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miRmapper:一种用于解读miRNA-mRNA相互作用网络的工具。

miRmapper: A Tool for Interpretation of miRNA⁻mRNA Interaction Networks.

作者信息

da Silveira Willian A, Renaud Ludivine, Simpson Jonathan, Glen William B, Hazard Edward S, Chung Dongjun, Hardiman Gary

机构信息

Center for Genomic Medicine, Bioinformatics, Medical University of South Carolina (MUSC), Charleston, SC 29425, USA.

Division of Nephrology, Department of Medicine, Medical University of South Carolina (MUSC), Charleston, SC 29425, USA.

出版信息

Genes (Basel). 2018 Sep 14;9(9):458. doi: 10.3390/genes9090458.

Abstract

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.

摘要

据估计,哺乳动物细胞中30%的基因受微小RNA(miRNA)调控。在细胞环境中,最相关的miRNA不一定是那些在健康组织和患病组织之间表达水平变化最大的miRNA。调控大量信使核糖核酸(mRNA)转录本的差异表达(DE)miRNA最终在决定表型结果方面具有更大影响,并且在整体生物学背景下比仅调控少数mRNA转录本的miRNA更重要。在此,我们描述了一种工具“miRmapper”的开发,它可识别miRNA-mRNA网络中最主要的miRNA,并基于共同调控的mRNA识别miRNA之间的相似性。利用miRNA-靶基因相互作用列表和DE转录本列表,miRmapper提供了几个输出结果:(1)一个邻接矩阵,用于利用杰卡德距离计算miRNA相似性;(2)一个树形图;(3)一个基于miRNA对mRNA表达的影响显示miRNA簇的同一性热图;(4)一个miRNA影响表;(5)一个条形图,直观展示这种影响。我们使用非转移性和转移性膀胱癌细胞系测试了该工具,结果表明在细胞环境中最相关的miRNA不一定是那些具有最大倍数变化的miRNA。此外,通过利用杰卡德距离,我们揭示了来自独立家族的miRNA在调控共同靶mRNA方面的新型协同相互作用;即前10个miRNA中有5个协同作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aded/6162471/de3c146bfe54/genes-09-00458-g001.jpg

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