Our aim is to screen miRNAs and genes related to tetralogy of Fallot and construct a co-expression network based on integrating miRNA and gene microarrays. We downloaded the gene expression profile GSE35490 (miRNA) and GSE35776 (mRNA) of tetralogy of Fallot from the Gene Expression Omnibus database, which includes eight normal and 15 disease samples from infants, and screened differentially expressed miRNAs and genes between normal and disease samples (cut-off: p < 0.05; FDR < 0.05; and log FC > 2 or log FC < -2); in addition, we downloaded human miRNA and their targets, which were collected in the miRNA targets prediction database TargetScan, and selected ones that also appeared in our differentially expressed miRNAs and their predicted targets (score >0.9) and then made a relationship of diff_miRNAs and diff_genes of our results. Finally, we uploaded all the diff_target genes into String, constructed a co-expression network regulated by diff_miRNAs, and performed functional analysis with the software DAVID. Comparing normal and disease lesion tissue, we got 32 and 875 differentially expressed miRNAs and genes, respectively, and found hsa-miR-124 with 34 diff_target genes and hsa-miR-138 with two diff_target genes. Then we constructed a co-expression network that contains 231 pairs of genes. Genes in the network were enriched into 14 function clusters, and the most significant one is protein localisation. We screened the tetralogy of Fallot-related hsa-miR-124 and hsa-miR-138 with their direct and indirect differentially expressed target genes, and found that protein localisation is the significant cause affecting tetralogy of Fallot. Our approach may provide the groundwork for a new therapy approach to treating tetralogy of Fallot.