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首页> 外文期刊>Genomics >Application of transcriptional and biological network analyses in mouse germ-cell transcriptomes.
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Application of transcriptional and biological network analyses in mouse germ-cell transcriptomes.

机译：转录和生物网络分析在小鼠生殖细胞转录组中的应用。

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Serial analysis of gene expression (SAGE) provides a global analysis platform for profiling mRNA populations present in cells of interest without the constraint of gene selection and the ambiguous nature of data obtained. However, most of the reports on SAGE and germ cell development are limited to descriptive analyses. Here, we report a series of bioinformatic analyses using recently published SAGE data on the transcriptome of mouse type A spermatogonia (Spga), pachytene spermatocytes (Spcy), and round spermatids (Sptd). Tags with a total count of > or =20 in three SAGE libraries were examined. Our aim was to identify and discover potential transcriptional regulators and pathways involved at different stages of spermatogenesis. Unsupervised hierarchical clustering based on tag expression and Gene Ontology analysis were applied to identify genes and biological processes overrepresented at a particular stage of development. The 5' cis-regulatory elements were examined for common regulators in different functional clusters. Potential biological networks were also constructed to reveal the link between the gene candidates. Biological pathways related to the three germ cell stages were constructed. A number of known transcription regulators in spermatogenesis, including NF-kappaB, SP1, AP-1, and EGR, were identified. Novel promoter elements such as the E box in Spga-specific genes, GATA in Spcy-specific genes, and GKLF in Sptd-specific genes were also observed. Taken together, our approach is reliable and provides a foundation for the generation of novel biological hypotheses for studying spermatogenesis.
机译：基因表达的序列分析（SAGE）提供了一个全局分析平台，可用于分析目标细胞中存在的mRNA种群，而不受基因选择的限制和获得数据的含糊性质。但是，有关SAGE和生殖细胞发育的大多数报道仅限于描述性分析。在这里，我们报告了一系列有关小鼠A型精原细胞（Spga），粗线精原细胞（Spcy）和圆形精子（Sptd）转录组的SAGE数据，进行了生物信息学分析。检查了三个SAGE库中总数≥20的标签。我们的目标是鉴定和发现精子发生不同阶段涉及的潜在转录调节因子和途径。基于标签表达和基因本体分析的无监督分层聚类被用于识别在特定发展阶段过度表达的基因和生物学过程。检查了5'顺式调节元件在不同功能簇中的常见调节剂。还构建了潜在的生物网络以揭示候选基因之间的联系。构建了与三个生殖细胞阶段有关的生物学途径。确定了许多已知的精子发生转录调节因子，包括NF-κB，SP1，AP-1和EGR。还观察到了新的启动子元件，例如Spga特异性基因中的E框，Spcy特异性基因中的GATA和Sptd特异性基因中的GKLF。综上所述，我们的方法是可靠的，并为研究精子发生的新的生物学假设的产生提供了基础。

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