Dissecting the biological relationship between TCGA miRNA and mRNA sequencing data using MMiRNA-Viewer

Abstract

BackgroundMicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3′ untranslated regions (UTRs). The Cancer Genome Atlas (TCGA) harbors an increasing amount of cancer genome data for both tumor and normal samples. However, there are few visualization tools focusing on concurrently displaying important relationships and attributes between miRNAs and mRNAs of both cancer tumor and normal samples. Moreover, a deep investigation of miRNA-mRNA target and biological relationships across multiple cancer types by integrating web-based analysis has not been thoroughly conducted.ResultsWe developed an interactive visualization tool called MMiRNA-Viewer that can concurrently present the co-relationships of expression between miRNA-mRNA pairs of both tumor and normal samples into a single graph. The input file of MMiRNA-Viewer contains the expression information including fold changes between normal and tumor samples for mRNAs and miRNAs, the correlation between mRNA and miRNA, and the predicted target relationship by a number of databases. Users can also load their own input data into MMiRNA-Viewer and visualize and compare detailed information about cancer-related gene expression changes, and also changes in the expression of transcription-regulating miRNAs.To validate the MMiRNA-Viewer, eight types of TCGA cancer datasets with both normal and control samples were selected in this study and three filter steps were applied subsequently. We performed Gene Ontology (GO) analysis for genes available in final selected 238 pairs and also for genes in the top 5 % (95 percentile) for each of eight cancer types to report a significant number of genes involved in various biological functions and pathways. We also calculated various centrality measurement matrices for the largest connected component(s) in each of eight cancers and reported top genes and miRNAs with high centrality measurements.ConclusionsWith its user-friendly interface, dynamic visualization and advanced queries, we also believe MMiRNA-Viewer offers an intuitive approach for visualizing and elucidating co-relationships between miRNAs and mRNAs of both tumor and normal samples. We suggest that miRNA and mRNA pairs with opposite fold changes of their expression and with inverted correlation values between tumor and normal samples might be most relevant for explaining the decoupling of mRNAs and their targeting miRNAs in tumor samples for certain cancer types.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1219-y) contains supplementary material, which is available to authorized users.

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes

“…The Genomic Data Commons database is a monumental collection of genetic data for cancer research, encompassing The Cancer Genome Atlas (TCGA) and other projects, creating an opportunity for revealing new microRNA-mRNA pairs impacting cell proliferation. Indeed, there have been attempts to build tools that could, to a certain degree, automatize the search and were applied to TCGA datasets [20,21]. However, identification of the candidate pairs is a challenging task due to the regulatory complexity and inter-dependence of mRNAs and microRNAs and performing only correlation analysis between differentially expressed mRNAs and microRNAs followed by a network analysis might not be a satisfactory approach.…”

MMiRNA-Viewer2, a bioinformatics tool for visualizing functional annotation for MiRNA and MRNA pairs in a network

“…We took the significant mRNA-miRNA target pairs obtained from RNA-Seq and miRNA-Seq data for 15 cancer types from The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov) project. We used a similar approach adopted in our previous study [28,29] to select input pairs. Specifically, we employed a computer C program to calculate the Pearson Correlation Coefficient (CC).…”

Proceedings of the 2016 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference

“…Yongsheng Bai et al developed a program called MMiRNA-Viewer [6] for interactive visualization of the expression relationships between miRNA-mRNA pairs of both tumor and normal samples into a single graph, to help users better explore the relationships between these two entities.…”