In silico Identification of miRNA Target Genes and Related Pathways

To identify potential target genes of the significantly differentially expressed miRNAs, we conducted an in silico analysis using DIANA Tools with mirPath v2.0, microT-CDS v5.0¹ that support all analyses for KEGG (Kyoto Encyclopedia of Genes and genomes, https://www.genome.jp/kegg/) molecular pathways, as well as multiple slices of Gene Ontology (GO, http://geneontology.org/) in Mus musculus (Kanehisa and Goto, 2000; Vlachos et al., 2012; Kanehisa et al., 2016). Analysis using DIANA were performed with the default parameters (p value threshold: 0.05, microT threshold: 0.8) (Vlachos et al., 2012). The web server identifies miRNAs targeting the selected pathway and ranks them according to their enrichment p values. We implemented functional enrichment analysis of miRNA target genes using annotation from the KEGG Pathway Database (Kanehisa and Goto, 2000; Kanehisa et al., 2016). Additionally, to functional annotation of miRNAs and miRNA combinations DIANA and KEGG as well as GO were used using all datasets or their subsets (genes union and pathways union parameters were selected). The biology process terms with p < 0.05 were considered statistically significant. Targeted Pathways clusters/heatmaps were generated from DIANA. By selecting Targeted Pathways Clusters/heatmap, miRpath flags all the significant pathways (with p values < 0.05) with 0 and the other pathways with 1. The miRD², microRNA.org-Targets and Expression, and miRbase: the microRNA database were also used to predicted miRNA-target interactions (http://www.microrna.org/microrna/home.do; http://mirbase.org/; http://mirdb.org/). Ensembl and miRbase were used to support miRNA nomenclature history (http://mirbase.org/; http://www.ensembl.org/index.html). The combination of validated and predicted miRNA-target interactions were used for further analyses with qPCR.