title: Identifying direct miRNA-mRNA causal regulatory relationships in heterogeneous data.
abstract: Discovering the regulatory relationships between microRNAs (miRNAs) and mRNAs is an important problem that interests many biologists and medical researchers. A number of computational methods have been proposed to infer miRNA-mRNA regulatory relationships, and are mostly based on the statistical associations between miRNAs and mRNAs discovered in observational data. The miRNA-mRNA regulatory relationships identified by these methods can be both direct and indirect regulations. However, differentiating direct regulatory relationships from indirect ones is important for biologists in experimental designs. In this paper, we present a causal discovery based framework (called DirectTarget) to infer direct miRNA-mRNA causal regulatory relationships in heterogeneous data, including expression profiles of miRNAs and mRNAs, and miRNA target information. DirectTarget is applied to the Epithelial to Mesenchymal Transition (EMT) datasets. The validation by experimentally confirmed target databases suggests that the proposed method can effectively identify direct miRNA-mRNA regulatory relationships. To explore the upstream regulators of miRNA regulation, we further identify the causal feedforward patterns (CFFPs) of TF-miRNA-mRNA to provide insights into the miRNA regulation in EMT. DirectTarget has the potential to be applied to other datasets to elucidate the direct miRNA-mRNA causal regulatory relationships and to explore the regulatory patterns.
authors.affiliation: Faculty of Engineering, Dali University, Dali, China. Electronic address: zhangjunpeng_411@yahoo.com.
authors.forename: Junpeng
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA 5095, Australia. Electronic address: leyty017@mymail.unisa.edu.au.
authors.forename: Thuc Duy
authors.initials: TD
authors.lastname: Le
authors.affiliation: School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA 5095, Australia. Electronic address: lin.liu@unisa.edu.au.
authors.forename: Lin
authors.initials: L
authors.lastname: Liu
authors.affiliation: Children's Cancer Institute Australia, Randwick, NSW 2301, Australia. Electronic address: BLiu@ccia.unsw.edu.au.
authors.forename: Bing
authors.initials: B
authors.lastname: Liu
authors.affiliation: Kunming University of Science and Technology, Kunming, China. Electronic address: jfenghe@kmust.edu.cn.
authors.forename: Jianfeng
authors.initials: J
authors.lastname: He
authors.affiliation: Centre for Cancer Biology, SA Pathology, SA 5000, Australia. Electronic address: greg.goodall@health.sa.gov.au.
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Goodall
authors.affiliation: School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA 5095, Australia. Electronic address: jiuyong.li@unisa.edu.au.
authors.forename: Jiuyong
authors.initials: J
authors.lastname: Li
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D058750:Epithelial-Mesenchymal Transition / Q000235:genetics; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger
keywords: Causal feedforward patterns; Causal regulatory relationships; Epithelial–mesenchymal transition; MicroRNA; mRNA