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Genome-Wide Dissection of Posttranscriptional and Posttranslational Interactions

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 786))

Abstract

Transcriptional interactions in the cell are modulated by a variety of posttranscriptional and posttranslational mechanisms that make them highly dependent on the molecular context of the specific cell. These include, among others, microRNA-mediated control of transcription factor (TF) mRNA translation and degradation, transcription factor activation by phosphorylation and acetylation, formation of active complexes with one or more cofactors, and mRNA/protein degradation and stabilization processes. Thus, the ability of a transcription factor to regulate its targets depends on a variety of genetic and epigenetic mechanisms, resulting in highly context-dependent regulatory networks. In this chapter, we introduce a step-by-step guide on how to use the MINDy systems biology algorithm (Modulator Inference by Network Dynamics) that we recently developed, for the genome-wide, context-specific identification of posttranscriptional and posttranslational modulators of transcription factor activity.

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References

  1. Faith, J. J., Hayete, B., Thaden, J. T., Mogno, I., Wierzbowski, J., Cottarel, G., Kasif, S., Collins, J. J., and Gardner, T. S. (2007) Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles, PLoS Biol 5, e8.

    Article  PubMed  Google Scholar 

  2. Friedman, N. (2004) Inferring cellular networks using probabilistic graphical models, Science 303, 799–805.

    Article  PubMed  CAS  Google Scholar 

  3. Gardner, T. S., di Bernardo, D., Lorenz, D., and Collins, J. J. (2003) Inferring genetic networks and identifying compound mode of action via expression profiling, Science 301, 102–105.

    Article  PubMed  CAS  Google Scholar 

  4. Basso, K., Margolin, A. A., Stolovitzky, G., Klein, U., Dalla-Favera, R., and Califano, A. (2005) Reverse engineering of regulatory networks in human B cells, Nat Genet 37, 382–390.

    Article  PubMed  CAS  Google Scholar 

  5. Elkon, R., Linhart, C., Sharan, R., Shamir, R., and Shiloh, Y. (2003) Genome-Wide In Silico Identification of Transcriptional Regulators Controlling the Cell Cycle in Human Cells, Genome Res. 13, 773–780.

    Article  PubMed  CAS  Google Scholar 

  6. Stuart, J. M., Segal, E., Koller, D., and Kim, S. K. (2003) A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules, Science 302, 249–255.

    Article  PubMed  CAS  Google Scholar 

  7. Zhao, X., D, D. A., Lim, W. K., Brahmachary, M., Carro, M. S., Ludwig, T., Cardo, C. C., Guillemot, F., Aldape, K., Califano, A., Iavarone, A., and Lasorella, A. (2009) The N-Myc-DLL3 Cascade Is Suppressed by the Ubiquitin Ligase Huwe1 to Inhibit Proliferation and Promote Neurogenesis in the Developing Brain, Dev Cell 17, 210–221.

    Google Scholar 

  8. Carro, M. S., Lim, W. K., Alvarez, M. J., Bollo, R. J., Zhao, X., Snyder, E. Y., Sulman, E. P., Anne, S. L., Doetsch, F., Colman, H., Lasorella, A., Aldape, K., Califano, A., and Iavarone, A. (2009) The transcriptional network for mesenchymal transformation of brain tumours, Nature.

    Google Scholar 

  9. Della Gatta, G., Bansal, M., Ambesi-Impiombato, A., Antonini, D., Missero, C., and di Bernardo, D. (2008) Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering, Genome Res 18, 939–948.

    Article  PubMed  CAS  Google Scholar 

  10. Zeitlinger, J., Simon, I., Harbison, C. T., Hannett, N. M., Volkert, T. L., Fink, G. R., and Young, R. A. (2003) Program-Specific Distribution of a Transcription Factor Dependent on Partner Transcription Factor and MAPK Signaling, Cell 113, 395.

    Article  PubMed  CAS  Google Scholar 

  11. Si, J., Yu, X., Zhang, Y., and DeWille, J. W. (2010) Myc interacts with Max and Miz1 to repress C/EBPdelta promoter activity and gene expression, Mol Cancer 9, 92.

    Article  PubMed  Google Scholar 

  12. Luscombe, N. M., Babu, M. M., Yu, H., Snyder, M., Teichmann, S. A., and Gerstein, M. (2004) Genomic analysis of regulatory network dynamics reveals large topological changes, Nature 431, 308–312.

    Article  PubMed  CAS  Google Scholar 

  13. Segal, E., Shapira, M., Regev, A., Pe’er, D., Botstein, D., Koller, D., and Friedman, N. (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data, Nat Genet 34, 166–176.

    Article  PubMed  CAS  Google Scholar 

  14. Wang, K., Saito, M., Bisikirska, B. C., Alvarez, M. J., Lim, W. K., Rajbhandari, P., Shen, Q., Nemenman, I., Basso, K., Margolin, A. A., Klein, U., Dalla-Favera, R., and Califano, A. (2009) Genome-wide identification of post-translational modulators of transcription factor activity in human B cells, Nat Biotechnol 27, 829–837.

    Article  PubMed  CAS  Google Scholar 

  15. Linding, R., Jensen, L. J., Ostheimer, G. J., van Vugt, M. A., Jorgensen, C., Miron, I. M., Diella, F., Colwill, K., Taylor, L., Elder, K., Metalnikov, P., Nguyen, V., Pasculescu, A., Jin, J., Park, J. G., Samson, L. D., Woodgett, J. R., Russell, R. B., Bork, P., Yaffe, M. B., and Pawson, T. (2007) Systematic discovery of in vivo phosphorylation networks, Cell 129, 1415–1426.

    Article  PubMed  CAS  Google Scholar 

  16. Margolin, A. A., Nemenman, I., Basso, K., Wiggins, C., Stolovitzky, G., Favera, D., and Califano, A. (2006) ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context, BMC Bioinformatics 7 Suppl 1, S1–7.

    Article  Google Scholar 

  17. Basso, K., Margolin, A. A., Stolovitzky, G., Klein, U., Dalla-Favera, R., and Califano, A. (2005) Reverse engineering of regulatory networks in human B cells, Nat Genet 37, 382–390.

    Article  PubMed  CAS  Google Scholar 

  18. Butte, A. J., and Kohane, I. S. (2000) Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements, Pac Symp Biocomput, 418–429.

    Google Scholar 

  19. Friedman, N., Linial, M., Nachman, I., and Pe’er, D. (2000) Using Bayesian networks to analyze expression data, J Comput Biol 7, 601–620.

    Article  PubMed  CAS  Google Scholar 

  20. Cover, T. M., and Thomas, J. (2006) Elements of Information Theory, 2nd edition, Wiley Interscience.

    Google Scholar 

  21. Tu, Y., Stolovitzky, G., and Klein, U. (2002) Quantitative noise analysis for gene expression microarray experiments, Proc Natl Acad Sci USA 99, 14031–14036.

    Article  PubMed  CAS  Google Scholar 

  22. Nemenman, I. (2004) Information theory, multivariate dependence, and genetic network inference, In Technical Report NSF-KITP-04-54, KITP, http://arxiv.org/abs/0904.1587, UCSB.

  23. Kraskov, A., Stogbauer, H., and Grassberger, P. (2004) Estimating mutual information, Phys Rev E Stat Nonlin Soft Matter Phys 69, 066138.

    Article  PubMed  Google Scholar 

  24. Joe, H. (1997) Multivariate models and dependence concepts., Chapman & Hall, Boca Raton, FL.

    Google Scholar 

  25. Margolin, A. A., Wang, K., Lim, W. K., Kustagi, M., Nemenman, I., and Califano, A. (2006) Reverse engineering cellular networks, Nat Protocols 1, 663–672.

    Article  Google Scholar 

  26. Mani, K. M., Lefebvre, C., Wang, K., Lim, W. K., Basso, K., Dalla-Favera, R., and Califano, A. (2008) A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas, Mol Syst Biol 4, 169.

    Article  PubMed  Google Scholar 

  27. Dang, C. V., O’Donnell, K. A., Zeller, K. I., Nguyen, T., Osthus, R. C., and Li, F. (2006) The c-Myc target gene network, Seminars in Cancer Biology 16, 253–264.

    Article  PubMed  CAS  Google Scholar 

  28. Dominguez-Sola, D., Ying, C. Y., Grandori, C., Ruggiero, L., Chen, B., Li, M., Galloway, D. A., Gu, W., Gautier, J., and Dalla-Favera, R. (2007) Non-transcriptional control of DNA replication by c-Myc, Nature 448, 445–451.

    Article  PubMed  CAS  Google Scholar 

  29. Zeller, K. I., Jegga, A. G., Aronow, B. J., O’Donnell, K. A., and Dang, C. V. (2003) An integrated database of genes responsive to the Myc oncogenic transcription factor: identification of direct genomic targets, Genome Biol 4, R69.

    Article  PubMed  Google Scholar 

  30. Pelengaris, S., Khan, M., and Evan, G. (2002) c-MYC: more than just a matter of life and death, Nat Rev Cancer 2, 764–776.

    Article  PubMed  CAS  Google Scholar 

  31. Levens, D. L. (2003) Reconstructing MYC, Genes Dev 17, 1071–1077.

    Article  PubMed  CAS  Google Scholar 

  32. Patel, J. H., Du, Y., Ard, P. G., Phillips, C., Carella, B., Chen, C. J., Rakowski, C., Chatterjee, C., Lieberman, P. M., Lane, W. S., Blobel, G. A., and McMahon, S. B. (2004) The c-MYC oncoprotein is a substrate of the acetyltransferases hGCN5/PCAF and TIP60, Mol Cell Biol 24, 10826–10834.

    Article  PubMed  CAS  Google Scholar 

  33. Sears, R., Nuckolls, F., Haura, E., Taya, Y., Tamai, K., and Nevins, J. R. (2000) Multiple Ras-dependent phosphorylation pathways regulate Myc protein stability, Genes Dev 14, 2501–2514.

    Article  PubMed  CAS  Google Scholar 

  34. Peri, S., Navarro, J. D., Amanchy, R., Kristiansen, T. Z., Jonnalagadda, C. K., Surendranath, V., Niranjan, V., Muthusamy, B., Gandhi, T. K., Gronborg, M., Ibarrola, N., Deshpande, N., Shanker, K., Shivashankar, H. N., Rashmi, B. P., Ramya, M. A., Zhao, Z., Chandrika, K. N., Padma, N., Harsha, H. C., Yatish, A. J., Kavitha, M. P., Menezes, M., Choudhury, D. R., Suresh, S., Ghosh, N., Saravana, R., Chandran, S., Krishna, S., Joy, M., Anand, S. K., Madavan, V., Joseph, A., Wong, G. W., Schiemann, W. P., Constantinescu, S. N., Huang, L., Khosravi-Far, R., Steen, H., Tewari, M., Ghaffari, S., Blobe, G. C., Dang, C. V., Garcia, J. G., Pevsner, J., Jensen, O. N., Roepstorff, P., Deshpande, K. S., Chinnaiyan, A. M., Hamosh, A., Chakravarti, A., and Pandey, A. (2003) Development of human protein reference database as an initial platform for approaching systems biology in humans, Genome Res 13, 2363–2371.

    Article  PubMed  CAS  Google Scholar 

  35. Kanazawa, S., Soucek, L., Evan, G., Okamoto, T., and Peterlin, B. M. (2003) c-Myc recruits P-TEFb for transcription, cellular proliferation and apoptosis, Oncogene 22, 5707–5711.

    Article  PubMed  CAS  Google Scholar 

  36. Tsuneoka, M., and Mekada, E. (2000) Ras/MEK signaling suppresses Myc-dependent apoptosis in cells transformed by c-myc and activated ras, Oncogene 19, 115–123.

    Article  PubMed  CAS  Google Scholar 

  37. Luscher, B., Kuenzel, E. A., Krebs, E. G., and Eisenman, R. N. (1989) Myc oncoproteins are phosphorylated by casein kinase II, EMBO J 8, 1111–1119.

    PubMed  CAS  Google Scholar 

  38. Mac Partlin, M., Homer, E., Robinson, H., McCormick, C. J., Crouch, D. H., Durant, S. T., Matheson, E. C., Hall, A. G., Gillespie, D. A. F., and Brown, R. (2003) Interactions of the DNA mismatch repair proteins MLH1 and MSH2 with c-MYC and MAX, Oncogene 22, 819–825.

    Article  PubMed  CAS  Google Scholar 

  39. Feng, X. H., Liang, Y. Y., Liang, M., Zhai, W., and Lin, X. (2002) Direct interaction of c-Myc with Smad2 and Smad3 to inhibit TGF-beta-mediated induction of the CDK inhibitor p15(Ink4B), Mol Cell 9, 133–143.

    Article  PubMed  CAS  Google Scholar 

  40. Chapman, N. R., Webster, G. A., Gillespie, P. J., Wilson, B. J., Crouch, D. H., and Perkins, N. D. (2002) A novel form of the RelA nuclear factor kappaB subunit is induced by and forms a complex with the proto-oncogene c-Myc, Biochem J 366, 459–469.

    Article  PubMed  CAS  Google Scholar 

  41. Otsuki, Y., Tanaka, M., Kamo, T., Kitanaka, C., Kuchino, Y., and Sugimura, H. (2003) Guanine nucleotide exchange factor, Tiam1, directly binds to c-Myc and interferes with c-Myc-mediated apoptosis in rat-1 fibroblasts, J Biol Chem 278, 5132–5140.

    Article  PubMed  CAS  Google Scholar 

  42. Ingenuity Systems, I. www.ingenuity.com.

  43. Wang, K., Alvarez, M. J., Bisikirska, B. C., Linding, R., Basso, K., Dalla Favera, R., and Califano, A. (2009) Dissecting the interface between signaling and transcriptional regulation in human B cells, Pac Symp Biocomput, 264–275.

    Google Scholar 

  44. Lefebvre, C., Rajbhandari, P., Alvarez, M. J., Bandaru, P., Lim, W. K., Sato, M., Wang, K., Sumazin, P., Kustagi, M., Bisikirska, B. C., Basso, K., Beltrao, P., Krogan, N., Gautier, J., Dalla-Favera, R., and Califano, A. (2010) A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers, Mol Syst Biol 6, 377.

    Article  PubMed  Google Scholar 

  45. He, L., He, X., Lowe, S., and Hannon, G. (2007) microRNAs join the p53 network – another piece in the tumour-suppression puzzle., Nat Rev Cancer 7, 819–822.

    Article  PubMed  CAS  Google Scholar 

  46. Mestdagh, P., Fredlund, E., Pattyn, F., Schulte, J., Muth, D., Vermeulen, J., Kumps, C., Schlierf, S., De Preter, K., Van Roy, N., Noguera, R., Laureys, G., Schramm, A., Eggert, A., Westermann, F., Speleman, F., and Vandesompele, J. (2009) MYCN/c-MYC-induced microRNAs repress coding gene networks associated with poor outcome in MYCN/c-MYC-activated tumors., Oncogene.

    Google Scholar 

  47. Kim, H., Huang, W., Jiang, X., Pennicooke, B., Park, P., and Johnson, M. (2010) Integrative genome analysis reveals an oncomir/oncogene cluster regulating glioblastoma survivorship., Proc Natl Acad Sci USA.

    Google Scholar 

  48. Carro, M., Lim, W., Alvarez, M., Bollo, R., Zhao, X., Snyder, E., Sulman, E., Anne, S., Doetsch, F., Colman, H., Lasorella, A., Aldape, K., Califano, A., and Iavarone, A. (2009) The transcriptional network for mesenchymal transformation of brain tumours., Nature.

    Google Scholar 

  49. Cover, T. M., and Thomas, J. A. (1991), John Wiley & Sons, New York.

    Google Scholar 

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Acknowledgments

We would like to thank Pavel Sumazin for providing the insight into the application of MINDy on miRNAs and providing the Figure for it and Paolo Guarnieri for proof reading the document.

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Correspondence to Andrea Califano .

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MINDy executables and MATLAB scripts to compute mutual information, kernel width and the statistical threshold for mutual information and \( \Delta I\) can be downloaded from http://wiki.c2b2.columbia.edu/califanolab/index.php/Software.

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Bansal, M., Califano, A. (2012). Genome-Wide Dissection of Posttranscriptional and Posttranslational Interactions. In: Deplancke, B., Gheldof, N. (eds) Gene Regulatory Networks. Methods in Molecular Biology, vol 786. Humana Press. https://doi.org/10.1007/978-1-61779-292-2_8

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  • DOI: https://doi.org/10.1007/978-1-61779-292-2_8

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