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Integrated Network Modeling of Molecular and Genetic Interactions

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Sourcebook of Models for Biomedical Research

Abstract

In model organisms, systematic genetic perturbation and high-throughput data acquisition allow measurements of mutant phenotypes and detection of biomolecular interactions on a genome-wide scale. These data types are complementary in the sense that genetic interactions inferred from gene expression and other phenotype measurements can assign functional significance to the physical interactions between biomolecules. This chapter describes methods for the analysis of large-scale phenotype and expression data that employ genetic interactions to infer functional relationships between genes. Functional information is then used to direct the integration of physical interaction data to derive network models of cellular activity. These models, obtained from functional relationships but constrained by biochemistry, facilitate explicit and precise prediction of the effects of additional network perturbations.

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References

  1. Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H, et al. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 2001;294(5550):2364–2368.

    Article  PubMed  CAS  Google Scholar 

  2. Tong AH, Lesage G, Bader GD, Ding H, Xu H, Xin X, Young J, Berriz GF, Brost RL, Chang M, et al. Global mapping of the yeast genetic interaction network. Science 2004;303(5659):808–813.

    Article  PubMed  CAS  Google Scholar 

  3. Fraser AG, Kamath RS, Zipperlen P, Martinez-Campos M, Sohrmann M, Ahringer J. Functional genomic analysis of C. elegans chromosome I by systematic RNA interference. Nature 2000;408(6810): 325–330.

    Article  PubMed  CAS  Google Scholar 

  4. Tewari M, Hu PJ, Ahn JS, Ayivi-Guedehoussou N, Vidalain PO, Li S, Milstein S, Armstrong CM, Boxem M, Butler MD, et al. Systematic interactome mapping and genetic perturbation analysis of a C. elegans TGF-beta signaling network. Mol Cell 2004;13(4):469–482.

    Article  PubMed  CAS  Google Scholar 

  5. Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, Bangham R, Benito R, Boeke JD, Bussey H, et al. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 1999;285(5429):901–906.

    Article  PubMed  CAS  Google Scholar 

  6. Strausberg RL, Schreiber SL. From knowing to controlling: A path from genomics to drugs using small molecule probes. Science 2003;300(5617):294–295.

    Article  PubMed  CAS  Google Scholar 

  7. Swedlow JR, Goldberg I, Brauner E, Sorger PK. Informatics and quantitative analysis in biological imaging. Science 2003;300(5616): 100–102.

    Article  PubMed  CAS  Google Scholar 

  8. Drees BL, Thorsson V, Carter GW, Rives AW, Raymond MZ, Avila-Campillo I, Shannon P, Galitski T. Phenotype and the interaction of genetic perturbations. Genome Biol 2004;6(4):R38.

    Article  Google Scholar 

  9. Avery L, Wasserman S. Ordering gene function: The interpretation of epistasis in regulatory hierarchies. Trends Genet 1992;8(9): 312–316.

    Article  PubMed  CAS  Google Scholar 

  10. Zhang LV, King OD, Wong SL, Goldberg DS, Tong AH, Lesage G, Andrews B, Bussey H, Boone C, Roth FP. Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network. J Biol 2005;4(2):6.

    Article  PubMed  CAS  Google Scholar 

  11. Kelley R, Ideker T. Systematic interpretation of genetic interactions using protein networks. Nat Biotechnol 2005;23(5):561–566.

    Article  PubMed  CAS  Google Scholar 

  12. Galitski T. Molecular networks in model systems. Annu Rev Genomics Hum Genet 2004;5:177–187.

    Article  PubMed  CAS  Google Scholar 

  13. Carter GW. Inferring network interactions within a cell. Brief Bioinform 2005;6(4):380–389.

    Article  PubMed  CAS  Google Scholar 

  14. Kamath RS, Fraser AG, Dong Y, Poulin G, Durbin R, Gotta M, Kanapin A, Le Bot N, Moreno S, Sohrmann M, Welchman DP, Zipperlen P, Ahringer J. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 2003;421: 231–237.

    Article  PubMed  CAS  Google Scholar 

  15. Boutros M, Kiger AA, Armknecht S, Kerr K, Hild M, Koch B, Haas SA, Consortium HF, Paro R, Perrimon N. Genome-wide RNAi analysis of growth and viability in Drosophila cells. Science 2004;303: 832–835.

    Article  PubMed  CAS  Google Scholar 

  16. Drysdale R. Phenotypic data in FlyBase. Brief Bioinform 2001;2:68–80.

    Article  PubMed  CAS  Google Scholar 

  17. Hartman JL IV, Garvik B, Hartwell L. Principles for the buffering of genetic variation. Science 2001;291:1001–1004.

    Article  PubMed  CAS  Google Scholar 

  18. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res 2003;13:2498–2504.

    Article  PubMed  CAS  Google Scholar 

  19. Online at http://galitski.systemsbiology.net.

  20. Van Driessche N, Demsar J, Booth EO, Hill P, Juvan P, Zupan B, Kuspa A, Shaulsky G. Epistasis analysis with global transcriptional phenotypes. Nat Genet 2005;37(5):471–477.

    Article  PubMed  Google Scholar 

  21. Online at http://www.geneontology.org.

  22. Carter GW, Rupp S, Fink GR, Galitski T. Disentangling information flow in the Ras-cAMP signaling network. Genome Res 2006;16(4):520–526.

    Article  PubMed  CAS  Google Scholar 

  23. Gimeno CJ, Fink GR. The logic of cell division in the life cycle of yeast. Science 1992;257:626.

    Article  PubMed  CAS  Google Scholar 

  24. Thevelein JM. The RAS-adenylate cyclase pathway and cell cycle control in Saccharomyces cerevisiae. Antonie Van Leeuwenhoek 1992;62:109–130.

    Article  PubMed  CAS  Google Scholar 

  25. D’Souza CA, Heitman J. Conserved cAMP signaling cascades regulate fungal development and virulence. FEMS Microbiol Rev 2001;25:349–364.

    Article  PubMed  CAS  Google Scholar 

  26. Jones DL, Petty J, Hoyle DC, Hayes A, Ragni E, Popolo L, Oliver SG, Stateva LI. Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway. Physiol Genomics 2003;16:107–118.

    Article  PubMed  CAS  Google Scholar 

  27. Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstrale M, Laurila E, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 2003;34(3):267–273.

    Article  PubMed  CAS  Google Scholar 

  28. Carter GW, Prinz S, Neou C, Shelby JP, Marzolf B, Thorsson V, Galitski T. Prediction of phenotype and genomic expression for combinations of mutations. Mol Syst Biol 2007;3:96.

    Article  PubMed  Google Scholar 

  29. Weaver DC, Workman CT, Stormo GD. Modeling regulatory networks with weight matrices. Pac Symp Biocomput 1999;4(1): 112–123.

    Google Scholar 

  30. Alter O, Brown PO, Botstein D. Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci USA 2000;97:10101–10106.

    Article  PubMed  CAS  Google Scholar 

  31. Yang YL, Suen J, Brynildsen MP, Galbraith SJ, Liao JC. Inferring yeast cell cycle regulators and interactions using transcription factor activities. BMC Genomics 2005;6(1):90.

    Article  PubMed  Google Scholar 

  32. Lengeler KB, Davidson RC, D’Souza C, Harashima T, Shen WC, Wang P, Pan X, Waugh M, Heitman J. Signal transduction cascades regulating fungal development and virulence. Microbiol Mol Biol Rev 2000;64(4):746–785.

    Article  PubMed  CAS  Google Scholar 

  33. Tonouchi A, Fujita A, Kuhara S. Molecular cloning of the gene encoding a highly expressed protein in SFL1 gene-disrupted flocculating yeast. J Biochem (Tokyo) 1994;115(4):683–688.

    CAS  Google Scholar 

  34. Vidal M. Interactome modeling. FEBS Lett 2005;579(8):1834–1838.

    Article  PubMed  CAS  Google Scholar 

  35. Bader GD, Heilbut A, Andrews B, Tyers M, Hughes T, Boone C. Functional genoimcs and proteomics: Charting a multidimensional map of the yeast cell. Trends Cell Biol 2003;13:344–356.

    Article  PubMed  CAS  Google Scholar 

  36. Gunsalus KC, Ge H, Schetter AJ, Goldberg DS, Han JD, Hao T, Berriz GF, Bertin N, Huang J, Chuang LS, et al. Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis. Nature 2005;436(7052):861–865.

    Article  PubMed  CAS  Google Scholar 

  37. Sachs K, Perez O, Pe’er D, Lauffenburger DA, Nolan GP. Causal protein-signaling networks derived from multiparameter single-cell data. Science 2005;308(5721):523–529.

    Article  PubMed  CAS  Google Scholar 

  38. Zhong W, Sternberg PW. Genome-wide prediction of C. elegans genetic interactions. Science 2006;311(5766):1481–1484.

    Article  PubMed  CAS  Google Scholar 

  39. Workman CT, Mak HC, McCuine S, Tagne JB, Agarwal M, Ozier O, Begley TJ, Samson LD, Ideker T. A systems approach to mapping DNA damage response pathways. Science 2006;312(5776): 1054–1059.

    Article  PubMed  CAS  Google Scholar 

  40. Kaern M, Elston TC, Blake WJ, Collins JJ. Stochasticity in gene expression: From theories to phenotypes. Nat Rev Genet 2005;6:451–464.

    Article  PubMed  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute for Systems Biology, Seattle, WA

    Gregory W. Carter PhD, Vesteinn Thorsson PhD & Timothy Galitski PhD

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  1. Gregory W. Carter PhD
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  2. Vesteinn Thorsson PhD
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  3. Timothy Galitski PhD
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Editor information

Editors and Affiliations

  1. Oregon National Primate Research Center, Beaverton, OR

    P. Michael Conn PhD (Associate Director and Senior Scientist, Professor of Physiology and Pharmacology, Professor of Cell and Developmental Biology) (Associate Director and Senior Scientist, Professor of Physiology and Pharmacology, Professor of Cell and Developmental Biology)

  2. Oregon Health and Science University, Portland, OR

    P. Michael Conn PhD (Associate Director and Senior Scientist, Professor of Physiology and Pharmacology, Professor of Cell and Developmental Biology) (Associate Director and Senior Scientist, Professor of Physiology and Pharmacology, Professor of Cell and Developmental Biology)

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© 2008 Humana Press Inc., Totowa, NJ

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Carter, G.W., Thorsson, V., Galitski, T. (2008). Integrated Network Modeling of Molecular and Genetic Interactions. In: Conn, P.M. (eds) Sourcebook of Models for Biomedical Research. Humana Press. https://doi.org/10.1007/978-1-59745-285-4_9

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  • DOI: https://doi.org/10.1007/978-1-59745-285-4_9

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-933-8

  • Online ISBN: 978-1-59745-285-4

  • eBook Packages: MedicineMedicine (R0)

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