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.

乳腺在泌乳和怀孕之间经历了巨大的变化。这种重塑涉及不同的功能，例如受无数调节器和各种基因网络控制的泌乳，但仍未完全了解。MicroRNAs (miRNAs) 是重要的非编码基因调控因子之一，它控制着广泛的生物过程。因此，探索miRNA的功能对于解决基因调控的复杂性很重要。本研究的主要目的是确定参与乳腺泌乳过程的各种基因调控整合网络。我们分析了绵羊乳腺组织数据集，其中包括与 6 只母羊在泌乳和营养治疗的不同天数相关的 mRNA（基因）和 miRNA 的表达谱。我们结合了两种不同类型的信息：通过 mRNA（RNA-seq 数据）、miRNA 和转录因子（TF）表达矩阵进行模块推理的网络以及通过计算方法预测目标的网络。为了发现 miRNA 的调控功能，使用基因表达数据预测了 134 个模块，并将 14 个 TF 和 20 个 miRNA 分配给这些预测模块。通过应用这种基于集成计算的方法，在泌乳过程中从绵羊乳腺组织数据中鉴定了 38 个 miRNA 模块和 35 个 TF 模块相互作用。许多这些模块参与脂质和蛋白质代谢，以及类固醇和维生素的生物合成，这将在乳腺组织和泌乳发育中发挥关键作用。