Skip to main content
Log in

Searching for Modular Structure in Complex Phenotypes: Inferences from Network Theory

  • Tools and Techniques
  • Published:
Evolutionary Biology Aims and scope Submit manuscript

Abstract

The notion of modularity has become a unifying principle to understand structural and functional aspects of biological organization at different levels of complexity. Recently, deciphering the modular organization of molecular systems has been greatly aided by network theory. Nevertheless, network theory is completely absent from the investigation of modularity of complex macroscopic phenotypes, a fundamental level of organization at which organisms experience and interact with the environment. Here, we used geometric descriptors of phenotypic variation to derive a network representation of a complex morphological structure, the mammalian mandible, in terms of nodes and links. Then, by integrating the network representation and description with random matrix theory, we uncovered a modular organization for the mammalian mandible, which deviates significantly from an equivalent random network. The modules revealed by the network analysis correspond to the four morphogenetic units recognized for the mammalian mandible on a developmental basis. Furthermore, these modules are known to be affected only by particular genes and are also functionally differentiated. This study shows that the powerful formalism of network theory can be applied to the discovery of modules in complex phenotypes and opens the possibility of an integrated approach to the study of modularity at all levels of organizational complexity.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Adams, D. C., Rohlf, F. J., & Slice, D. E. (2004). Geometric morphometrics: Ten years of progress following the ‘revolution’. The Italian Journal of Zoology, 71, 5–16.

    Article  Google Scholar 

  • Albert, R., & Barabási, A. L. (2002). Statistical mechanics of complex networks. Review of Modern Physics, 74, 47–97.

    Article  Google Scholar 

  • Atchley, W. R., & Hall, B. K. (1991). A model for development and evolution of complex morphological structures. Biological Review, 66, 101–157.

    CAS  Google Scholar 

  • Batagelj, V., & Mrvar, A. (2008). Pajek 1.23 software. http://vlado.fmf.uni-lj.si/pub/networks/pajek/.

  • Bookstein, F. L. (1991). Morphometric tools for landmark data: Geometry and biology. London: Cambridge University Press.

    Google Scholar 

  • Cheverud, J. M. (2004). Modular pleiotropic effects of quantitative trait loci on morphological traits. In G. Schlosser & G. P. Wagner (Eds.), Modularity in development and evolution (pp. 132–153). Chicago: Chicago University Press.

    Google Scholar 

  • Cheverud, J. M., Routman, E. J., & Irschick, D. K. (1997). Pleiotropic effects of individual gene loci on mandibular morphology. Evolution, 51, 2004–2014.

    Article  Google Scholar 

  • Danon, L., Duch, J., Diaz-Guilera, A., Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics P09008.

  • Davidson, E. H., & Levine, M. (2008). Properties of developmental gene regulatory networks. Proceedings of the National Academy of Sciences of the United States of America, 105, 20063–20066.

    Article  CAS  PubMed  Google Scholar 

  • de Aguiar, M. A. M., & Bar-Yam, Y. (2005). Spectral analysis and the dynamic response of complex networks. Physical Review, E71, 6106.

    Google Scholar 

  • Ehrich, T. H., Vaughn, T. T., Koreishi, S. F., Linsey, R. B., Pletscher, L. S., & Cheverud, J. M. (2003). Pleiotropic effects on mandibular morphology I. Developmental morphological integration and differential dominance. Journal of Experimental Zoology Molecular and Developmental Evolution, 296B, 58–79.

    Article  Google Scholar 

  • Galewski, T., Mauffrey, J. F., Leite, Y. L. R., Patton, J. L., & Douzery, E. J. P. (2005). Ecomorphological diversification among South American spiny rats (Rodentia: Echimyidae): A phylogenetic and chronological approach. Molecular Phylogenetics and Evolution, 34, 601–615.

    Article  CAS  PubMed  Google Scholar 

  • Guimerà, R., & Amaral, L. A. N. (2005). Functional cartography of complex metabolic networks. Nature, 433, 895–900.

    Article  PubMed  Google Scholar 

  • Guimerà, R., Sales-Pardo, M., & Amaral, L. A. N. (2004). Modularity from fluctuations in random graphs and complex networks. Physical Review E, 70, 025101.

    Article  Google Scholar 

  • Hall, B. K. (2003). Unlocking the black box between genotype and phenotype: Cell condensations as morphogenetic (modular) units. Biology and Philosophy, 18, 219–247.

    Article  Google Scholar 

  • Hallgrimsson, B., Lieberman, D. E., Young, N. M., Parsons, T., & Wat, S. (2007). Evolution of covariance in the mammalian skull. Novartis Foundation Symposium, 284, 164–190.

    Article  PubMed  Google Scholar 

  • Hintze, A., & Adami, C. (2008). Evolution of complex modular biological networks. PLoS Computational Biology, 4, e23.

    Article  PubMed  Google Scholar 

  • Klingenberg, C. P., Mebus, K., & Auffray, J.-C. (2003). Developmental integration in a complex morphological structure: How distinct are the modules in the mouse mandible? Evolution and Development, 5, 522–531.

    Article  PubMed  Google Scholar 

  • Klingenberg, C. P., & Zaklan, S. D. (2000). Morphological integration between developmental compartments in the Drosophila wing. Evolution, 54, 1273–1285.

    CAS  PubMed  Google Scholar 

  • Kreimer, A., Boresntein, E., Gophna, U., & Ruppin, E. (2008). The evolution of modularity in bacterial metabolic networks. Proceedings of the National Academy of Sciences of the United States of America, 105, 6976–6981.

    Article  CAS  PubMed  Google Scholar 

  • Levin, S. A. (1992). The problem of pattern and scale in ecology. Ecology, 73, 1943–1967.

    Article  Google Scholar 

  • Levin, S. A. (2003). Complex adaptive systems: Exploring the known, the unknown and the unknowable. Bulletin of the American Mathematical Society, 40, 3–19.

    Article  Google Scholar 

  • Ma’ayan, A. (2009). Insights into the organization of biochemical regulatory networks using graph theory analyses. Journal of Biological Chemistry, 284, 5451–5455.

    Article  PubMed  Google Scholar 

  • Marroig, G., & Cheverud, J. M. (2001). A comparison of phenotypic variation and covariation patterns and the role of phylogeny, ecology and ontogeny during cranial evolution of New World monkeys. Evolution, 55, 2576–2600.

    CAS  PubMed  Google Scholar 

  • Mehta, M. L. (2004). Random matrices. New York: Academic Press.

    Google Scholar 

  • Mitteroecker, P., & Bookstein, F. (2009). The ontogenetic trajectory of the phenotypic covariance matrix, with examples from craniofacial shape in rats and humans. Evolution, 63, 727–737.

    Article  PubMed  Google Scholar 

  • Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103, 8577–8582.

    Article  CAS  PubMed  Google Scholar 

  • Oksanen, J., Kindt, R., Legendre, P., O’Hara, B., Simpson, G. L., Stevens, M. H. H. (2008). Vegan: Community ecology package. R package version 1.11-4. http://cran.r-project.org.

  • Palla, G., & Vattay, G. (2006). Spectral transitions in networks. New Journal of Physics, 8, 307.

    Article  Google Scholar 

  • Peres-Neto, P. R., & Jackson, D. A. (2001). How well do multivariate data sets match? The advantages of a procrustean superimposition approach over the Mantel test. Oecologia, 129, 169–178.

    Article  Google Scholar 

  • Perez, S. I., Diniz-Filho, J. A. F., Rohlf, F. J., & dos Reis, S. F. (2009). Morphological diversification among South American spiny rats (Rodentia: Echimyidae): Ecological and phylogenetic factors. Journal of the Linnean Society, 98, 646–660.

    Google Scholar 

  • Porto, A., de Oliveira, F. B., Shirai, L. T., De Conto, V., & Marroig, G. (2008). The evolution of modularity in the mammalian skull I: Morphological integration patterns and magnitudes. Evolutionary Biology, 35, 1–18.

    Article  Google Scholar 

  • Raff, R. A. (1996). The shape of life: Genes, development, and the evolution of animal form. Chicago: University of Chicago Press.

    Google Scholar 

  • Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A. L. (2002). Hierarchical organization of modularity in metabolic networks. Science, 297, 1551–1555.

    Article  CAS  PubMed  Google Scholar 

  • Rohlf, F. J. (2007). tps series softwares. http//life.bio.sunysb.edu/morph/.

  • Sales-Pardo, M., Guimerà, R., Moreira, A. A., & Amaral, L. A. N. (2007). Extracting the hierarchical organization of complex systems. Proceedings of the National Academy of Sciences of the United States of America, 104, 15224–15229.

    Article  CAS  PubMed  Google Scholar 

  • Schlosser, G., & Wagner, G. P. (Eds.). (2004). Modularity in development and evolution. Chicago: Chicago University Press.

    Google Scholar 

  • Sheets, H. D. (2003). IMP-integrated morphometrics package. Department of Physics, Canisius College, Buffalo, New York.

  • Steinhauser, D., Krall, L., Müssig, C., Büssis, D., & Usadel, B. (2008). Correlation networks. In B. H. Junker & F. Schreiber (Eds.), Analysis of biological networks (pp. 305–333). New Jersey: Wiley.

    Chapter  Google Scholar 

  • Wagner, G. P. (1984). On the eigenvalues of genetic and phenotypic dispersion matrices: Evidence for a nonrandom organization of quantitative character variation. Journal of Mathematical Biology, 21, 77–95.

    Google Scholar 

  • Wagner, G. P. (1996). Homologues, natural kinds and the evolution of modularity. American Zoologist, 36, 36–43.

    Google Scholar 

  • Wagner, G. P., Pavlicev, M., & Cheverud, J. M. (2007). The road to modularity. Nature Reviews. Genetics, 8, 921–931.

    Article  CAS  PubMed  Google Scholar 

  • Wang, Z., & Zhang, J. (2007). In search of the biological significance of modular structures in protein networks. PLoS Computational Biology, 3(6), e107.

    Article  PubMed  Google Scholar 

  • Winther, R. G. (2001). Varieties of modules: Kinds, levels, origins, and behaviours. Journal of Experimental Zoology Molecular and Developmental Evolution, 291, 116–129.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We thank J. A. de Oliveira (Museu Nacional, Rio de Janeiro, Brasil), for granting access to the echimyid skeletal collections under his care. We are sincerely grateful to two anonymous reviewers who contributed greatly to clarify the manuscript. Research supported by grants from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP). S. I. Perez was supported by a postdoctoral fellowship from FAPESP. M. A. M. de Aguiar and S. F. dos Reis are partially supported by research fellowships from the Conselho Nacional de Desenvolvimento Científico e Tecnológico and FAPESP. P. R. Guimarães Jr. was supported by a scholarship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Ivan Perez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ivan Perez, S., de Aguiar, M.A.M., Guimarães, P.R. et al. Searching for Modular Structure in Complex Phenotypes: Inferences from Network Theory. Evol Biol 36, 416–422 (2009). https://doi.org/10.1007/s11692-009-9074-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11692-009-9074-7

Keywords

Navigation