Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC J1M 0C8, Canada.
Department of Animal Science, McGill University, 21111, Lakeshore Road, Ste-Anne-de Bellevue, QC H9X 3V9, Canada.
Int J Mol Sci. 2017 Jul 18;18(7):1560. doi: 10.3390/ijms18071560.
Co-expression network analyses provide insights into the molecular interactions underlying complex traits and diseases. In this study, co-expression network analysis was performed to detect expression patterns (modules or clusters) of microRNAs (miRNAs) during lactation, and to identify miRNA regulatory mechanisms for milk yield and component traits (fat, protein, somatic cell count (SCC), lactose, and milk urea nitrogen (MUN)) via miRNA target gene enrichment analysis. miRNA expression (713 miRNAs), and milk yield and components (Fat%, Protein%, lactose, SCC, MUN) data of nine cows at each of six different time points (day 30 (D30), D70, D130, D170, D230 and D290) of an entire lactation curve were used. Four modules or clusters (GREEN, BLUE, RED and TURQUOISE) of miRNAs were identified as important for milk yield and component traits. The GREEN and BLUE modules were significantly correlated (|| > 0.5) with milk yield and lactose, respectively. The RED and TURQUOISE modules were significantly correlated (|| > 0.5) with both SCC and lactose. In the GREEN module, three abundantly expressed miRNAs (miR-148a, miR-186 and miR-200a) were most significantly correlated to milk yield, and are probably the most important miRNAs for this trait. DDR1 and DDHX1 are hub genes for miRNA regulatory networks controlling milk yield, while HHEX is an important transcription regulator for these networks. miR-18a, miR-221/222 cluster, and transcription factors HOXA7, and NOTCH 3 and 4, are important for the regulation of lactose. miR-142, miR-146a, and miR-EIA17-14144 (a novel miRNA), and transcription factors in the SMAD family and MYB, are important for the regulation of SCC. Important signaling pathways enriched for target genes of miRNAs of significant modules, included protein kinase A and PTEN signaling for milk yield, eNOS and Noth signaling for lactose, and TGF β, HIPPO, Wnt/β-catenin and cell cycle signaling for SCC. Relevant enriched gene ontology (GO)-terms related to milk and mammary gland traits included cell differentiation, G-protein coupled receptor activity, and intracellular signaling transduction. Overall, this study uncovered regulatory networks in which miRNAs interacted with each other to regulate lactation traits.
共表达网络分析提供了对复杂性状和疾病潜在分子相互作用的深入了解。在这项研究中,进行了共表达网络分析,以检测泌乳期间 microRNA (miRNA) 的表达模式(模块或聚类),并通过 miRNA 靶基因富集分析识别 miRNA 调节产奶量和成分性状(脂肪、蛋白质、体细胞计数(SCC)、乳糖和牛奶尿素氮(MUN)的机制。使用了 9 头奶牛在整个泌乳曲线的 6 个不同时间点(第 30 天(D30)、第 70 天、第 130 天、第 170 天、第 230 天和第 290 天)的每个时间点的 miRNA 表达(713 个 miRNA)和产奶量及成分(脂肪%、蛋白质%、乳糖、SCC、MUN)数据。鉴定了四个 miRNA 模块(GREEN、BLUE、RED 和 TURQUOISE)对于产奶量和成分性状很重要。GREEN 和 BLUE 模块与产奶量和乳糖显著相关(|| > 0.5)。RED 和 TURQUOISE 模块与 SCC 和乳糖均显著相关(|| > 0.5)。在 GREEN 模块中,三个大量表达的 miRNA(miR-148a、miR-186 和 miR-200a)与产奶量最显著相关,并且可能是该性状最重要的 miRNA。DDR1 和 DDHX1 是控制产奶量的 miRNA 调控网络的枢纽基因,而 HHEX 是这些网络的重要转录调节因子。miR-18a、miR-221/222 簇以及转录因子 HOXA7、NOTCH3 和 4 对乳糖的调节很重要。miR-142、miR-146a 和 miR-EIA17-14144(一种新的 miRNA)以及 SMAD 家族和 MYB 中的转录因子对 SCC 的调节很重要。miRNA 显著模块的靶基因富集的重要信号通路包括产奶量的蛋白激酶 A 和 PTEN 信号通路、乳糖的 eNOS 和 Noth 信号通路以及 SCC 的 TGFβ、HIPPO、Wnt/β-catenin 和细胞周期信号通路。与牛奶和乳腺性状相关的重要富集基因本体(GO)术语包括细胞分化、G 蛋白偶联受体活性和细胞内信号转导。总体而言,本研究揭示了 miRNA 相互作用以调节泌乳性状的调控网络。