Feedforward loop profile among transcription factor, miRNA and mRNA in influenza A virus-infected mouse lungs

Purpose:In the present study,we focused on the 46 microRNAs and 719 genes in the microRNA-gene network,reported by us,and aimed to build a research blueprint of feedforward loops and reveal the key TFs in H1N1-infected mouse lung.Method:Based on microRNAs and genes in the microRNA-gene network previously reported by us,we used Jemboss software to find relationships between TFs and microRNAs(or genes),and then built a TF-microRNA-gene network exploiting the interactions between TFs and microRNAs(or genes).Next,we searched the sequences of above genes or microRNAs near the transcription start site(TSS)area,and then used the MatchTM algorithm to predict relevant TFs,and built the TF-Gene-Network.Result:We built a TF-microRNAgene network and exploreed eight key TFs,namely NF-AT1,GKLF,SRY,SOX10,AML1,MZF1,CRX and myogenin,in the network,and then constructed subgraphs of these eight TFs.Simultaneously,we predicted the possible target genes of microRNAs and identified the feedforward regulation relationship of possible TFs,microRNAs and mRNAs.The results showed that all eight factors with a score greater than 100 were TFs,namely NF-AT1,GKLF,SRY,SOX10,AML1,CRX,myogenin and MZF1.We then constructed subtables of the above eight TFs.Conclusion:In this study,TFs including NF-AT1,GKLF,SRY,SOX10,AML1,MZF1,CRX and myogenin showed the highest score(>100)not only in the TF-microRNA-gene network but also in feedforward loops,indicating that these eight TFs play the most important roles in mouse H1N1 influenza virus infection biology.