Research Article: CSmiRTar: Condition-Specific microRNA targets database

Date Published: July 13, 2017

Publisher: Public Library of Science

Author(s): Wei-Sheng Wu, Bor-Wen Tu, Tsung-Te Chen, Shang-Wei Hou, Joseph T. Tseng, Robertus A M de Bruin.

http://doi.org/10.1371/journal.pone.0181231

Abstract

MicroRNAs (miRNAs) are functional RNA molecules which play important roles in the post-transcriptional regulation. miRNAs regulate their target genes by repressing translation or inducing degradation of the target genes’ mRNAs. Many databases have been constructed to provide computationally predicted miRNA targets. However, they cannot provide the miRNA targets expressed in a specific tissue and related to a specific disease at the same time. Moreover, they cannot provide the common targets of multiple miRNAs and the common miRNAs of multiple genes at the same time. To solve these two problems, we construct a database called CSmiRTar (Condition-Specific miRNA Targets). CSmiRTar collects computationally predicted targets of 2588 human miRNAs and 1945 mouse miRNAs from four most widely used miRNA target prediction databases (miRDB, TargetScan, microRNA.org and DIANA-microT) and implements functional filters which allows users to search (i) a miRNA’s targets expressed in a specific tissue or/and related to a specific disease, (ii) multiple miRNAs’ common targets expressed in a specific tissue or/and related to a specific disease, (iii) a gene’s miRNAs related to a specific disease, and (iv) multiple genes’ common miRNAs related to a specific disease. We believe that CSmiRTar will be a useful database for biologists to study the molecular mechanisms of post-transcriptional regulation in human or mouse. CSmiRTar is available at http://cosbi.ee.ncku.edu.tw/CSmiRTar/ or http://cosbi4.ee.ncku.edu.tw/CSmiRTar/.

Partial Text

MicroRNAs (miRNAs), 20–25 nucleotides non-coding RNAs, play important roles in the post-transcriptional regulation of gene expression [1–3]. Via binding to the complementary sites within the 3’ untranslated regions (3’ UTRs) of their target genes’ mRNAs, miRNAs induce mRNA degradation or lead to translational inhibition [1,4–6]. miRNAs are known to be involved in a wide range of biological processes including cell development, differentiation, cell-cycle control and apoptosis [7–9].

In this article, we present CSmiRTar which provide computationally predicted targets of 2588 human miRNAs and 1945 mouse miRNAs. CSmiRTar implements (i) a tissue filter for users to search the miRNA targets expressed in a specific tissue, (ii) a disease filter for users to search the miRNA targets related to a specific disease, and (iii) a database filter for users to search the predicted miRNA targets supported by multiple existing databases,. Moreover, CSmiRTar allows users to search the common targets of a set of input miRNAs under a specific physiological condition and the common miRNAs of a set of input genes under a specific physiological condition. We provide many case studies to show the effectiveness of our filters in reducing the number of predicted miRNA targets but still keep the functional ones. However, users should note that some functional miRNA targets may not be kept when applying both the tissue and disease filters if they are not expressed in normal tissues but are abnormally expressed in disease states. Nevertheless, we believe that CSmiRTar will be a useful database for biologists to study the molecular mechanisms of post-transcriptional regulation in human and mouse.

 

Source:

http://doi.org/10.1371/journal.pone.0181231

 

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