Skip to main content
SpringerLink
Log in

Topological Structure and Biological Function of Gene Network Regulated by MicroRNA

  • Chapter
  • First Online:
MicroRNA Regulatory Network: Structure and Function

  • 419 Accesses

Abstract

The physiological phenomena emerging from biological systems are closely related to the topological structure of biological systems. This chapter deals with the topological structure and biological function of gene network regulated by microRNA. MicroRNAs are a class of small endogenous noncoding RNAs, which regulate stability or translation of mRNA transcripts at the posttranscriptional level. Section 2.1 introduces the topological structure of biological network, from the topological classification and structure to its biological function. We give some network motifs in transcription networks and discuss their functions. Some important network motifs have defined information processing functions and significant patterns. Section 2.2 describes the network topologies involving microRNA that can achieve biological function by a mathematical model of the MFL. We construct a general computational model of the MFL based on biochemical regulations in this section. Detailed dynamical analysis of the model reveals that there exist wide ranges of kinetic parameters where the MFL can behave as bistable switches (oscillators). These functional features are consistent with the widespread appearance of miRNAs in fate decisions such as proliferation, differentiation, and apoptosis during development.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alon U. An introduction to systems biology: design principles of biological circuits. Boca Raton: CRC Press; 2007.

    Google Scholar 

  2. Ingolia NT. Cell Cycle: bistability is needed for robust cycling. Curr Biol. 2005;15(23):R961–3.

    Article  CAS  Google Scholar 

  3. Ingolia NT, Murray AW. Positive-feedback loops as a flexible biological module. Curr Biol. 2007;17:668–77.

    Article  CAS  Google Scholar 

  4. Lee Y, Jeon K, Lee JT, Kim S, Kim VN. MicroRNA maturation: stepwise processing and subcellular localization. EMBO J. 2002;21(17):4663–70.

    Article  CAS  Google Scholar 

  5. Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U. Network motifs: simple building blocks of complex networks. Science. 2002;298(5594):824–7.

    Article  CAS  Google Scholar 

  6. Mangan S, Alon U. Structure and function of the feed-forward loop network motif. Proc Natl Acad Sci. 2003;100(21):11980–5.

    Article  CAS  Google Scholar 

  7. Bennett MA, Shern JF, Kahn RA. Reverse two-hybrid techniques in the yeast Saccharomyces cerevisiae. In: Protein-protein interactions: Humana Press; 2004. p. 313–26.

    Google Scholar 

  8. Mangan PR, Harrington LE, O’quinn DB, Helms WS, Bullard DC, Elson CO, et al. Transforming growth factor-β induces development of the T H 17 lineage. Nature. 2006;441(7090):231.

    Article  CAS  Google Scholar 

  9. Kalir S, Mangan S, Alon U. A coherent feed-forward loop with a SUM input function prolongs flagella expression in Escherichia coli. Mol Syst Biol. 2005;(1):1.

    Article  Google Scholar 

  10. Basu U, et al. Reverse genetic analysis of the glutathione metabolic pathway suggests a novel role of PHGPX and URE2 genes in aluminum resistance in Saccharomyces cerevisiae. Mol Gen Genomics. 2004;271(5):627–37.

    Article  CAS  Google Scholar 

  11. Ptashne M, Gann A. Genes and signals: Cold Spring Harbor Laboratory Press; 2002.

    Google Scholar 

  12. Conant GC, Wagner A. Convergent evolution of gene circuits. Nat Genet. 2003;34(3):264–6.

    Article  CAS  Google Scholar 

  13. Babu P, et al. Akr1p-dependent palmitoylation of Yck2p yeast casein kinase 1 is necessary and sufficient for plasma membrane targeting. J Biol Chem. 2004;279(26):27138–47.

    Article  CAS  Google Scholar 

  14. Wang E, Purisima E. Network motifs are enriched with transcription factors whose transcripts have short half-lives. Trends Genet. 2005;21(9):492–5.

    Article  Google Scholar 

  15. Hayot F, Jayaprakash C. A feedforward loop motif in transcriptional regulation: induction and repression. J Theor Biol. 2005;234(1):133–43.

    Article  CAS  Google Scholar 

  16. Ishihara S, et al. Cross talking of network motifs in gene regulation that generates temporal pulses and spatial stripes. Genes Cells. 2005;10(11):1025–38.

    Article  CAS  Google Scholar 

  17. Shimoni Y, Friedlander G, Hetzroni G, et al. Regulation of gene expression by small non−coding RNAs: a quantitative view. Mol Syst Biol. 2014;3(1):138.

    Google Scholar 

  18. Hwang HW, Mendell JT. MicroRNAs in cell proliferation, cell death, and tumorigenesis. Br J Cancer. 2006;94(6):776–80.

    Article  CAS  Google Scholar 

  19. Inui M, Martello G, Piccolo S. MicroRNA control of signal transduction. Nat Rev Mol Cell Biol. 2010;11(4):252–63.

    Article  CAS  Google Scholar 

  20. Esquelakerscher A, Slack FJ. Oncomirs – microRNAs with a role in cancer. Nat Rev Cancer. 2006;6(4):259–69.

    Article  CAS  Google Scholar 

  21. Garzon R, Calin GA, Croce CM. MicroRNAs in cancer. Annu Rev Med. 2009;60(1):167–79.

    Article  CAS  Google Scholar 

  22. Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. Cell. 2012;148(6):1172–87.

    Article  CAS  Google Scholar 

  23. Nana−Sinkam SP, Croce CM. Clinical applications for microRNAs in cancer. Clin Pharmacol Ther. 2013;93(1):98–104.

    Article  Google Scholar 

  24. Ambros V. The functions of animal microRNAs. Nature. 2004;431(7006):350–5.

    Article  CAS  Google Scholar 

  25. Bushati N, Cohen SM. microRNA functions. Annu Rev Cell Dev Biol. 2007;23(23):175.

    Article  CAS  Google Scholar 

  26. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116:281–97.

    Article  CAS  Google Scholar 

  27. Valencia-Sanchez MA, Liu J, Hannon GJ, et al. Control of translation and mRNA degradation by miRNAs and siRNAs. Genes Dev. 2006;20(5):515–24.

    Article  CAS  Google Scholar 

  28. Guo H, Ingolia NT, Weissman JS, et al. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature. 2010;466(7308):835–40.

    Article  CAS  Google Scholar 

  29. Wang S, Raghavachari S. Quantifying negative feedback regulation by micro-RNAs. Phys Biol. 2011;8(5):055002.

    Article  Google Scholar 

  30. Maute RL, Dalla-Favera R, Basso K. RNAs with multiple personalities. Wiley Interdiscip Rev Rna. 2013;5(1):1–13.

    Article  Google Scholar 

  31. Kozomara A, Griffiths-Jones S. RBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acid Res. 2013;42(Database issue):D68–D73.

    PubMed  Google Scholar 

  32. Lai X, Wolkenhauer O, Vera J. Understanding microRNA-mediated gene regulatory networks through mathematical modelling. Nucleic Acids Res. 2016;25(11):gkw550.

    Google Scholar 

  33. Tsang J, Zhu J, Oudenaarden AV. MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals. Mol Cell. 2007;26(5):753–67.

    Article  CAS  Google Scholar 

  34. Shalgi R, Lieber D, Oren M, et al. Global and local architecture of the mammalian microRNA-transcription factor regulatory network. Plos Comput Biol. 2007;3(7):e131.

    Article  Google Scholar 

  35. Re A, Corá D, Taverna D, et al. Genome-wide survey of microRNA-transcription factor feed-forward regulatory circuits in human. Mol Biosyst. 2009;5(8):854–67.

    Article  CAS  Google Scholar 

  36. Martinez NJ, Ow MC, Barrasa MI, et al. A C. elegans genome-scale microRNA network contains composite feedback motifs with high flux capacity. Genes Dev. 2008;22(18): 2535–49.

    Article  CAS  Google Scholar 

  37. Martinez NJ, Walhout AJ. The interplay between transcription factors and microRNAs in genome-scale regulatory networks. Bioessays. 2010;31(4):435–45.

    Article  Google Scholar 

  38. Yu X, Lin J, Zack DJ, et al. Analysis of regulatory network topology reveals functionally distinct classes of microRNAs. Nucleic Acids Res. 2008;36(20):6494–503.

    Article  CAS  Google Scholar 

  39. Ivey KN, Srivastava D. MicroRNAs as regulators of differentiation and cell fate decisions. Cell Stem Cell. 2010;7(1):31–5.

    Article  Google Scholar 

  40. Johnston RJ Jr, Chang S, Etchberger JF, et al. MicroRNAs acting in a double-negative feedback loop to control a neuronal cell fate decision. Proc Natl Acad Sci USA. 2005;102(35):12449–54.

    Article  CAS  Google Scholar 

  41. Kim J, Inoue K, Ishii J, et al. A microRNA feedback circuit in midbrain dopamine neurons. Science. 2007;317(5842):1220–4.

    Article  CAS  Google Scholar 

  42. Fazi F, Rosa A, Fatica A, et al. A minicircuitry comprised of microRNA-223 and transcription factors NFI-A and C/EBPalpha regulates human granulopoiesis. Cell. 2005;123(5):819–31.

    Article  CAS  Google Scholar 

  43. Li X, Carthew ARW. A microRNA mediates EGF receptor signaling and promotes photoreceptor differentiation in the eye. Cell. 2005;123(7):1267–77.

    Article  CAS  Google Scholar 

  44. Visvanathan J, Lee S, Lee B, et al. The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development. Genes Dev. 2007;21(7):744.

    Article  CAS  Google Scholar 

  45. Bracken CP, Gregory PA, Kolesnikoff N, et al. A double-negative feedback loop between ZEB1-SIP1 and the microRNA-200 family regulates epithelial-mesenchymal transition. Cancer Res. 2008;68(19):7846–54.

    Article  CAS  Google Scholar 

  46. Xu N, Papagiannakopoulos T, Pan G, et al. MicroRNA-145 regulates OCT4, SOX2, and KLF4 and represses pluripotency in human embryonic stem cells. Cell. 2009;137(4):647–58.

    Article  CAS  Google Scholar 

  47. Juan AH, Kumar RM, Marx JG, et al. Mir-214-dependent regulation of the polycomb protein Ezh2 in skeletal muscle and embryonic stem cells. Mol Cell. 2009;36(1):61–74.

    Article  CAS  Google Scholar 

  48. Zhao C, Sun GQ, Li S, et al. A feedback regulatory loop involving microRNA-9 and nuclear receptor TLX in neural stem cell fate determination. Nat Struct Mol Biol. 2009;16(4):365–71.

    Article  CAS  Google Scholar 

  49. Pospisil V, Vargova K, Kokavec J, et al. Epigenetic silencing of the oncogenic miR-17–92 cluster during PU.1-directed macrophage differentiation. Embo J. 2014;30(21):4450–64.

    Article  Google Scholar 

  50. Zhao H, Kalota A, Jin S, et al. The c-myb proto-oncogene and microRNA-15a comprise an active autoregulatory feedback loop in human hematopoietic cells. Blood. 2009;113(3):505–16.

    Article  CAS  Google Scholar 

  51. Yu Z, Wang C, Wang M, et al. A cyclin D1/microRNA 17/20 regulatory feedback loop in control of breast cancer cell proliferation. J Cell Biol. 2008;182(3):509–17.

    Article  CAS  Google Scholar 

  52. Shenorr SS, Milo R, Mangan S, et al. Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet. 2002;31(1):64–8.

    Article  CAS  Google Scholar 

  53. Tong IL, Rinaldi NJ, Robert F, et al. Transcriptional regulatory networks in saccharomyces cerevisiae. Science. 2002;298(5594):799–804.

    Article  Google Scholar 

  54. Stamoulis C, Richardson AG. Mechanisms generating bistability and oscillations in microRNA-mediated motifs. Phys Rev E Stat Nonlin Soft Matter Phys. 2012;85(4 Pt 1):041916.

    Google Scholar 

  55. Gardner TS, Cantor CR, Collins JJ. Construction of a genetic toggle switch in Escherichia coli. Nature. 2000;403(6767):339.

    Article  CAS  Google Scholar 

  56. Ozbudak EM, Thattai M, Han NL, et al. Multistability in the lactose utilization network of Escherichia coli. Nature. 2004;427(6976):737–40.

    Article  CAS  Google Scholar 

  57. Ferrell JE Jr. Self-perpetuating states in signal transduction: positive feedback, double-negative feedback and bistability. Curr Opin Cell Biolo. 2002;14(2):140–8.

    Article  CAS  Google Scholar 

  58. Ferrell JE, Xiong W. Bistability in cell signaling: how to make continuous processes discontinuous, and reversible processes irreversible. Chaos Interdiscip J Nonlinear Sci. 2001;11(1):227–36.

    Article  CAS  Google Scholar 

  59. Novák B, Tyson JJ. Design principles of biochemical oscillators. Nat Rev Mol Cell Biol. 2008;9(12):981–91.

    Article  Google Scholar 

  60. François P, Hakim V. Core genetic module: the mixed feedback loop. Phys Rev E. 2005;72(1):031908.

    Article  Google Scholar 

  61. Liu D, Chang X, Liu Z, et al. Bistability and oscillations in gene regulation mediated by small noncoding RNAs. Plos One. 2011;6(3):e17029.

    Article  CAS  Google Scholar 

  62. Wang Y, Liu CL, Storey JD, et al. Precision and functional specificity in mRNA decay. Proc Natl Acad Sci USA. 2002;99(9):5860–5.

    Article  CAS  Google Scholar 

  63. Kaern M, Elston tc, Blake WJ, et al. Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet. 2005;6(6):451.

    Article  Google Scholar 

  64. Glickman MH, Ciechanover A. The ubiquitin-proteasome proteolytic pathway: destruction for the sake of construction. Physiol Rev. 2002;82(2):373–428.

    Article  CAS  Google Scholar 

  65. Khanin R, Vinciott V. Computational modeling of post-transcriptional gene regulation by microRNAs. J Comput Biol J Comput Mol Cell Biol. 2008;15(3):305.

    Article  CAS  Google Scholar 

  66. Aguda BD, Kim Y, Piper-Hunter MG, et al. MicroRNA regulation of a cancer network: consequences of the feedback loops involving miR-17–92, E2F, and Myc. Proc Natl Acad Sci USA. 2008;105(50):19678–83.

    Article  CAS  Google Scholar 

  67. Levine E, Zhang Z, Kuhlman T, et al. Quantitative characteristics of gene regulation by small RNA. Plos Biol. 2008;6(1):e229.

    Article  Google Scholar 

  68. Levine E, Hwa T. Small RNAs establish gene expression thresholds. Curr Opin Microbiol. 2008;11(6):574–9.

    Article  CAS  Google Scholar 

  69. Tyson JJ, Chen KC, Novak B. Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Cell Biol. 2003;15:221–31.

    CAS  Google Scholar 

  70. Ferrell J Jr, Machleder EM. The biochemical basis of an all-or-none cell fate switch in Xenopus oocytes. Science. 1998;280(5365):895.

    Article  CAS  Google Scholar 

  71. Xie ZR, Yang HT, Liu WC, et al. The role of microRNA in the delayed negative feedback regulation of gene expression. Biochem Biophys Res Commun. 2007;358(3):722–6.

    Article  CAS  Google Scholar 

  72. Lipshtat A, Loinger A, Balaban NQ, et al. Genetic toggle switch without cooperative binding. Phys Rev Lett. 2006;96(18):188101.

    Article  Google Scholar 

  73. Mengel B, Hunziker A, Pedersen L, et al. Modeling oscillatory control in NF-kB, p53 and Wnt signaling. Curr Opin Genet Dev. 2010;20(6):656–64.

    Article  CAS  Google Scholar 

  74. Sneppen K, Krishna S, Semsey S. Simplified models of biological networks. Annu Rev Biophys. 2010;39(39):43–59.

    Article  CAS  Google Scholar 

  75. Hasty J, Pradines J, Dolnik M, et al. Noise-based switches and amplifiers for gene expression. Proc Natl Acad Sci USA. 2000;97(5):2075–80.

    Article  CAS  Google Scholar 

  76. Xiong W, Ferrell JE Jr. A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision. Nature. 2003;426(6965):460.

    Article  CAS  Google Scholar 

  77. Ozbudak EM, Thattai M, Han NL, et al. Multistability in the lactose utilization network of Escherichia coli. Nature. 2004;427(6976):737–40.

    Article  CAS  Google Scholar 

  78. Alon U. Network motifs: theory and experimental approaches. Nat Rev Genet. 2007;8(6):450–461.

    Article  CAS  Google Scholar 

  79. Ma, W., Trusina, A., El-Samad, H., Lim, W. A., & Tang, C. (2009). Defining network topologies that can achieve biochemical adaptation. Cell, 138(4):760–773.

    Article  CAS  Google Scholar 

  80. Cui Q, Yu Z, Purisima EO, Wang E. Principles of microRNA regulation of a human cellular signaling network. Mol Syst Biol. 2006;2(1):46.

    PubMed  PubMed Central  Google Scholar 

  81. Collado-Vides J, Magasanik B, Gralla JD. Control site location and transcriptional regulation in Escherichia coli. Microbiol Rev. 1991;55(3):371–94.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

As for the topological structure of feedback loop, we learn from Dr. Alon and apply the motif to microRNA network motif. So we thank Dr. Alon for his enlightenment.

Author information

Authors and Affiliations

  1. Shanghai University, Shanghai, China

    Zengrong Liu

  2. Institute of Applied Mathematics, Xuchang University, Xuchang, China

    Jianwei Shen

  3. Faculty of Science, Jiangsu University, Zhenjiang, China

    Shuiming Cai

  4. School of Mathematics, Yunnan Normal University, Yunnan, China

    Fang Yan

Authors
  1. Zengrong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianwei Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shuiming Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fang Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature B.V.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Liu, Z., Shen, J., Cai, S., Yan, F. (2018). Topological Structure and Biological Function of Gene Network Regulated by MicroRNA. In: MicroRNA Regulatory Network: Structure and Function. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1577-3_2

Download citation

Publish with us

Policies and ethics

Search

Navigation