miRmapper: A Tool for Interpretation of miRNA-mRNA Interaction Networks

被引:19
|
作者
da Silveira, Willian A. [1 ]
Renaud, Ludivine [2 ,3 ]
Simpson, Jonathan [1 ]
Glen, William B., Jr. [1 ]
Hazard, Edward S. [1 ,4 ]
Chung, Dongjun [5 ]
Hardiman, Gary [1 ,2 ,3 ,5 ,6 ]
机构
[1] Med Univ South Carolina, Ctr Genom Med, Bioinformat, Charleston, SC 29425 USA
[2] Med Univ South Carolina, Dept Med, Div Nephrol, Charleston, SC 29425 USA
[3] Hollings Marine Lab, Lab Marine Syst Biol, Charleston, SC 29412 USA
[4] Med Univ South Carolina, Acad Affairs Fac, Charleston, SC 29425 USA
[5] Med Univ South Carolina, Dept Publ Hlth Sci, Charleston, SC 29425 USA
[6] Queens Univ Belfast, Inst Global Food Secur, Stranmillis Rd, Belfast BT9 5AG, Antrim, North Ireland
关键词
bioinformatics pipelines; algorithm development for network integration; miRNA-gene expression networks; multiomics integration; network topology analysis; PROMOTES PROLIFERATION; CELL-PROLIFERATION; COLORECTAL-CANCER; GENE-REGULATION; WEB TOOL; MICRORNAS; MIGRATION; INVASION; METASTASIS; EXPRESSION;
D O I
10.3390/genes9090458
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
It is estimated that 30% of all genes in the mammalian cells are regulated by microRNA (miRNAs). The most relevant miRNAs in a cellular context are not necessarily those with the greatest change in expression levels between healthy and diseased tissue. Differentially expressed (DE) miRNAs that modulate a large number of messenger RNA (mRNA) transcripts ultimately have a greater influence in determining phenotypic outcomes and are more important in a global biological context than miRNAs that modulate just a few mRNA transcripts. Here, we describe the development of a tool, miRmapper, which identifies the most dominant miRNAs in a miRNA-mRNA network and recognizes similarities between miRNAs based on commonly regulated mRNAs. Using a list of miRNA-target gene interactions and a list of DE transcripts, miRmapper provides several outputs: (1) an adjacency matrix that is used to calculate miRNA similarity utilizing the Jaccard distance; (2) a dendrogram and (3) an identity heatmap displaying miRNA clusters based on their effect on mRNA expression; (4) a miRNA impact table and (5) a barplot that provides a visual illustration of this impact. We tested this tool using nonmetastatic and metastatic bladder cancer cell lines and demonstrated that the most relevant miRNAs in a cellular context are not necessarily those with the greatest fold change. Additionally, by exploiting the Jaccard distance, we unraveled novel cooperative interactions between miRNAs from independent families in regulating common target mRNAs; i.e., five of the top 10 miRNAs act in synergy.
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页数:18
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