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Mammary tissue transcriptomic analysis for construction of integrated regulatory networks involved in lactogenesis of Ovis aries

机译:乳腺组织转录型分析卵白羊叶肝外综合监管网络的构建

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The mammary gland experiences vast changes between the onset of lactation and pregnancy. This remodeling involves different functions such as lactation that is controlled by innumerable regulators and various gene networks which are still not completely understood. MicroRNAs (miRNAs) are one of the important non-coding gene regulators which control an extensive range of biological processes. Thus, exploring miRNAs functions is important for solving gene regulation complexity. The main purpose in the present study is to identify the various gene regulative integrated networks involved in lactation progress in mammary gland. We analyzed ovine mammary tissue data sets which included expression profiles of mRNA (genes) and miRNAs related to six ewes in different days of lactation and nutritional treatments. We combined two different types of information: the network that is module inference by mRNAs (RNA-seq data), miRNAs and transcription factors (TFs) expression matrix and prediction of targets via computational methods. To discover the miRNAs regulatory function, 134 modules were predicted by using gene expression data and 14 TFs and 20 miRNAs were allocated to these predicted modules. By applying this integrated computation-based method, 38 miRNA-modules and 35 TF-module interactions were identified from ovine mammary tissue data during lactogenesis. A lot of these modules were involved in lipid and protein metabolism, as well as steroids and vitamin biosynthesis, which would play key roles in mammary tissue and lactation development. These results present new information about the regulatory procedures at the miRNAs and TF levels throughout lactation.
机译:乳腺发生哺乳期和怀孕之间的巨大变化。这种重塑涉及不同的功能,例如由无数稳压器和各种基因网络控制的哺乳期,这些基因网络仍然没有完全理解。 MicroRNAS(miRNA)是控制广泛的生物过程的重要非编码基因调节因子之一。因此,探索MiRNA功能对于求解基因调节复杂性是重要的。本研究中的主要目的是鉴定乳腺哺乳期进展中的各种基因调节网络。我们分析了绵延乳腺组织数据集,其包括在哺乳期和营养处理的不同日子中的mRNA(基因)和miRNA相关的mRNA(基因)和miRNA的表达谱。我们组合了两种不同类型的信息:通过MRNA(RNA-SEQ数据),MIRNA和转录因子(TFS)表达矩阵和通过计算方法预测目标的网络。为了发现miRNA调节功能,通过使用基因表达数据预测134个模块,并将14个TF和20 miRNA分配给这些预测模块。通过施加基于综合计算的方法,在生成期间从绵羊乳腺组织数据中鉴定38个miRNA模块和35个TF模块相互作用。许多这些模块涉及脂质和蛋白质代谢,以及类固醇和维生素生物合成,这将在乳腺组织和哺乳期发育中发挥关键作用。这些结果在哺乳期间提供了关于MiRNA和TF水平的新信息。

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