Skip to main content
Log in

Correlations Between the Morphology of Sonic Hedgehog Expression Domains and Embryonic Craniofacial Shape

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

Abstract

Quantitative analysis of gene expression domains and investigation of relationships between gene expression and developmental and phenotypic outcomes are central to advancing our understanding of the genotype–phenotype map. Gene expression domains typically have smooth but irregular shapes lacking homologous landmarks, making it difficult to analyze shape variation with the tools of landmark-based geometric morphometrics. In addition, 3D image acquisition and processing introduce many artifacts that further exacerbate the problem. To overcome these difficulties, this paper presents a method that combines optical projection tomography scanning, a shape regularization technique and a landmark-free approach to quantify variation in the morphology of Sonic hedgehog expression domains in the frontonasal ectodermal zone (FEZ) of avians and investigate relationships with embryonic craniofacial shape. The model reveals axes in FEZ and embryonic-head morphospaces along which variation exhibits a sharp linear relationship at high statistical significance. The technique should be applicable to analyses of other 3D biological structures that can be modeled as smooth surfaces and have ill-defined shape.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Bookstein, F. L. (1996). Morphometric tools for landmark data: Geometry and biology. Cambridge, MA: Cambridge University.

    Google Scholar 

  • Chong, H., Young, N., et al. (2012). Signaling by SHH rescues facial defects following blockade in the brain. Developmental Dynamics, 241, 247–256.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Dryden, I., & Mardia, K. (1998). Statistical shape analysis. Cambridge, MA: Cambridge University.

    Google Scholar 

  • Duchon, J. (1977). Splines minimizing rotation-invariant semi-norms in Sobolev spaces. Constructive Theory of Functions of Several Variables, 571, 85–100.

    Article  Google Scholar 

  • Fisher, M. E., Clelland, A. K., et al. (2008). Integrating technologies for comparing 3D gene expression domains in the developing chick limb. Development Biology, 317, 13–23.

    Article  CAS  Google Scholar 

  • Fortune, S. (1987). A sweepline algorithm for Voronoi diagrams. In SCG ‘86 Proceedings of the second annual symposium on computational geometry (pp. 313–322). New York, NY: ACM.

    Google Scholar 

  • Fowlkes, C., Hendriks, C., et al. (2008). A quantitative spatiotemporal atlas of gene expression in the Drosophila blastoderm. Cell, 133, 364–374.

    Article  CAS  PubMed  Google Scholar 

  • Guibas, L., Stolfi, J. (1985). Primitives for the manipulation of general subdivisions and the computation of Voronoi diagrams. In ACM transactions on graphics (TOG), 74–123.

  • Hallgrimsson, B., & Hall, B. K. (2011). Epigenetics: Linking genotype and phenotype in development and evolution. Oakland, CA: University of California Press.

    Google Scholar 

  • Hallgrimsson, B., Jamniczky, H., et al. (2009). Deciphering the palimpsest: Studying the relationship between morphological integration and phenotypic covariation. Evolutionary Biology, 36, 355–376.

    Article  PubMed Central  PubMed  Google Scholar 

  • Hendrikse, J. L., Parsons, T. E., & Hallgrimsson, B. (2007). Evolvability as the proper focus of evolutionary developmental biology. Evolution and Development, 9, 393–401.

    Article  PubMed  Google Scholar 

  • Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28, 321–377.

    Article  Google Scholar 

  • Houle, D., Govindaraju, D. R., & Omholt, S. (2010). Phenomics: The next challenge. Nature Reviews Genetics, 11, 855–866.

    Article  CAS  PubMed  Google Scholar 

  • Hu, D., & Marcucio, R. S. (2009). A SHH-responsive signaling center in the forebrain regulates craniofacial morphogenesis via the facial ectoderm. Development, 136, 107–116.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Hu, D., Marcucio, R. S., & Helms, J. A. (2003). A zone of frontonasal ectoderm regulates patterning and growth in the face. Development, 130, 1749–1758.

    Article  CAS  PubMed  Google Scholar 

  • Hu, D., Young, N., et al. (2015). Signals from the brain induce variation in avian facial shape. Developmental Dynamics (in press).

  • Kendall, D. L. (1984). Shape manifolds, procrustean metrics and complex projective spaces. Bulletin of the London Mathematical Society, 16, 81–121.

    Article  Google Scholar 

  • Kendall, D. G., Barden, D., Carne, T. K., & Le, H. (1999). Shape and shape theory. Chichester, NY: Wiley.

    Book  Google Scholar 

  • Krzanowski, W. J. (1988). Principles of multivariate analysis: A user’s perspective. New York, NY: Oxford University.

    Google Scholar 

  • Kudoh, T., Tsang, M., et al. (2001). Gene expression screen in zebrafish embryogenesis. Genome Research, 11, 1979–1987.

    Article  CAS  PubMed  Google Scholar 

  • Le, H., & Kendall, D. L. (1993). The Riemannian structure of Euclidean shape spaces: A novel environment for statistics. Annals of Statistics, 21, 1225–1271.

    Article  Google Scholar 

  • Lein, E. S., Hawrylycz, M. J., et al. (2007). Genome-wide atlas of gene expression in the adult mouse brain. Nature, 445, 168–176.

    Article  CAS  PubMed  Google Scholar 

  • Liu, X., Mio, W., et al. (2008). Models of normal variation and local contrasts in hippocampal anatomy. In Medical Image Computing and Computer-Assisted InterventionMICCAI 2008, New York, NY: Springer.

  • Marcucio, R. S., Cordero, D., & Helms, J. A. (2005). Molecular interactions coordinating development of the forebrain and face. Development Biology, 284, 48–61.

    Article  CAS  Google Scholar 

  • Marcucio, R. S., Young, N. M., Hu, D., & Hallgrimsson, B. (2011). Mechanisms that underlie co-variation of the brain and face. Genesis, 49, 177–189.

    Article  PubMed Central  PubMed  Google Scholar 

  • Meinguet, J. (1979). Multivariate interpolation at arbitrary points made simple. Applied Mathematics Physics, 30, 292–304.

    Article  Google Scholar 

  • Mio, W., Bowers, J. C., Hurdal, M. K., & Liu, X. (2007). Modeling brain anatomy with 3D arrangements of curves. In ICCV 2007, 11th IEEE International Conference on Computer Vision 2007 (pp. 1–8). doi:10.1109/ICCV.2007.4409164.

  • Myasnikova, E., Samsonova, A., et al. (2001). Registration of the expression patterns of Drosophila segmentation genes by two independent methods. Bioinformatics, 17, 3–12.

    Article  CAS  PubMed  Google Scholar 

  • Parzen, E. (1962). On estimation of a probability density function and mode. The Annals of Mathematical Statistics, 33, 1065–1076.

    Article  Google Scholar 

  • Quintana, L., & Sharpe, J. (2011). Optical projection tomography of vertebrate embryo development. Cold Spring Harbor Protocols,. doi:10.1101/pdb.top116.

    Google Scholar 

  • Rosenbaltt, M. (1956). Remarks on some nonparametric estimates of a density function. The Annals of Mathematical Statistics, 27, 832–837.

    Article  Google Scholar 

  • Seber, G. (1984). Multivariate observations. Hoboken, NJ: Wiley.

    Book  Google Scholar 

  • Sharpe, J. (2002). Optical projection tomography as a tool for 3D microscopy and gene expression studies. Science, 296, 541–545.

    Article  CAS  PubMed  Google Scholar 

  • Silverman, B. W. (1998). Density estimation for statistics and data analysis. London: Chapman Hall/CRC.

    Google Scholar 

  • Tassy, O., Dauga, D., et al. (2010). The ANISEED database: Digital representation, formalization, and elucidation of a chordate developmental program. Genome Research, 20, 1459–1468.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Visel, A., Thaller, C., & Eichele, G. (2004). GenePaint.org: An atlas of gene expression patterns in the mouse embryo. Nucleic Acids Research, 32, 552–556.

    Article  Google Scholar 

  • Wagner, P., Ruta, M., & Coates, M. (2006). Evolutionary patterns in early tetrapods. II. Differing constraints on available character space among clades. Proceedings of the Royal Society B: Biological Sciences, 273, 2107–2111.

    Article  PubMed Central  PubMed  Google Scholar 

  • Wahba, G. (1990). Spline models for observational data. Philadelphia, PA: Society for Industrial and Applied Mathematics.

    Book  Google Scholar 

  • Wong, F., Welten, M., et al. (2013). eChickAtlas: An introduction to the database. Genesis, 51, 365–371.

    Article  CAS  PubMed  Google Scholar 

  • Young, N. M., Chong, H. J., et al. (2010). Quantitative analyses link modulation of sonic hedgehog signaling to continuous variation in facial growth and shape. Development, 137, 3405–3409.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We acknowledge funding from the National Science Foundation Grant DBI-1052942 (WM) and National Institutes of Health Grants 3R01DE021708 (BH, RSM and WM) and F32DE02214 (RMG). We thank the anonymous reviewers for their comments.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

All experiments comply with the current laws of the United States of America and Canada.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Washington Mio.

Additional information

Software Accessibility Matlab code for the shape regularization method developed in this paper is available for free use at https://github.com/qx0731/Mesh-Regularization-/.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, Q., Jamniczky, H., Hu, D. et al. Correlations Between the Morphology of Sonic Hedgehog Expression Domains and Embryonic Craniofacial Shape. Evol Biol 42, 379–386 (2015). https://doi.org/10.1007/s11692-015-9321-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11692-015-9321-z

Keywords

Navigation