Construction And Analysis Of Competitive Endogenous Regulatory Networks In Energy Confinement

Calorie restriction(CR)is currently the only non-pharmacological intervention that can prolong life.Competing endogenous RNA(ceRNA)hypothesis holds the idea that transcripts such as mRNA and lncRNA can competitively bind to microRNA through miRNA response element(miRNA response element,MRE),interact with each other and regulate their respective expression levels,resulting in large-scale regulatory network.Among them,miRNA plays an important role as an intermediary factor in the network,and the interaction of competitive endogenous RNA,especially ceRNA related to energy limitation,has not been fully elucidated.Therefore,exploring the interaction of CR-related ceRNA is of great significance to the mechanism of CR.We integrated three levels of expression profile data of lncRNA,mRNA and miRNA,used topological network analysis algorithm to find active miRNAs with regulatory functions in CR,Based on the selected CR regulatory activity miRNAs,high-throughput sequencing technology was used to predict miRNA-related lncRNAs,and miRNA target gene information was extracted through the CR miRNA-mRNA sub-network,miRNA was used as an intermediary factor to reconstruct the ceRNA interaction network.We also evaluated and analyzed the nature of the network.Finally,we used CR-related key genes as a mapping to explore CR-specific sub-networks to discover key factors in the regulatory network.Then we used gene function enrichment analysis to screen the key genes related to CR among the target genes.Compared with AL,there were 34 differentially expressed lncRNAs.Among them,the expression of 15 lncRNA in CR were up-regulated;the expression of 19 lncRNA were down-regulated.There were 110 differentially expressed miRNAs,of which 33 miRNAs were up-regulated.And 77 miRNAs were all down-regulated.There were 1179 differentially expressed mRNAs.Among them,the expression of 594 mRNAs in CR were up-regulated compared to AL.The expression levels of 585 mRNAs were all downregulated.The endogenous competitive regulatory networks were constructed according to gene regulatory relationships,and the core networks with key genes were screened out by topological analysis.The top three topological networks with the highest analysis score were verified by real-time fluorescence quantitative PCR.This study intends to screen for functional miRNAs related to gastric cancer based on systems biology and the concept of integromics.We applied bioinformatic methods to dig deeper into the data,then used the regulatory relationship between them to perform predictive analysis and data integration to construct a CR-related ceRNA regulatory network and lastly found the factors that play a key role.Our results provide new ideas for CR mechanism.