BackgroundIn the male germline, neonatal prospermatogonia give rise to spermatogonia, which include stem cell population (undifferentiated spermatogonia) that supports continuous spermatogenesis in adults. Although the levels of DNA methyltransferases change dynamically in the neonatal and early postnatal male germ cells, detailed genome-wide DNA methylation profiles of these cells during the stem cell formation and differentiation have not been reported.ResultsTo understand the regulation of spermatogonial stem cell formation and differentiation, we examined the DNA methylation and gene expression dynamics of male mouse germ cells at the critical stages: neonatal prospermatogonia, and early postntal (day 7) undifferentiated and differentiating spermatogonia. We found large partially methylated domains similar to those found in cancer cells and placenta in all these germ cells, and high levels of non-CG methylation and 5-hydroxymethylcytosines in neonatal prospermatogonia. Although the global CG methylation levels were stable in early postnatal male germ cells, and despite the reported scarcity of differential methylation in the adult spermatogonial stem cells, we identified many regions showing stage-specific differential methylation in and around genes important for stem cell function and spermatogenesis. These regions contained binding sites for specific transcription factors including the SOX family members.ConclusionsOur findings show a distinctive and dynamic regulation of DNA methylation during spermatogonial stem cell formation and differentiation in the neonatal and early postnatal testes. Furthermore, we revealed a unique accumulation and distribution of non-CG methylation and 5hmC marks in neonatal prospermatogonia. These findings contrast with the reported scarcity of differential methylation in adult spermatogonial stem cell differentiation and represent a unique phase of male germ cell development.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1833-5) contains supplementary material, which is available to authorized users.

SUMMARYDuring meiosis, specific histone modifications at pericentric heterochromatin (PCH), especially histone H3 tri-and dimethylation at lysine 9 (H3K9me3 and H3K9me2, respectively), are required for proper chromosome interactions. However, the molecular mechanism by which H3K9 methylation mediates the synapsis is not yet understood. We have generated a Cbx3-deficient mouse line and performed comparative analysis on Suv39h1/h2-, G9a-and Cbx3-deficient spermatocytes. This study revealed that H3K9me2 at PCH depended on Suv39h1/h2-mediated H3K9me3 and its recognition by the Cbx3 gene product HP1. We further found that centromere clustering and synapsis were commonly affected in G9a-and Cbx3-deficient spermatocytes. These genetic observations suggest that HP1/G9a-dependent PCH-mediated centromere clustering is an axis for proper chromosome interactions during meiotic prophase. We propose that the role of the HP1/G9a axis is to retain centromeric regions of unpaired homologous chromosomes in close alignment and facilitate progression of their pairing in early meiotic prophase. This study also reveals considerable plasticity in the interplay between different histone modifications and suggests that such stepwise and dynamic epigenetic modifications may play a pivotal role in meiosis.

SUMMARYEpigenetic modifications influence gene expression and chromatin remodeling. In embryonic pluripotent stem cells, these epigenetic modifications have been extensively characterized; by contrast, the epigenetic events of tissue-specific stem cells are poorly understood. Here, we define a new epigenetic shift that is crucial for differentiation of murine spermatogonia toward meiosis. We have exploited a property of incomplete cytokinesis, which causes male germ cells to form aligned chains of characteristic lengths, as they divide and differentiate. These chains revealed the stage of spermatogenesis, so the epigenetic differences of various stages could be characterized. Single, paired and medium chain-length spermatogonia not expressing Kit (a marker of differentiating spermatogonia) showed no expression of Dnmt3a2 and Dnmt3b (two de novo DNA methyltransferases); they also lacked the transcriptionally repressive histone modification H3K9me2. By contrast, spermatogonia consisting of ~8-16 chained cells with Kit expression dramatically upregulated Dnmt3a2/3b expression and also displayed increased H3K9me2 modification. To explore the function of these epigenetic changes in spermatogonia in vivo, the DNA methylation machinery was destabilized by ectopic Dnmt3b expression or Np95 ablation. Forced Dnmt3b expression induced expression of Kit; whereas ablation of Np95, which is essential for maintaining DNA methylation, interfered with differentiation and viability only after spermatogonia become Kit positive. These data suggest that the epigenetic status of spermatogonia shifts dramatically during the Kit-negative to Kit-positive transition. This shift might serve as a switch that determines whether spermatogonia self-renew or differentiate.

In many adult tissues, homeostasis relies on self-renewing stem cells that are primed for differentiation. The reconciliation mechanisms of these characteristics remain a fundamental question in stem cell biology. We propose that regulation at the post-transcriptional level is essential for homeostasis in murine spermatogonial stem cells (SSCs). Here, we show that Nanos2, an evolutionarily conserved RNA-binding protein, works with other cellular messenger ribonucleoprotein (mRNP) components to ensure the primitive status of SSCs through a dual mechanism that involves (1) direct recruitment and translational repression of genes that promote spermatogonial differentiation and (2) repression of the target of rapamycin complex 1 (mTORC1), a well-known negative pathway for SSC self-renewal, by sequestration of the core factor mTOR in mRNPs. This mechanism links mRNA turnover to mTORC1 signaling through Nanos2-containing mRNPs and establishes a post-transcriptional buffering system to facilitate SSC homeostasis in the fluctuating environment within the seminiferous tubule.

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space.