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

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.

[1]  V. Thayanithy,et al.  Regulation of Heme Oxygenase-1 Protein Expression by miR-377 in Combination with miR-217* , 2010, The Journal of Biological Chemistry.

[2]  G. Luo,et al.  PTTG1 regulated by miR-146a-3p promotes bladder cancer migration, invasion, metastasis and growth , 2016, Oncotarget.

[3]  B. Wang,et al.  miR-421 is a diagnostic and prognostic marker in patients with osteosarcoma , 2016, Tumor Biology.

[4]  L. Kiesel,et al.  HS3ST2 modulates breast cancer cell invasiveness via MAP kinase‐ and Tcf4 (Tcf7l2)‐dependent regulation of protease and cadherin expression , 2014, International journal of cancer.

[5]  E. Izaurralde,et al.  Getting to the Root of miRNA-Mediated Gene Silencing , 2008, Cell.

[6]  P. Tsonis,et al.  mirPRo–a novel standalone program for differential expression and variation analysis of miRNAs , 2015, Scientific Reports.

[7]  L. Sieburth,et al.  Widespread Translational Inhibition by Plant miRNAs and siRNAs , 2008, Science.

[8]  Yadong Feng,et al.  MicroRNA-1290 promotes esophageal squamous cell carcinoma cell proliferation and metastasis. , 2015, World journal of gastroenterology.

[9]  Gabriele Sales,et al.  MAGIA, a web-based tool for miRNA and Genes Integrated Analysis , 2010, Nucleic Acids Res..

[10]  Ana Kozomara,et al.  miRBase: annotating high confidence microRNAs using deep sequencing data , 2013, Nucleic Acids Res..

[11]  Vicente P. Guerrero-Bote,et al.  A new approach to the metric of journals' scientific prestige: The SJR indicator , 2010, J. Informetrics.

[12]  John G Doench,et al.  Comparison of siRNA-induced off-target RNA and protein effects. , 2007, RNA.

[13]  A. Pasquinelli,et al.  Regulation by let-7 and lin-4 miRNAs Results in Target mRNA Degradation , 2005, Cell.

[14]  Daniel J. Brass Being in the right place: A structural analysis of individual influence in an organization. , 1984 .

[15]  K. Voskarides Plasticity vs Mutation. The role of microRNAs in human adaptation , 2017, Mechanisms of Ageing and Development.

[16]  Curtis Balch,et al.  MicroRNA and mRNA integrated analysis (MMIA): a web tool for examining biological functions of microRNA expression , 2009, Nucleic Acids Res..

[17]  D. Bartel,et al.  Predicting effective microRNA target sites in mammalian mRNAs , 2015, eLife.

[18]  Xiaofeng Jiang,et al.  MiR-1297 promotes apoptosis and inhibits the proliferation and invasion of hepatocellular carcinoma cells by targeting HMGA2. , 2015, International journal of molecular medicine.

[19]  M. Boutros,et al.  Wnt signaling in cancer , 2016, Oncogene.

[20]  Michal Linial,et al.  MiRror: a combinatorial analysis web tool for ensembles of microRNAs and their targets , 2010, Bioinform..

[21]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[22]  A. Hatzigeorgiou,et al.  The DIANA-mirExTra Web Server: From Gene Expression Data to MicroRNA Function , 2010, PloS one.

[23]  Y. Toiyama,et al.  Circulating microRNA-1290 as a novel diagnostic and prognostic biomarker in human colorectal cancer. , 2016, Annals of oncology : official journal of the European Society for Medical Oncology.

[24]  Zhifu Sun,et al.  CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data , 2014, BMC Genomics.

[25]  E. Sontheimer,et al.  Origins and Mechanisms of miRNAs and siRNAs , 2009, Cell.

[26]  L. Stechow Cancer Systems Biology , 2018, Methods in Molecular Biology.

[27]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[28]  Din J. Wasem Mining of Massive Datasets , 2014 .

[29]  Ralf Zimmer,et al.  Widespread context dependency of microRNA-mediated regulation , 2014, Genome research.

[30]  H. Osada,et al.  MicroRNAs in biological processes and carcinogenesis. , 2007, Carcinogenesis.

[31]  Xuan Liang,et al.  MicroRNA-1297 inhibits prostate cancer cell proliferation and invasion by targeting the AEG-1/Wnt signaling pathway. , 2016, Biochemical and biophysical research communications.

[32]  W. Filipowicz,et al.  Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? , 2008, Nature Reviews Genetics.

[33]  Eduardo Andrés-León,et al.  miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA analysis , 2016, Scientific Reports.

[34]  E. Izaurralde,et al.  Gene silencing by microRNAs: contributions of translational repression and mRNA decay , 2011, Nature Reviews Genetics.

[35]  Jie Tang,et al.  Deregulated expression of miR‐107 inhibits metastasis of PDAC through inhibition PI3K/Akt signaling via caveolin‐1 and PTEN , 2017, Experimental cell research.

[36]  János Podani,et al.  Introduction to the exploration of multivariate biological data , 2000 .

[37]  N. Rajewsky,et al.  The evolution of gene regulation by transcription factors and microRNAs , 2007, Nature Reviews Genetics.

[38]  Chun-Wei Hsu,et al.  Characterization of microRNA‐regulated protein‐protein interaction network , 2008, Proteomics.

[39]  angesichts der Corona-Pandemie,et al.  UPDATE , 1973, The Lancet.

[40]  Peer Bork,et al.  Target-specific requirements for enhancers of decapping in miRNA-mediated gene silencing. , 2007, Genes & development.

[41]  C. Myers,et al.  Using networks to measure similarity between genes: association index selection , 2013, Nature Methods.

[42]  Ulrich Bodenhofer,et al.  Hsa-miR-375 is a predictor of local control in early stage breast cancer , 2016, Clinical Epigenetics.

[43]  Massimo Negrini,et al.  Micromarkers: miRNAs in cancer diagnosis and prognosis , 2010, Expert review of molecular diagnostics.

[44]  H. Akaza,et al.  FOXO1 and TCF7L2 genes involved in metastasis and poor prognosis in clear cell renal cell carcinoma , 2010, Genes, chromosomes & cancer.

[45]  E. Turiel,et al.  I. INTRODUCTION , 2018, Monographs of the Society for Research in Child Development.

[46]  Shu-Guang Su,et al.  miR-107-mediated decrease of HMGCS2 indicates poor outcomes and promotes cell migration in hepatocellular carcinoma. , 2017, The international journal of biochemistry & cell biology.

[47]  H. An,et al.  Hsa-miR-1246 and hsa-miR-1290 are associated with stemness and invasiveness of non-small cell lung cancer. , 2016, Lung cancer.

[48]  Ying Ding,et al.  Applying centrality measures to impact analysis: A coauthorship network analysis , 2009, J. Assoc. Inf. Sci. Technol..

[49]  Anton J. Enright,et al.  Zebrafish MiR-430 Promotes Deadenylation and Clearance of Maternal mRNAs , 2006, Science.

[50]  Lin Chen,et al.  A social matching system : using implicit and explicit information for personalized recommendation in online dating service , 2013 .

[51]  M. Peter,et al.  Targeting of mRNAs by multiple miRNAs: the next step , 2010, Oncogene.

[52]  Daniel J. Brass,et al.  Network Analysis in the Social Sciences , 2009, Science.

[53]  Xianghuo He,et al.  Multiple microRNAs modulate p21Cip1/Waf1 expression by directly targeting its 3′ untranslated region , 2010, Oncogene.

[54]  Cunchuan Wang,et al.  MicroRNA-421 inhibits breast cancer metastasis by targeting metastasis associated 1. , 2016, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[55]  Willian A. da Silveira,et al.  Genomics pipelines and data integration: challenges and opportunities in the research setting , 2017, Expert review of molecular diagnostics.

[56]  H. White,et al.  “Structural Equivalence of Individuals in Social Networks” , 2022, The SAGE Encyclopedia of Research Design.

[57]  Sanghamitra Bandyopadhyay,et al.  Participation of microRNAs in human interactome: extraction of microRNA-microRNA regulations. , 2011, Molecular bioSystems.

[58]  Russell Bowler,et al.  The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations , 2014, Nucleic acids research.

[59]  Giancarlo Mauri,et al.  SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data , 2017, International journal of molecular sciences.

[60]  Y. Li,et al.  Downregulation of tumor suppressor menin by miR-421 promotes proliferation and migration of neuroblastoma , 2014, Tumor Biology.

[61]  Jingwu Jiang,et al.  LncRNA MEG3 inhibits cell epithelial-mesenchymal transition by sponging miR-421 targeting E-cadherin in breast cancer. , 2017, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[62]  Ligang Wu,et al.  Let me count the ways: mechanisms of gene regulation by miRNAs and siRNAs. , 2008, Molecular cell.

[63]  Cinzia Di Pietro,et al.  Specific alterations of the microRNA transcriptome and global network structure in colorectal cancer after treatment with MAPK/ERK inhibitors , 2012, Journal of Molecular Medicine.

[64]  Ligang Wu,et al.  Micro-RNA Regulation of the Mammalian lin-28 Gene during Neuronal Differentiation of Embryonal Carcinoma Cells , 2005, Molecular and Cellular Biology.

[65]  R. Gu,et al.  MicroRNA-107 Promotes Proliferation, Migration, and Invasion of Osteosarcoma Cells by Targeting Tropomyosin 1. , 2017, Oncology research.

[66]  Mark D. Robinson,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[67]  T. Rohan,et al.  Hsa‐miR‐375 is differentially expressed during breast lobular neoplasia and promotes loss of mammary acinar polarity , 2012, The Journal of pathology.

[68]  W. Guo,et al.  MiR-1297 regulates the growth, migration and invasion of colorectal cancer cells by targeting cyclo-oxygenase-2. , 2014, Asian Pacific journal of cancer prevention : APJCP.

[69]  Piet Van Mieghem,et al.  Topology of molecular interaction networks , 2013, BMC Systems Biology.

[70]  O. Sansom,et al.  Exploring molecular genetics of bladder cancer: lessons learned from mouse models , 2012, Disease Models & Mechanisms.

[71]  Nicholas T. Ingolia,et al.  Mammalian microRNAs predominantly act to decrease target mRNA levels , 2010, Nature.

[72]  Doron Betel,et al.  The microRNA.org resource: targets and expression , 2007, Nucleic Acids Res..

[73]  Dong Liu,et al.  IKKβ Enforces a LIN28B/TCF7L2 Positive Feedback Loop That Promotes Cancer Cell Stemness and Metastasis. , 2015, Cancer research.

[74]  Chao Sun,et al.  miR-103/107 promote ER stress-mediated apoptosis via targeting the Wnt3a/β-catenin/ATF6 pathway in preadipocytes , 2018, Journal of Lipid Research.

[75]  F. Jurnak,et al.  WIF1, a Wnt pathway inhibitor, regulates SKP2 and c-myc expression leading to G1 arrest and growth inhibition of human invasive urinary bladder cancer cells , 2009, Molecular Cancer Therapeutics.

[76]  Gregory J. Goodall,et al.  A network-biology perspective of microRNA function and dysfunction in cancer , 2016, Nature Reviews Genetics.

[77]  H. Pu,et al.  MicroRNA-421 promotes the proliferation and metastasis of gastric cancer cells by targeting claudin-11. , 2017, Experimental and therapeutic medicine.

[78]  Sanghyuk Lee,et al.  miRGator: an integrated system for functional annotation of microRNAs , 2007, Nucleic Acids Res..

[79]  Gabriele Sales,et al.  MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update) , 2012, Nucleic Acids Res..

[80]  Nadezhda T. Doncheva,et al.  Topological analysis and interactive visualization of biological networks and protein structures , 2012, Nature Protocols.

[81]  K. Basso,et al.  RNAs with multiple personalities , 2014, Wiley interdisciplinary reviews. RNA.

[82]  W. J. Hadden,et al.  A Comparison of , 1971 .