The G protein-coupled receptors (GPCR) sensing nutritional signals (amino acids, fatty acids, glucose, etc.) are not fully understood. In this research, we used transcriptome sequencing to analyse differentially expressed genes (DEG) in mouse mammary gland tissues at puberty, lactation and involution stages, in which eight GPCR were selected out and verified by qRT-PCR assay. It was further identified the role of GPR110-mediating nutrients including palmitic acid (PA) and methionine (Met) to improve milk synthesis using mouse mammary epithelial cell line HC11. PA but not Met affected GPR110 expression in a dose-dependent manner. GPR110 knockdown decreased milk protein and fat synthesis and cell proliferation and blocked the stimulation of PA on mechanistic target of rapamycin (mTOR) phosphorylation and sterol-regulatory element binding protein 1c (SREBP-1c) expression. In summary, these experimental results disclose DEG related to lactation and reveal that GPR110 mediates PA to activate the mTOR and SREBP-1c pathways to promote milk protein and fat synthesis.

We construct a high-order conditional distance covariance, which generalizes the notation of conditional distance covariance. The joint conditional distance covariance is defined as a linear combination of conditional distance covariances, which can capture the joint relation of many random vectors given one vector. Furthermore, we develop a new method of conditional independence test based on the joint conditional distance covariance. Simulation results indicate that the proposed method is very effective. We also apply our method to analyze the relationships of PM2.5 in five Chinese cities: Beijing, Tianjin, Jinan, Tangshan and Qinhuangdao by the Gaussian graphical model.