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Parsimonious Reconstruction of Network Evolution

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Algorithms in Bioinformatics (WABI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6833))

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Abstract

We consider the problem of reconstructing a maximally parsimonious history of network evolution under models that support gene duplication and loss and independent interaction gain and loss. We introduce a combinatorial framework for encoding network histories, and we give a fast procedure that, given a set of duplication histories, in practice finds network histories with close to the minimum number of interaction gain or loss events. In contrast to previous studies, our method does not require knowing the relative ordering of unrelated duplication events. Results on simulated histories suggest that common ancestral networks can be accurately reconstructed using this parsimony approach.

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References

  1. Aldana, M., Balleza, E., Kauffman, S., Resendiz, O.: Robustness and evolvability in genetic regulatory networks. J. Theor. Biol. 245(3), 433–448 (2007)

    Article  Google Scholar 

  2. Arvestad, L., Berglund, A.C., Sennblad, B.: Bayesian gene/species tree reconciliation and orthology analysis using mcmc. Bioinformatics 19(Suppl. 1), i7–i15 (2003)

    Article  Google Scholar 

  3. Borenstein, E., Feldman, M.W.: Topological signatures of species interactions in metabolic networks. J. Comput. Biol. 16(2), 191–200 (2009)

    Article  Google Scholar 

  4. Borenstein, E., Kupiec, M., Feldman, M.W., Ruppin, E.: Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proc. Natl. Acad. Sci. USA 105(38), 14482–14487 (2008)

    Article  Google Scholar 

  5. Chen, K., Durand, D., Farach-Colton, M.: NOTUNG: A program for dating gene duplications and optimizing gene family trees. Journal of Computational Biology 7(3-4), 429–447 (2000)

    Article  Google Scholar 

  6. Chung, F., Lu, L., Dewey, T.G., Galas, D.J.: Duplication models for biological networks. J. Comp. Biol. 10(5), 677–687 (2003)

    Article  Google Scholar 

  7. Durand, D., Halldrsson, B.V., Vernot, B.: A hybrid micromacroevolutionary approach to gene tree reconstruction. J. Comp. Biol. 13(2), 320–335 (2006)

    Article  Google Scholar 

  8. Dutkowski, J., Tiuryn, J.: Identification of functional modules from conserved ancestral proteinprotein interactions. Bioinformatics 23(13), i149–i158 (2007)

    Article  Google Scholar 

  9. Erten, S., Li, X., Bebek, G., Li, J., Koyuturk, M.: Phylogenetic analysis of modularity in protein interaction networks. BMC Bioinformatics 10, 333 (2009)

    Article  Google Scholar 

  10. Espinosa-Soto, C., Martin, O.C., Wagner, A.: Phenotypic robustness can increase phenotypic variability after nongenetic perturbations in gene regulatory circuits. J. Evol. Biol. 24(6), 1284–1297 (2011)

    Article  Google Scholar 

  11. Flannick, J., Novak, A., Srinivasan, B.S., McAdams, H.H., Batzoglou, S.: Graemlin: general and robust alignment of multiple large interaction networks. Genome Res. 16(9), 1169–1181 (2006)

    Article  Google Scholar 

  12. Foster, D.V., Kauffman, S.A., Socolar, J.E.S.: Network growth models and genetic regulatory networks. Phys. Rev. E 73(3), 031912 (2006)

    Article  Google Scholar 

  13. Gibson, T.A., Goldberg, D.S.: Reverse engineering the evolution of protein interaction networks. In: Pac. Symp. Biocomput., pp. 190–202 (2009)

    Google Scholar 

  14. Ispolatov, I., Krapivsky, P.L., Yuryev, A.: Duplication-divergence model of protein interaction network. Phys. Rev. E 71(6 Pt 1), 061911 (2005)

    Article  Google Scholar 

  15. Kreimer, A., Borenstein, E., Gophna, U., Ruppin, E.: The evolution of modularity in bacterial metabolic networks. Proc. Natl. Acad. Sci. USA 105(19), 6976–6981 (2008)

    Article  Google Scholar 

  16. Kuchaiev, O., Milenkovic, T., Memisevic, V., Hayes, W., Przulj, N.: Topological network alignment uncovers biological function and phylogeny. J. R. Soc. Interface 7(50), 1341–1354 (2010)

    Article  Google Scholar 

  17. Levy, E.D., Pereira-Leal, J.B.: Evolution and dynamics of protein interactions and networks. Curr. Opin. Struct. Biol. 18(3), 349–357 (2008)

    Article  Google Scholar 

  18. Middendorf, M., Ziv, E., Wiggins, C.H.: Inferring network mechanisms: the Drosophila melanogaster protein interaction network. Proc. Natl. Acad. Sci. USA 102(9), 3192–3197 (2005)

    Article  Google Scholar 

  19. Mirkin, B.G., Fenner, T.I., Galperin, M.Y., Koonin, E.V.: Algorithms for computing parsimonious evolutionary scenarios for genome evolution, the last universal common ancestor and dominance of horizontal gene transfer in the evolution of prokaryotes. BMC Evol. Biol. 3, 2 (2003)

    Article  Google Scholar 

  20. Mithani, A., Preston, G., Hein, J.: A stochastic model for the evolution of metabolic networks with neighbor dependence. Bioinformatics 25(12), 1528–1535 (2009)

    Article  Google Scholar 

  21. Navlakha, S., Kingsford, C.: Network archaeology: Uncovering ancient networks from present-day interactions. PLoS Comput. Biol. 7(4), e1001119 (2011)

    Article  Google Scholar 

  22. Pachter, L.: An introduction to reconstructing ancestral genomes. In: Proc. Symp. in Applied Mathematics, vol. 64, pp. 1–20 (2007)

    Google Scholar 

  23. Pastor-Satorras, R., Smith, E., Sole, R.: Evolving protein interaction networks from gene duplication. J. Theor. Biol. 222, 199–210 (2003)

    Article  Google Scholar 

  24. Pereira-Leal, J.B., Levy, E.D., Kamp, C., Teichmann, S.A.: Evolution of protein complexes by duplication of homomeric interactions. Genome Biol. 8(4), R51 (2007)

    Article  Google Scholar 

  25. Pinney, J.W., Amoutzias, G.D., Rattray, M., Robertson, D.L.: Reconstruction of ancestral protein interaction networks for the bZIP transcription factors. Proc. Natl. Acad. Sci. USA 104(51), 20449–20453 (2007)

    Article  Google Scholar 

  26. Raman, K., Wagner, A.: Evolvability and robustness in a complex signalling circuit. Mol. Biosyst. 7(4), 1081–1092 (2011)

    Article  Google Scholar 

  27. Singh, R., Xu, J., Berger, B.: Pairwise global alignment of protein interaction networks by matching neighborhood topology. In: Speed, T., Huang, H. (eds.) RECOMB 2007. LNCS (LNBI), vol. 4453, pp. 16–31. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  28. Stewart, A.J., Seymour, R.M., Pomiankowski, A.: Degree dependence in rates of transcription factor evolution explains the unusual structure of transcription networks. Proc. Biol. Sci. 276(1666), 2493–2501 (2009)

    Article  Google Scholar 

  29. Teichmann, S.A., Babu, M.M.: Gene regulatory network growth by duplication. Nat. Genetics 36(5), 492–496 (2004)

    Article  Google Scholar 

  30. Zhang, X., Moret, B.: Refining transcriptional regulatory networks using network evolutionary models and gene histories. Alg. Mol. Biol. 5(1), 1 (2010)

    Article  Google Scholar 

  31. Zhang, X., Moret, B.M.: Boosting the performance of inference algorithms for transcriptional regulatory networks using a phylogenetic approach. In: Crandall, K.A., Lagergren, J. (eds.) WABI 2008. LNCS (LNBI), vol. 5251, pp. 245–258. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742, USA

    Rob Patro, Emre Sefer, Justin Malin, Guillaume Marçais & Carl Kingsford

  2. Department of Computer Science, University of Maryland, College Park, MD, 20742, USA

    Rob Patro, Emre Sefer & Carl Kingsford

  3. Computational Biology, Bioinformatics and Genomics Concentration, Biological Sciences Graduate Program, University of Maryland, College Park, MD, 20742, USA

    Justin Malin & Carl Kingsford

  4. Program in Applied Mathematics, Statistics, and Scientific Computation, University of Maryland, College Park, MD, 20742, USA

    Guillaume Marçais & Carl Kingsford

  5. School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Saket Navlakha

Authors
  1. Rob Patro
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  2. Emre Sefer
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  3. Justin Malin
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  4. Guillaume Marçais
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  5. Saket Navlakha
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  6. Carl Kingsford
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Editor information

Editors and Affiliations

  1. National Center for Biotechnology Information, U.S. National Library of Medicine, 8600 Rockville Pike, 20894, Bethesda, MD, USA

    Teresa M. Przytycka

  2. Institut National de Recherche en Informatique et en Automatique (INRIA) and Université Lyon 1 (UCBL), 43 bd du 11 Novembre 1918, 69622, Villeurbanne cedex, France

    Marie-France Sagot

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Patro, R., Sefer, E., Malin, J., Marçais, G., Navlakha, S., Kingsford, C. (2011). Parsimonious Reconstruction of Network Evolution. In: Przytycka, T.M., Sagot, MF. (eds) Algorithms in Bioinformatics. WABI 2011. Lecture Notes in Computer Science(), vol 6833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23038-7_21

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  • DOI: https://doi.org/10.1007/978-3-642-23038-7_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23037-0

  • Online ISBN: 978-3-642-23038-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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