Journal of Molecular Evolution

, Volume 58, Issue 2, pp 203–211 | Cite as

Molecular Evolution in Large Genetic Networks: Does Connectivity Equal Constraint?

  • Matthew W. Hahn
  • Gavin C. Conant
  • Andreas Wagner


Genetic networks show a broad-tailed distribution of the number of interaction partners per protein, which is consistent with a power-law. It has been proposed that such broad-tailed distributions are observed because they confer robustness against mutations to the network. We evaluate this hypothesis for two genetic networks, that of the E. coli core intermediary metabolism and that of the yeast protein-interaction network. Specifically, we test the hypothesis through one of its key predictions: highly connected proteins should be more important to the cell and, thus, subject to more severe selective and evolutionary constraints. We find, however, that no correlation between highly connected proteins and evolutionary rate exists in the E. coli metabolic network and that there is only a weak correlation in the yeast protein-interaction network. Furthermore, we show that the observed correlation is function-specific within the protein-interaction network: only genes involved in the cell cycle and transcription show significant correlations. Our work sheds light on conflicting results by previous researchers by comparing data from multiple types of protein-interaction datasets and by using a closely related species as a reference taxon. The finding that highly connected proteins can tolerate just as many amino acid substitutions as other proteins leads us to conclude that power-laws in cellular networks do not reflect selection for mutational robustness.


Power-law Mutational robustness Selective constraint Genetic network 



M.W.H. thanks M. Rausher, M. Rockman, M. Rutter, A. Sweigart, M. Uyenoyama, and R. Zufall for comments and suggestions; an NSF Doctoral Dissertation Improvement Grant provided support. G.C.C. is supported by the Department of Energy’s Computational Sciences Graduate Fellowship program, administered by the Krell Institute. A.W. acknowledges financial support through NIH Grant GM63882 and the Santa Fe Institute.


  1. 1.
    Akashi, H 2001Gene expression and molecular evolution.Curr Opin Genet Dev11660666CrossRefPubMedGoogle Scholar
  2. 2.
    Albert, R, Jeong, H, Barabasi, A-L 2000Error and attack tolerance of complex networks.Nature406378382CrossRefGoogle Scholar
  3. 3.
    Altschul, SF, Madden, TL, Schaffer, AA, Zhang, JH, Zhang, Z, Miller, W, Lipman, DJ 1997Gapped BLAST and PSI-BLAST: A new generation of protein database search programs.Nucleic Acids Res2533893402PubMedGoogle Scholar
  4. 4.
    Barabasi, A-L, Albert, R 1999Emergence of scaling in random networks.Science286509512CrossRefGoogle Scholar
  5. 5.
    Bhalla, US, lyengar, R 1999Emergent properties of networks of biological signaling pathways.Science283381387PubMedGoogle Scholar
  6. 6.
    Blattner, FR, Plunkett, G, Bloch, CA, Perna, NT, Burland, V, Riley, M, Collado-Vides, J, Glasner, JD, Rode, CK, Mayhew, GF, Gregor, J, Davis, NW, Kirkpatrick, HA, Goeden, MA, Rose, DJ, Mau, B, Shao, Y 1997The complete genome sequence of Escherichia coli K-12.Science27714531462PubMedGoogle Scholar
  7. 7.
    Conant, GC, Wagner, A 2002GenomeHistory: A software tool and its application to fully sequenced genomes.Nucleic Acids Res3033783386CrossRefPubMedGoogle Scholar
  8. 8.
    Dykhuizen, DE, Hartl, DL 1983Functional effects of PGI allozymes in Escherichiacoli.Genetics105118PubMedGoogle Scholar
  9. 9.
    Edwards, JS, Palsson, BO 1999Systems properties of the Haemophilusinfluenzae Rd metabolic genotype.J Biol Chem2741741017416PubMedGoogle Scholar
  10. 10.
    Edwards, JS, Palsson, BO 2000The Escherichiacoli MG1655 insilico metabolic genotype: Its definition, characteristics, and capabilities.Proc Natl Acad Sci USA9755285533PubMedGoogle Scholar
  11. 11.
    Fleischmann, RD, Adams, MD, White, O,  et al. 1995Whole-genome random sequencing and assembly of Haemophilusinfluenzae Rd.Science269496512PubMedGoogle Scholar
  12. 12.
    Fraser, HB, Hirsh, AE, Steinmetz, LM, Scharfe, C, Feldman, MW 2002Evolutionary rate in the protein interaction network.Science296750752CrossRefPubMedGoogle Scholar
  13. 13.
    Fraser, HB, Wall, DP, Hirsh, AE 2003A simple dependence between protein evolution rate and the number of protein-protein interactions.BMC Evol Biol311CrossRefPubMedGoogle Scholar
  14. 14.
    Gavin, AC, Bosche, M, Krause, R,  et al. 2002Functional organization of the yeast proteome by systematic analysis of protein complexes.Nature415141147PubMedGoogle Scholar
  15. 15.
    The Gene Ontology Consortium2000Gene Ontology: Tool for the unification of biology.Nature Genet252529Google Scholar
  16. 16.
    Goffeau, A, Barrell, BG, Bussey, H, Davis, RW, Dujon, B, Feldmann, H, Galibert, F, Hoheisel, JD, Jacq, C, Johnston, M, Louis, EJ, Mewes, HW, Murakami, Y, Philippsen, P, Tettelin, H, Oliver, SG 1996Life with 6000 genes.Science274563567CrossRefGoogle Scholar
  17. 17.
    Goldman, N, Yang, Z 1994A codon-based model of nucleotide substitution for protein-coding DNA sequences.Mol Biol Evol11725736PubMedGoogle Scholar
  18. 18.
    Hartwell, LH, Hopfield, JJ, Leibler, S, Murray, AW 1999From molecular to modular cell biology.Nature402C47C52CrossRefPubMedGoogle Scholar
  19. 19.
    Ho, Y, Gruhler, A, Heilbut, A, Bader, GD,  et al. 2002Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry.Nature415180183PubMedGoogle Scholar
  20. 20.
    Hurst, LD, Smith, NGC 1999Do essential genes evolve slowly?Curr Biol9747750CrossRefPubMedGoogle Scholar
  21. 21.
    Ito, T, Chiba, T, Ozawa, R, Yoshida, M, Hattori, M, Sakaki, Y 2001A comprehensive two-hybrid analysis to explore the yeast protein interactome.Proc Natl Acad Sci USA9845694574PubMedGoogle Scholar
  22. 22.
    Jeong, H, Tombor, B, Albert, R, Oltvai, ZN, Barabasi, A-L 2000The large-scale organization of metabolic networks.Nature407651654PubMedGoogle Scholar
  23. 23.
    Jeong, H, Mason, SP, Barabasi, A-L, Oltvai, ZN 2001Lethality and centrality in protein networks.Nature4114142CrossRefGoogle Scholar
  24. 24.
    Jordan, IK, Wolf, YI, Koonin, EV 2003aNo simple dependence between protein evolution rate and the number of protein-protein interactions: Only the most prolific interactors tend to evolve slowly.BMC Evol Biol31Google Scholar
  25. 25.
    Jordan, IK, Wolf, YI, Koonin, EV 2003bCorrection: No simple dependence between protein evolution rate and the number of protein-protein interactions: Only the most prolific interactors tend to evolve slowly.BMC Evol Biol35Google Scholar
  26. 26.
    Kellis, M, Patterson, N, Endrizzi, M, Birren, B, Lander, ES 2003Sequencing and comparison of yeast species to identify genes and regulatory elements.Nature423241254CrossRefPubMedGoogle Scholar
  27. 27.
    Kimura, M 1977Preponderance of synonymous changes as evidence for the neutral theory of molecular evolution.Nature267275276PubMedGoogle Scholar
  28. 28.
    Kumar, S, Subramanian, S 2002Mutation rates in mammalian genomes.Proc Natl Acad Sci USA99803808CrossRefGoogle Scholar
  29. 29.
    Li, W-H 1997Molecular evolution.Sinauer AssociatesSunderland, MAGoogle Scholar
  30. 30.
    Lynch, M, Conery, JS 2000The evolutionary fate and consequences of duplicate genes.Science29011511155CrossRefPubMedGoogle Scholar
  31. 31.
    Mewes, HW, Heumann, K, Kaps, A, Mayer, K, Pfeiffer, F, Stocker, S, Frishman, D 1999MIPS: A database for genomes and protein sequences.Nucleic Acids Res274448PubMedGoogle Scholar
  32. 32.
    Morowitz, HJ 1992Beginnings of cellular life.Yale University PressNew Haven, CTGoogle Scholar
  33. 33.
    Rausher, MD, Miller, RE, Tiffin, P 1999Patterns of evolutionary rate variation among genes of the anthocyanin biosynthetic pathway.Mol Biol Evol16266274PubMedGoogle Scholar
  34. 34.
    Ross-Macdonald, P, Coelho, PSR, Roemer, T, Agarwal, S, Kumar, A, Jansen, R, Cheung, KH, Sheehan, A, Symoniatis, D, Umansky, L, Heldtman, M, Nelson, FK, Iwasaki, H, Hager, K, Gerstein, M, Miller, P, Roeder, GS, Snyder, M 1999Large-scale analysis of the yeast genome by transposon tagging and gene disruption.Nature402413418PubMedGoogle Scholar
  35. 35.
    Smith, V, Chou, KN, Lashkari, D, Botstein, D, Brown, PO 1996Functional analysis of the genes of yeast chromosome V by genetic footprinting.Science27420692074CrossRefPubMedGoogle Scholar
  36. 36.
    Tatusov, RL, Mushegian, AR, Bork, P, Brown, NP, Hayes, WS, Borodovsky, M, Rudd, KE, Koonin, EV 1996Metabolism and evolution of Haemophilusinfluenzae deduced from a whole-genome comparison with Escherichiacoli.Curr Biol6279291PubMedGoogle Scholar
  37. 37.
    Thompson, JD, Higgins, DG, Gibson, TJ 1994Clustal-W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.Nucleic Acids Res2246734680PubMedGoogle Scholar
  38. 38.
    Uetz, P, Giot, L, Cagney, G, Mansfield, TA, Judson, RS, Knight, JR, Lockshon, D, Narayan, V, Srinivasan, M, Pochart, P, Qureshi-Emili, A, Li, Y, Godwin, B, Conover, D, Kalbfleisch, T, Vijayadamodar, G, Yang, MJ, Johnston, M, Fields, S, Rothberg, JM 2000A comprehensive analysis of protein-protein interactions in Saccharomycescerevisiae.Nature403623627PubMedGoogle Scholar
  39. 39.
    von Mering, C, Krause, R, Snel, B, Cornell, M, Oliver, SG, Fields, S, Bork, P 2002Comparative assessment of large-scale data sets of protein-protein interactions.Nature417399403PubMedGoogle Scholar
  40. 40.
    Wagner, A 2000Mutational robustness in genetic networks of yeast.Nature Genet24355361CrossRefPubMedGoogle Scholar
  41. 41.
    Wagner, A 2001The yeast protein interaction network evolves rapidly and contains few duplicate genes.Mol Biol Evol1812831292PubMedGoogle Scholar
  42. 42.
    Wagner, A 2002Estimating coarse gene network structure from large-scale gene perturbation data.Genome Res12309315CrossRefPubMedGoogle Scholar
  43. 43.
    Wagner, A, Fell, D 2001The small world inside large metabolic networks.Proc Roy Soc Lond Ser B28018031810CrossRefGoogle Scholar
  44. 44.
    Watts, DJ 1999Small worlds.Princeton University PressPrinceton, NJGoogle Scholar
  45. 45.
    Watts, DJ, Strogatz, SH 1998Collective dynamics of small-world networks.Nature393440442CrossRefGoogle Scholar
  46. 46.
    Williams, EJB, Hurst, LD 2000The proteins of linked genes evolve at similar rates.Nature407900903PubMedGoogle Scholar
  47. 47.
    Winzeler, EA, Shoemaker, DD, Astromoff, A,  et al. 1999Functional characterization of the S. cerevisiae genome by gene deletion ad parallel analysis.Science285901906CrossRefPubMedGoogle Scholar
  48. 48.
    Wood, V, Gwilliam, R, Rajandream, MA,  et al. 2002The genome sequence of Schizosaccharomycespombe.Nature415871880PubMedGoogle Scholar

Copyright information

© Springer-Verlag New York Inc. 2004

Authors and Affiliations

  • Matthew W. Hahn
    • 1
  • Gavin C. Conant
    • 2
  • Andreas Wagner
    • 2
  1. 1.Department of Biology, Box 90338Duke University, Durham, NC 27708USA
  2. 2.Department of Biology, 167 Castetter HallUniversity of New Mexico, Albuquerque, NM 87131USA

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