role in hippocampal neurons[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], whereas it is significantly reduced in testes with dysgenic spermatogenesis, and its downregulation significantly inhibits SSC proliferation. Considering that RGS14 is a scaffolding protein, there may be differences in its intercalating proteins in stem cells and differentiated cells, leading to different roles of RGS14. Notably, RGS14 has been reported to interact with both GNAI1 and GNAI3[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. However, our co-IP experiments revealed a significant interaction only with GNAI3. This discrepancy may arise from the low specificity of the antibodies used. We will subsequently investigate potential interactions via pull-down assays and the yeast two-hybrid system.\u003c/p\u003e \u003cp\u003eThe formation and development of SSCs is a complex process that involves multiple developmental events and signaling pathways. Although the underlying mechanisms are still unclear, SSC formation may involve several stages, including the migration of PGCs, the differentiation of PGCs into prospermatogonia (proSg), and the transformation of prospermatogonia into SSCs[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. RGS14 has been reported to be expressed in zygotes and is required to complete the first mitotic division of the mouse embryo[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Our data suggest that in adult testes, RGS14 is predominantly expressed in SSCs. Whether RGS14 is expressed in PGCs and proSgs and influences the process of SSC formation at an earlier stage is not known. We will investigate this by analyzing data from embryonic testes and by constructing RGS14 knockout mice. Although we explored the downstream target genes of RGS14 via RNA-seq and confirmed the role of \u003cem\u003ePLPP2\u003c/em\u003e in RGS14-mediated SSC proliferation, whether other downregulated genes also play a role is unclear, and we do not know whether RGS14 is directly involved in the transcriptional regulation of \u003cem\u003ePLPP2\u003c/em\u003e or indirectly affects its level via other pathways. In addition, as RGS14 is a scaffolding molecule, we will study the reciprocal molecules of RGS14 in combination with protein immunoprecipitation and mass spectrometry experiments in the future to elucidate the detailed mechanism of its role.\u003c/p\u003e \u003cp\u003eBy performing scRNA-seq analysis and cellular experiments, we discovered that RGS14 is downregulated in patients with NOA, which impacts SSC proliferation. However, conclusive evidence linking the dysregulation of RGS14 to NOA is still lacking. Despite conducting whole-exome sequencing on numerous NOA patients, no pertinent mutation sites were identified. Given that RGS14 expression commences at the zygote stage and is linked to the embryo's first division, mutations in RGS14 could be lethal, which might explain why we failed to detect any deleterious mutations in RGS14. In future studies, we plan to expand our screening of NOA samples and consider epigenetic factors to further explore the correlation between RGS14 and the occurrence of NOA. Additionally, creating a mouse model with conditional knockout of RGS14 in the testes will be crucial for understanding the role of RGS14 in male fertility and spermatogenesis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn our study, a systematic analysis of gene expression alterations in SSCs from NOA and normal testes was conducted through scRNA-seq.\u0026nbsp;It was discovered that within SSCs, RGS14 forms a complex with GNAI3, which modulates the MAPK signaling pathway and the expression of PLPP2. This, in turn, affects cell viability and self-renewal. The dysregulation of these molecules may underlie the pathogenesis of NOA. Our findings elucidate the molecular mechanisms underlying the dysfunction of SSCs in NOA and may provide novel insights for the diagnosis and therapeutic strategies for this condition.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNOA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-obstructive azoospermia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSSCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSpermatogonial stem cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRGS14\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRegulator of G-protein signaling 14\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGNAI3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eG protein subunit alpha i3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLPP2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhospholipid phosphatase 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAPK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMitogen-activated protein kinase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003escRNA-seq\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSingle-cell RNA sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003esiRNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSmall interfering RNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqPCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuantitative polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCK-8\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCell Counting Kit-8\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEdU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-ethynyl-2'-deoxyuridine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTUNEL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTerminal deoxynucleotidyl transferase dUTP nick end labeling\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePropidium iodide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlial cell line-derived neurotrophic factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGFRA1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGDNF family receptor alpha 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLZF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePromyelocytic leukemia zinc finger protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emTORC1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMammalian target of rapamycin complex 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSALL4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSal-like protein 4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFGF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibroblast growth factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSF1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eColony stimulating factor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein kinase B\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSrc\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProto-oncogene tyrosine-protein kinase Src\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRBDs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRas/Rap-binding domains\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGPCRs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eG protein-coupled receptors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSeurat\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eA software package for single-cell genomics\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUMAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUniform manifold approximation and projection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eParaformaldehyde\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDAPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e4',6-diamidino-2-phenylindole\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethics committee of CITIC-Xiangya approved this study (LL-SC-2021-025), and all participants provided signed informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors consent to publish this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe information produced by this research can be acquired from the author in question upon a reasonable inquiry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the National Natural Science Foundation for Young Scholars of China (No.82201771), the Natural Science Foundation of Hunan Province (No. 2024JJ6083, 2023JJ30064, 2023JJ40068), the Health Research Project of Hunan Provincial Health Commission (No. W20243143, W20243010), the Natural Science Foundation of Changsha (No. kq2202491, kq1701016), the National Key Research and Development Program: Establishment of a Database for Genetic Retrieval of Early Pregnancy Fetal Ultrasound Abnormal Phenotypes and Development and Promotion of Consensus Guidelines (No. 2022YFC2703305), and the Science and Technology Innovation Project of Hunan Province (No. 2021SK53204).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDZ, AMD, ZHM and SSZ\u0026nbsp;were responsible for the design and funding of the experiments. DZ and BL were responsible for the bioinformatics analysis, manuscript writing and molecular experiments. LJL, LP and XWL are responsible for data statistics and graphical processing. FZ was responsible for sample collection.\u0026nbsp;All\u0026nbsp;the\u0026nbsp;authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our gratitude to Professor Zuping He from the School of Medicine at Hunan Normal University for providing the human SSC lines. The website Home for Researchers (https://www.home-for-researchers.com) is acknowledged for its provision of imaging platforms. Additionally, we express our thanks to ProMab Biotechnologies, Inc., for supplying the antibody and molecular detection platforms.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQiao J, Wang Y, Li X, Jiang F, Zhang Y, Ma J, et al. A Lancet Commission on 70 years of women's reproductive, maternal, newborn, child, and adolescent health in China. Lancet. 2021;397(10293):2497\u0026ndash;536.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgarwal A, Baskaran S, Parekh N, Cho CL, Henkel R, Vij S, et al. Male infertility. Lancet. 2021;397(10271):319\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevine H, J\u0026oslash;rgensen N, Martino-Andrade A, Mendiola J, Weksler-Derri D, Jolles M, et al. Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. Hum Reprod Update. 2023;29(2):157\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirtanen HE, J\u0026oslash;rgensen N, Toppari J. Semen quality in the 21(st) century. Nat reviews Urol. 2017;14(2):120\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Persio S, Neuhaus N. 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Dev Cell. 2004;7(5):763\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"RGS14, GNAI3, PLPP2, spermatogonial stem cells, NOA, proliferation","lastPublishedDoi":"10.21203/rs.3.rs-5770052/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5770052/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNon-obstructive azoospermia (NOA) is a severe form of male infertility characterized by the absence of sperm in the ejaculate due to impaired spermatogenesis. Spermatogonial stem cells (SSCs) play a crucial role in maintaining male fertility by ensuring continuous sperm production. However, the molecular mechanisms regulating SSC fate and their involvement in NOA remain largely unknown.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn this study, we utilized single-cell RNA sequencing to analyze gene expression profiles in normal and NOA testes, revealing a significant downregulation of RGS14 in SSCs of NOA patients. We found that RGS14 interacts with GNAI3 and modulates SSC proliferation and apoptosis by regulating the expression of PLPP2 and the MAPK signaling pathway. Knockdown of RGS14 significantly inhibited SSC proliferation and increased apoptosis, effects that were partially rescued by overexpression of PLPP2. Additionally, both PLPP2 and GNAI3 were found to be significantly downregulated in NOA patients, correlating with the expression pattern of RGS14.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings provide novel insights into the molecular mechanisms underlying SSC dysfunction in NOA. The dysregulation of RGS14, GNAI3, and PLPP2 may contribute to the pathogenesis of NOA. These results not only elucidate the role of RGS14 in SSC fate determination but also identify potential therapeutic targets for male infertility.\u003c/p\u003e","manuscriptTitle":"RGS14 binding to GNAI3 regulates human SSC proliferation and apoptosis through PLPP2, and abnormalities in these genes are associated with azoospermia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-08 19:55:59","doi":"10.21203/rs.3.rs-5770052/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"908eca22-ef11-455f-8484-c3ebc7fb149a","owner":[],"postedDate":"January 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-08T19:56:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-08 19:55:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5770052","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5770052","identity":"rs-5770052","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}