title: A tri-component conservation strategy reveals highly confident microRNA-mRNA interactions and evolution of microRNA regulatory networks.
abstract: MicroRNAs are small non-coding RNAs that can regulate expressions of their target genes at the post-transcriptional level. In this study, we propose a tri-component strategy that combines the conservation of microRNAs, homology of mRNA coding regions, and conserved microRNA binding sites in the 3' untranslated regions to discover conserved microRNA-mRNA interactions. To validate the performance of our conservation strategy, we collected the experimentally validated microRNA-mRNA interactions from three databases as the golden standard. We found that the proposed strategy can improve the performance of existing target prediction algorithms by approximately 2-4 fold. In addition, we demonstrated that the proposed strategy could efficiently retain highly confident interactions from the intersection results of the existing algorithms and filter out the possible false positive predictions in the union one. Furthermore, this strategy can facilitate our ability to trace the homologues in different species that are targeted by the same miRNA family because it combines these three features to identify the conserved miRNA-mRNA interactions during evolution. Through an extensive application of the proposed conservation strategy to a study of the miR-1/206 regulatory network, we demonstrate that the target mRNA recruiting process could be associated with expansion of miRNA family during its evolution. We also uncovered the functional evolution of the miR-1/206 regulatory network. In this network, the early targeted genes tend to participate in more general and development-related functions. In summary, the conservation strategy is capable of helping to highlight the highly confident miRNA-mRNA interactions and can be further applied to reveal the evolutionary features of miRNA regulatory network and functions.
authors: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
authors: Chen-Ching
authors: CC
authors: Lin
authors: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
authors: Ramkrishna
authors: R
authors: Mitra
authors: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
authors: Zhongming
authors: Z
authors: Zhao
mesh_terms: D020413:3' Untranslated Regions; D000818:Animals; D002417:Cattle; D019143:Evolution, Molecular; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D051379:Mice; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D012333:RNA, Messenger / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D014981:Xenopus
chemical_list: D020413:3' Untranslated Regions; D035683:MicroRNAs; D012333:RNA, Messenger