Identifying microRNA targets in epithelial-mesenchymal transition using joint-intervention causal inference

microRNAs (miRNAs) are important gene regulators, controlling a wide range of biological processes and being involved in several types of cancers. Currently, several computational approaches have been developed to elucidate the miRNA-mRNA regulatory relationships. However, these approaches have their own limitations and we are still far from understanding the miRNA-mRNA relationships, especially in specific biological processes. In this paper, we adapt a causal inference method to infer miRNA targets from the Epithelial Mesenchymal Transition (EMT) dataset. Our method utilises a causality based method that estimates the causal effect of each miRNA on a mRNA while controlling the effects of other miRNAs on the mRNA. The inferred causal effect is similar to the effect of a miRNA on a mRNA when we knockout all the other miRNAs. The experimental results show that our method is better than existing benchmark methods in finding experimentally confirmed miRNA targets. Moreover, we have found that the miR-200 family members (miR-141, miR-200a/b/c, and miR-429) synergistically regulate a number of target genes in EMT, suggesting their roles in controlling cancer metastasis. In addition, functional and pathway enrichment analyses show that the discovered miRNA-mRNA regulatory relationships are highly enriched in EMT, implying the validity of the proposed method. Novel miRNA-mRNA regulatory relationships discovered by our method provide a rich resource for follow up wet-lab experiments and EMT related studies.