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Computational Biology of Non-Coding RNA pp 341–366Cite as

Quantitative Characteristic of ncRNA Regulation in Gene Regulatory Networks

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1912))

Abstract

RNA is mostly known for its role in protein synthesis, where it encodes information for protein sequence in its messenger RNA (mRNA) form (translation). Yet, RNA molecules regulate several cellular processes other than translation. Here, we present an overview of several mathematical models that help understanding and characterizing the role of noncoding RNA molecules (ncRNAs) in regulating gene expression and protein synthesis. First, we discuss relatively simple models where ncRNAs can modulate protein synthesis via targeting a mRNA. Then, we consider the case of feedback interactions between ncRNAs and their target proteins, and discuss several biological applications where these feedback architectures modulate a cellular phenotype and control the levels of intrinsic and extrinsic noise. Building from these simple circuit motifs, we examine feed-forward circuit motifs involving ncRNAs that generate precise spatial and temporal patterns of protein expression. Further, we investigate the competition between ncRNAs and other endogenous RNA molecules and show that the cross talk between coding and noncoding RNAs can form large genetic circuits that involve up to hundreds of chemical species. Finally, we discuss the role of ncRNAs in modulating cell-cell signaling pathways and therefore the dynamics of spatiotemporal pattern formation in a tissue.

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References

  1. Crick F (1970) Central dogma of molecular biology. Nature 227:561–563

    Article  CAS  PubMed  Google Scholar 

  2. Mattick JS, Makunin IV (2006) Non-coding RNA. Hum Mol Genet 15(Spec 1):17–29. https://doi.org/10.1093/hmg/ddl046

    Article  CAS  Google Scholar 

  3. Eddy SR (2001) Non-coding RNA genes and the modern RNA world. Nat Rev Genet 2:919–929. https://doi.org/10.1038/35103511

    Article  CAS  PubMed  Google Scholar 

  4. Zhdanov VP (2011) Kinetic models of gene expression including non-coding RNAs. Phys Rep 500:1–42

    Article  CAS  Google Scholar 

  5. Lai X, Wolkenhauer O, Vera J (2016) Understanding microRNA-mediated gene regulatory networks through mathematical modelling. Nucleic Acids Res 44:6019–6035

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ambros V (2004) The functions of animal microRNAs. Nature 431:350–355. https://doi.org/10.1038/nature02871

    Article  CAS  PubMed  Google Scholar 

  7. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297. https://doi.org/10.1016/S0092-8674(04)00045-5

    Article  CAS  PubMed  Google Scholar 

  8. Neema A, Dasaradhi PVN, Asif Mohmmed PM, Bhatnagar RK, SKM (2004) RNA interference: biology, mechanism, and applications. Microbiol Mol Biol Rev 38:285–294. https://doi.org/10.1128/MMBR.67.4.657

    Article  Google Scholar 

  9. Ma L, Bajic VB, Zhang Z (2013) On the classification of long non-coding RNAs. RNA Biol 10:924–933. https://doi.org/10.4161/rna.24604

    Article  CAS  PubMed Central  Google Scholar 

  10. Geisler S, Coller J (2013) RNA in unexpected places: long non-coding RNA functions in diverse cellular contexts. Nat Rev Mol Cell Biol 14:699–712. https://doi.org/10.1038/nrm3679

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gibb EA, Brown CJ, Lam WL (2011) The functional role of long non-coding RNA in human carcinomas. Mol Cancer 10:38. https://doi.org/10.1186/1476-4598-10-38

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Gutschner T, Diederichs S (2012) The hallmarks of cancer: a long non-coding RNA point of view. RNA Biol 9:703–709. https://doi.org/10.4161/rna.20481

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136:215–233. https://doi.org/10.1016/j.cell.2009.01.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ghildiyal M, Zamore PD (2009) Small silencing RNAs: an expanding universe. Nat Rev Genet 10:94–108. https://doi.org/10.1038/nrg2504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Yang E, van Nimwegen E, Zavolan M, Rajewsky N, Schroeder M, Magnasco M, Darnell JE (2003) Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes. Genome Res 13:1863–1872. https://doi.org/10.1101/gr.1272403

  16. Gottesman S (2005) Micros for microbes: non-coding regulatory RNAs in bacteria. Trends Genet 21:399–404. https://doi.org/10.1016/j.tig.2005.05.008

    Article  CAS  PubMed  Google Scholar 

  17. Storz G, Vogel J, Wassarman KM (2011) Regulation by small RNAs in bacteria: expanding frontiers. Mol Cell 43:880–891. https://doi.org/10.1016/j.molcel.2011.08.022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mitarai N, Benjamin J-AM, Krishna S, Semsey S, Csiszovszki Z, Massé E, Sneppen K (2009) Dynamic features of gene expression control by small regulatory RNAs. Proc Natl Acad Sci U S A 106:10655–10659. https://doi.org/10.1073/pnas.0901466106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Massé E, Vanderpool CK, Gottesman S (2005) Effect of RyhB small RNA on global iron use in Escherichia coli. J Bacteriol 187:6962–6971. https://doi.org/10.1128/JB.187.20.6962-6971.2005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Veĉerek B, Moll I, Bläsi U (2007) Control of Fur synthesis by the non-coding RNA RyhB and iron-responsive decoding. EMBO J 26:965–975. https://doi.org/10.1038/sj.emboj.7601553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Hansen GT, Ahmad R, Hjerde E, Fenton CG, Willassen NP, Haugen P (2012) Expression profiling reveals Spot 42 small RNA as a key regulator in the central metabolism of Aliivibrio salmonicida. BMC Genomics 13:37. https://doi.org/10.1186/1471-2164-13-37

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Semsey S, Andersson AMC, Krishna S, Jensen MH, Massé E, Sneppen K (2006) Genetic regulation of fluxes: iron homeostasis of Escherichia coli. Nucleic Acids Res 34:4960–4967. https://doi.org/10.1093/nar/gkl627

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mitarai N, Andersson AMC, Krishna S, Semsey S, Sneppen K (2007) Efficient degradation and expression prioritization with small RNAs. Phys Biol 4:164–171. https://doi.org/10.1088/1478-3975/4/3/003

    Article  CAS  PubMed  Google Scholar 

  24. Legewie S, Dienst D, Wilde A, Herzel H, Axmann IM (2008) Small RNAs establish delays and temporal thresholds in gene expression. Biophys J 95:3232–3238. https://doi.org/10.1529/biophysj.108.133819

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Shimoni Y, Friedlander G, Hetzroni G, Niv G, Altuvia S, Biham O, Margalit H (2007) Regulation of gene expression by small non-coding RNAs: a quantitative view. Mol Syst Biol 3:1–9. https://doi.org/10.1038/msb4100181

    Article  CAS  Google Scholar 

  26. Alon U (2007) Network motifs: theory and experimental approaches. Nat Rev Genet 8:450–461. https://doi.org/10.1038/nrg2102

    Article  CAS  PubMed  Google Scholar 

  27. Mangan S, Alon U (2003) Structure and function of the feed-forward loop network motif. Proc Natl Acad Sci U S A 100:11980–11985. https://doi.org/10.1073/pnas.2133841100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Levine E, Zhang Z, Kuhlman T, Hwa T (2007) Quantitative characteristics of gene regulation by small RNA. PLoS Biol 5:1998–2010. https://doi.org/10.1371/journal.pbio.0050229

    Article  CAS  Google Scholar 

  29. Levine E, Hwa T (2008) Small RNAs establish gene expression thresholds. Curr Opin Microbiol 11:574–579. https://doi.org/10.1016/j.mib.2008.09.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Levine E, Ben JE, Levine H (2007) Target-specific and global effectors in gene regulation by microRNA. Biophys J 93:L52–L54. https://doi.org/10.1529/biophysj.107.118448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Milo R, Jorgensen P, Moran U, Weber G, Springer M (2009) BioNumbers The database of key numbers in molecular and cell biology. Nucleic Acids Res 38:750–753. https://doi.org/10.1093/nar/gkp889

    Article  CAS  Google Scholar 

  32. Swain PS, Elowitz MB, Siggia ED (2002) Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc Natl Acad Sci 99:12795–12800. https://doi.org/10.1073/pnas.162041399

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297:1183–1186

    Article  CAS  PubMed  Google Scholar 

  34. Raser JM, O’Shea EK (2010) Noise in gene expression. Science 309:2010–2014. https://doi.org/10.1126/science.1105891

    Article  CAS  Google Scholar 

  35. Schwanhüusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Selbach M (2011) Global quantification of mammalian gene expression control. Nature 473:337–342. https://doi.org/10.1038/nature10098

    Article  CAS  Google Scholar 

  36. Jia Y, Liu W, Li A, Yang L, Zhan X (2009) Intrinsic noise in post-transcriptional gene regulation by small non-coding RNA. Biophys Chem 143:60–69. https://doi.org/10.1016/j.bpc.2009.04.001

    Article  CAS  PubMed  Google Scholar 

  37. Elgart V, Jia T, Kulkarni RV (2010) Applications of Little’s Law to stochastic models of gene expression. Phys Rev E Stat Nonlinear Soft Matter Phys 82:1–6. https://doi.org/10.1103/PhysRevE.82.021901

    Article  CAS  Google Scholar 

  38. Elgart V, Jia T, Kulkarni R (2010) Quantifying mRNA synthesis and decay rates using small RNAs. Biophys J 98:2780–2784. https://doi.org/10.1016/j.bpj.2010.03.022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhdanov VP (2009) Conditions of appreciable influence of microRNA on a large number of target mRNAs. Mol BioSyst 5:638. https://doi.org/10.1039/b808095j

    Article  CAS  PubMed  Google Scholar 

  40. Jost D, Nowojewski A, Levine E (2013) Regulating the many to benefit the few: role of weak small RNA targets. Biophys J 104:1773–1782. https://doi.org/10.1016/j.bpj.2013.02.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Shalgi R, Lieber D, Oren M, Pilpel Y (2007) Global and local architecture of the mammalian microRNA-transcription factor regulatory network. PLoS Comput Biol 3:1291–1304. https://doi.org/10.1371/journal.pcbi.0030131

    Article  CAS  Google Scholar 

  42. Wu S, Huang S, Ding J, Zhao Y, Liang L, Liu T, Zhan R, He X (2010) Multiple microRNAs modulate p21Cip1/Waf1 expression by directly targeting its 3′ untranslated region. Oncogene 29:2302–2308. https://doi.org/10.1038/onc.2010.34

    Article  CAS  PubMed  Google Scholar 

  43. Lai X, Schmitz U, Gupta SK, Bhattacharya A, Kunz M, Wolkenhauer O, Vera J (2012) Computational analysis of target hub gene repression regulated by multiple and cooperative miRNAs. Nucleic Acids Res 40:8818–8834. https://doi.org/10.1093/nar/gks657

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Lai X, Bhattacharya A, Schmitz U, Kunz M, Vera J, Wolkenhauer O (2013) A systems’ biology approach to study microrna-mediated gene regulatory networks. Biomed Res Int 2013:703849. https://doi.org/10.1155/2013/703849

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Doench JG, Sharp PA (2004) Specificity of microRNA target selection in translational repression. Genes (Basel) 504:504–511. https://doi.org/10.1101/gad.1184404.species

    Article  Google Scholar 

  46. Sætrom P, Heale BSE, Snøve O, Aagaard L, Alluin J, Rossi JJ (2007) Distance constraints between microRNA target sites dictate efficacy and cooperativity. Nucleic Acids Res 35:2333–2342. https://doi.org/10.1093/nar/gkm133

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK (2014) Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Nucleic Acids Res 42:7539–7552. https://doi.org/10.1093/nar/gku465

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lu M, Jolly MK, Levine H, Onuchic JN, Ben-Jacob E (2013) MicroRNA-based regulation of epithelial-hybrid-mesenchymal fate determination. Proc Natl Acad Sci U S A 110:18174–18179. https://doi.org/10.1073/pnas.1318192110

    Article  Google Scholar 

  49. Vasudevan S, Tong Y, Steitz JA (2007) Switching from repression to activation: MicroRNAs can up-regulate translation. Science 318:1931–1934

    Article  CAS  PubMed  Google Scholar 

  50. Ghosh T, Soni K, Scaria V, Halimani M, Bhattacharjee C, Pillai B (2008) MicroRNA-mediated up-regulation of an alternatively polyadenylated variant of the mouse cytoplasmic β-actin gene. Nucleic Acids Res 36:6318–6332. https://doi.org/10.1093/nar/gkn624

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Ma F, Liu X, Li D, Wang P, Li N, Lu L, Cao X (2010) MicroRNA-466l upregulates IL-10 expression in TLR-triggered macrophages by antagonizing RNA-binding protein tristetraprolin-mediated IL-10 mRNA degradation. J Immunol 184:6053–6059. https://doi.org/10.4049/jimmunol.0902308

    Article  CAS  PubMed  Google Scholar 

  52. Gokhale SA, Gadgil CJ (2012) Analysis of miRNA regulation suggests an explanation for ‘unexpected’ increase in target protein levels. Mol BioSyst 8:760–765. https://doi.org/10.1039/C1MB05368J

    Article  CAS  PubMed  Google Scholar 

  53. Zhdanov VP (2010) ncRNA-mediated bistability in the synthesis of hundreds of distinct mRNAs and proteins. Phys A Stat Mech Appl 389:887–890. https://doi.org/10.1016/j.physa.2009.11.028

    Article  CAS  Google Scholar 

  54. Zhdanov VP (2010) Effect of non-coding RNA on bistability and oscillations in the mRNA-protein interplay. Biophys Rev Lett 05:89–107

    Article  CAS  Google Scholar 

  55. Zhdanov VP (2006) Transient stochastic bistable kinetics of gene transcription during the cellular growth. Chem Phys Lett 424:394–398. https://doi.org/10.1016/j.cplett.2006.05.024

    Article  CAS  Google Scholar 

  56. Tian XJ, Zhang H, Xing J (2013) Coupled reversible and irreversible bistable switches underlying TGFβ-induced epithelial to mesenchymal transition. Biophys J 105:1079–1089. https://doi.org/10.1016/j.bpj.2013.07.011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Nieto MA, Huang RY, Jackson RA, Thiery JP (2016) EMT: 2016. Cell 166:21–45

    Article  CAS  PubMed  Google Scholar 

  58. Jolly MK, Boareto M, Huang B, Jia D, Lu M, Ben-Jacob E, Onuchic JN, Levine H (2015) Implications of the hybrid epithelial/mesenchymal phenotype in metastasis. Front Oncol 5:155. https://doi.org/10.3389/fonc.2015.00155

    Article  PubMed  PubMed Central  Google Scholar 

  59. Yang X, Lin X, Zhong X, Kaur S, Li N, Liang S, Lassus H, Wang L, Katsaros D, Montone K, Zhao X, Zhang Y, Bützow R, Coukos G, Zhang L (2010) Double-negative feedback loop between reprogramming factor LIN28 and microRNA let-7 regulates aldehyde dehydrogenase 1-positive cancer stem cells. Cancer Res 70:9463–9472. https://doi.org/10.1158/0008-5472.CAN-10-2388

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Jolly MK, Huang B, Lu M, Mani SA, Levine H, Ben-Jacob E (2014) Towards elucidating the connection between epithelial--mesenchymal transitions and stemness. J R Soc Interface 11:20140962

    Article  PubMed  PubMed Central  Google Scholar 

  61. Jolly MK, Jia D, Boareto M, Mani SA, Pienta KJ, Ben-Jacob E, Levine H (2015) Coupling the modules of EMT and stemness: a tunable ‘stemness window’model. Oncotarget 6:25161–25174

    Article  PubMed  PubMed Central  Google Scholar 

  62. Hafner M, Max KEA, Bandaru P, Morozov P, Gerstberger S, Brown M, Molina H, Tuschl T (2013) Identification of mRNAs bound and regulated by human LIN28 proteins and molecular requirements for RNA recognition. RNA 19:613–626. https://doi.org/10.1261/rna.036491.112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Wilbert ML, Huelga SC, Kapeli K, Stark TJ, Liang TY, Chen SX, Yan BY, Nathanson JL, Hutt KR, Lovci MT, Kazan H, Vu AQ, Massirer KB, Morris Q, Hoon S, Yeo GW (2012) LIN28 binds messenger RNAs at GGAGA motifs and regulates splicing factor abundance. Mol Cell 48:195–206. https://doi.org/10.1016/j.molcel.2012.08.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Zisoulis DG, Kai ZS, Chang RK, Pasquinelli AE (2012) Autoregulation of microRNA biogenesis by let-7 and Argonaute. Nature 486:541–544. https://doi.org/10.1038/nature11134

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Emmrich S, Pützer BM (2010) Checks and balances: E2F – MicroRNA crosstalk in cancer control. Cell Cycle 9:2555–2567. https://doi.org/10.4161/cc.9.13.12061

    Article  CAS  PubMed  Google Scholar 

  66. Concepcion CP, Bonetti C, Ventura A (2012) The MicroRNA-17-92 family of MicroRNA clusters in development and disease. Cancer J (United States) 18:262–267. https://doi.org/10.1097/PPO.0b013e318258b60a

    Article  CAS  Google Scholar 

  67. Aguda BD, Kim Y, Piper-Hunter MG, Friedman A, Marsh CB (2008) MicroRNA regulation of a cancer network: consequences of the feedback loops involving miR-17-92, E2F, and Myc. Proc Natl Acad Sci 105:19678–19683. https://doi.org/10.1073/pnas.0811166106

    Article  PubMed  PubMed Central  Google Scholar 

  68. Zhang H, Chen Y, Chen Y (2012) Noise propagation in gene regulation networks involving interlinked positive and negative feedback loops. PLoS One 7:1–8. https://doi.org/10.1371/journal.pone.0051840

    Article  CAS  Google Scholar 

  69. Li Y, Li Y, Zhang H, Chen Y (2011) Microrna-mediated positive feedback loop and optimized bistable switch in a cancer network involving miR-17-92. PLoS One 6:2–10. https://doi.org/10.1371/journal.pone.0026302

    Article  CAS  Google Scholar 

  70. Giampieri E, Remondini D, de Oliveira L, Castellani G, Lió P (2011) Stochastic analysis of a miRNA-protein toggle switch. Mol BioSyst 7:2796–2803. https://doi.org/10.1039/c1mb05086a

    Article  CAS  PubMed  Google Scholar 

  71. Tsang J, Zhu J, van Oudenaarden A (2007) MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals. Mol Cell 26:753–767. https://doi.org/10.1016/j.molcel.2007.05.018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Re A, Cora D, Taverna D, Caselle M (2009) Genome-wide survey of MicroRNA – transcription factor feed-forward regulatory circuits in human. BMC Bioinformatics 5:51. https://doi.org/10.1039/b900177h

    Article  CAS  Google Scholar 

  73. Wall ME, Dunlop MJ, Hlavacek WS (2005) Multiple functions of a feed-forward-loop gene circuit. J Mol Biol 349:501–514. https://doi.org/10.1016/j.jmb.2005.04.022

    Article  CAS  PubMed  Google Scholar 

  74. Herranz H, Cohen SM (2010) MicroRNAs and gene regulatory networks: managing the impact of noise in biological systems. Genes Dev 24:1339–1344. https://doi.org/10.1101/gad.1937010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Shalgi R, Brosh R, Oren M, Pilpel Y, Rotter V (2009) Coupling transcriptional and post-transcriptional miRNA regulation in the control of cell fate. Aging (Albany NY) 1:762–770

    Article  CAS  Google Scholar 

  76. Kobayashi K, Sakurai K, Hiramatsu H, Inada KI, Shiogama K, Nakamura S, Suemasa F, Kobayashi K, Imoto S, Haraguchi T, Ito H, Ishizaka A, Tsutsumi Y, Iba H (2015) The miR-199a/Brm/EGR1 axis is a determinant of anchorage-independent growth in epithelial tumor cell lines. Sci Rep 5:8428. https://doi.org/10.1038/srep08428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Taulli R, Loretelli C, Pandolfi PP (2013) From pseudo-ceRNAs to circ-ceRNAs: a tale of cross-talk and competition. Nat Struct Mol Biol 20:541–543. https://doi.org/10.1038/nsmb2580

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Tay Y, Rinn J, Pandolfi PP (2014) The multilayered complexity of ceRNA crosstalk and competition. Nature 505:344–352. https://doi.org/10.1038/nature12986

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Kartha RV, Subramanian S (2014) Competing endogenous RNAs (ceRNAs): new entrants to the intricacies of gene regulation. Front Genet 5:1–9. https://doi.org/10.3389/fgene.2014.00008

    Article  CAS  Google Scholar 

  80. Ebert MS, Sharp PA (2012) Roles for MicroRNAs in conferring robustness to biological processes. Cell 149:505–524. https://doi.org/10.1016/j.cell.2012.04.005

    Article  CAS  Google Scholar 

  81. Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP (2011) A ceRNA hypothesis: the rosetta stone of a hidden RNA language? Cell 146:353–358. https://doi.org/10.1016/j.cell.2011.07.014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Ala U, Karreth FA, Bosia C, Pagnani A, Taulli R, Leopold V, Tay Y, Provero P, Zecchina R, Pandolfi PP (2013) Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments. Proc Natl Acad Sci U S A 110:7154–7159. https://doi.org/10.1073/pnas.1222509110

    Article  PubMed  PubMed Central  Google Scholar 

  83. Bosia C, Pagnani A, Zecchina R (2013) Modelling competing endogenous RNA networks. PLoS One 8:e66609. https://doi.org/10.1371/journal.pone.0066609

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Martirosyan A, Figliuzzi M, Marinari E, De Martino A (2016) Probing the limits to MicroRNA-mediated control of gene expression. PLoS Comput Biol 12:1–23. https://doi.org/10.1371/journal.pcbi.1004715

    Article  CAS  Google Scholar 

  85. Gérard C, Novák B (2013) microRNA as a potential vector for the propagation of robustness in protein expression and oscillatory dynamics within a ceRNA network. PLoS One 8:e83372. https://doi.org/10.1371/journal.pone.0083372

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Pedraza JM, van Oudenaarden A (2005) Noise propagation in gene networks. Science 307:1965–1970

    Article  CAS  PubMed  Google Scholar 

  87. Skalsky RL, Cullen BR (2010) Viruses, microRNAs, and host interactions. Annu Rev Microbiol 64:123–141. https://doi.org/10.1146/annurev.micro.112408.134243

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Grundhoff A, Sullivan CS (2011) Virus-encoded microRNAs. Virology 411:325–343. https://doi.org/10.1016/j.virol.2011.01.002

    Article  CAS  PubMed  Google Scholar 

  89. Cullen BR (2009) Viral and cellular messenger RNA targets of viral microRNAs. Nature 457:421–425. https://doi.org/10.1038/nature07757

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. McCaskill J, Praihirunkit P, Sharp PM, Buck AH (2015) RNA-mediated degradation of microRNAs: a widespread viral strategy? RNA Biol 12:579–585. https://doi.org/10.1080/15476286.2015.1034912

    Article  PubMed  PubMed Central  Google Scholar 

  91. Luna JM, Scheel TKH, Danino T, Shaw KS, Mele A, Fak JJ, Nishiuchi E, Takacs CN, Catanese MT, De Jong YP, Jacobson IM, Rice CM, Darnell RB (2015) Hepatitis C virus RNA functionally sequesters miR-122. Cell 160:1099–1110. https://doi.org/10.1016/j.cell.2015.02.025

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Bray SJ (2006) Notch signalling: a simple pathway becomes complex. Nat Rev Mol Cell Biol 7:678–689. https://doi.org/10.1038/nrm2009

    Article  CAS  PubMed  Google Scholar 

  93. Andersson ER, Sandberg R, Lendahl U (2011) Notch signaling: simplicity in design, versatility in function. Development 138:3593–3612

    Article  CAS  PubMed  Google Scholar 

  94. Bolos V, Grego-Bessa J, De La Pompa JL (2007) Notch signaling in development and cancer. Endocr Rev 28:339–363. https://doi.org/10.1210/er.2006-0046

    Article  PubMed  Google Scholar 

  95. Gerdes HH, Rustom A, Wang X (2013) Tunneling nanotubes, an emerging intercellular communication route in development. Mech Dev 130:381–387. https://doi.org/10.1016/j.mod.2012.11.006

    Article  CAS  PubMed  Google Scholar 

  96. Gerdes HH, Bukoreshtliev NV, Barroso JFV (2007) Tunneling nanotubes: a new route for the exchange of components between animal cells. FEBS Lett 581:2194–2201. https://doi.org/10.1016/j.febslet.2007.03.071

    Article  CAS  PubMed  Google Scholar 

  97. Théry C, Zitvogel L, Amigorena S (2002) Exosomes: composition, biogenesis and function. Nat Rev Immunol 2:569–579. https://doi.org/10.1038/nri855

    Article  CAS  PubMed  Google Scholar 

  98. Raposo G, Stoorvogel W (2013) Extracellular vesicles: exosomes, microvesicles, and friends. J Cell Biol 200:373–383. https://doi.org/10.1083/jcb.201211138

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Shaya O, Sprinzak D (2011) From Notch signaling to fine-grained patterning: modeling meets experiments. Curr Opin Genet Dev 21:732–739

    Article  CAS  PubMed  Google Scholar 

  100. Beatus P, Lendahl U (1998) Notch and neurogenesis. J Neurosci Res 54:125–136. https://doi.org/10.1002/(SICI)1097-4547(19981015)54:2<125::AID-JNR1>3.0.CO;2-G

    Article  CAS  PubMed  Google Scholar 

  101. Boareto M, Jolly MK, Lu M, Onuchic JN, Clementi C, Ben-Jacob E (2015) Jagged--Delta asymmetry in Notch signaling can give rise to a Sender/Receiver hybrid phenotype. Proc Natl Acad Sci U S A 112:402–409

    Article  Google Scholar 

  102. Jolly MK, Boareto M, Lu M, Onuchic JN, Clementi C, Ben-Jacob E, Jose’N O, Clementi C, Ben-Jacob E (2015) Operating principles of Notch--Delta--Jagged module of cell--cell communication. New J Phys 17:55021

    Article  Google Scholar 

  103. Hartman BH, Reh TA, Bermingham-McDonogh O (2010) Notch signaling specifies prosensory domains via lateral induction in the developing mammalian inner ear. Proc Natl Acad Sci U S A 107:15792–15797

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Chen JS, Gumbayan AM, Zeller RW, Mahaffy JM (2014) An expanded Notch-Delta model exhibiting long-range patterning and incorporating MicroRNA regulation. PLoS Comput Biol 10:e1003655. https://doi.org/10.1371/journal.pcbi.1003655

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Goodfellow M, Phillips NE, Manning C, Galla T, Papalopulu N (2014) MicroRNA input into a neural ultradian oscillator controls emergence and timing of alternative cell states. Nat Commun 5:1–10. https://doi.org/10.1038/ncomms4399

    Article  CAS  Google Scholar 

  106. Roese-Koerner B, Stappert L, Brüstle O (2017) Notch/Hes signaling and miR-9 engage in complex feedback interactions controlling neural progenitor cell proliferation and differentiation. Neurogenesis 4:e1313647. https://doi.org/10.1080/23262133.2017.1313647

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Boareto M, Jolly MK, Goldman A, Pietilä M, Mani SA, Sengupta S, Ben-Jacob E, Levine H, Jose’N O (2016) Notch-Jagged signalling can give rise to clusters of cells exhibiting a hybrid epithelial/mesenchymal phenotype. J R Soc Interface 13:20151106

    Article  PubMed  PubMed Central  Google Scholar 

  108. Fabisiewicz A, Grzybowska E, Grybowska E (2017) CTC clusters in cancer progression and metastasis. Med Oncol 34:12

    Article  PubMed  Google Scholar 

  109. Bocci F, Jolly MK, Tripathi SC, Aguilar M, Onuchic N, Hanash SM, Levine H, Levine H (2017) Numb prevents a complete epithelial – mesenchymal transition by modulating Notch signalling. J R Soc Interface 14:20170512

    Article  PubMed  PubMed Central  Google Scholar 

  110. Jolly MK, Tripathi SC, Jia D, Mooney SM, Celiktas M, Hanash SM, Mani SA, Pienta KJ, Ben-Jacob E, Levine H (2016) Stability of the hybrid epithelial/mesenchymal phenotype. Oncotarget 7:27067–27084. https://doi.org/10.18632/oncotarget.8166

    Article  PubMed  PubMed Central  Google Scholar 

  111. Bocci F, Jolly MK, George J, Levine H, Onuchic JN (2018) A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling. Oncotarget 9:29906–29920. https://doi.org/10.1101/314187

  112. Bocci F, Gearhart-Serna L, Boareto M, Ribeiro M, Ben-Jacob E, Devi GR, Levine H, Onuchic JN, Jolly MK (2018) Towards understanding cancer stem cell heterogeneity in the tumor microenvironment. BiorXiv https://doi.org/10.1101/408823

  113. Bocci F, Levine H, Onuchic JN, Jolly MK (2018) Deciphering the dynamics of Epithelial-Mesenchymal Transition and Cancer Stem Cells in tumor progression. Arxiv https://arxiv.org/pdf/1808.09113

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Authors and Affiliations

  1. Center for Theoretical Biological Physics, Rice University, Houston, TX, USA

    Federico Bocci, Mohit Kumar Jolly, Herbert Levine & José Nelson Onuchic

  2. Department of Chemistry, Rice University, Houston, TX, USA

    Federico Bocci, Herbert Levine & José Nelson Onuchic

  3. Department of Bioengineering, Rice University, Houston, TX, USA

    Herbert Levine

  4. Department of Physics and Astronomy, Rice University, Houston, TX, USA

    Herbert Levine & José Nelson Onuchic

  5. Department of Biosciences, Rice University, Houston, TX, USA

    José Nelson Onuchic

Authors
  1. Federico Bocci
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  2. Mohit Kumar Jolly
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  3. Herbert Levine
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  4. José Nelson Onuchic
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Corresponding authors

Correspondence to Herbert Levine or José Nelson Onuchic .

Editor information

Editors and Affiliations

  1. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Xin Lai

  2. Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany

    Shailendra K. Gupta

  3. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Julio Vera

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Bocci, F., Jolly, M.K., Levine, H., Onuchic, J.N. (2019). Quantitative Characteristic of ncRNA Regulation in Gene Regulatory Networks. In: Lai, X., Gupta, S., Vera, J. (eds) Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8982-9_14

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  • DOI: https://doi.org/10.1007/978-1-4939-8982-9_14

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  • Publisher Name: Humana Press, New York, NY

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  • Online ISBN: 978-1-4939-8982-9

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