Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis

Neus Martínez-Abadías, Roger Mateu Estivill, Jaume Sastre Tomas, Susan Motch Perrine, Melissa Yoon, Alexandre Robert-Moreno, Jim Swoger, Lucia Russo, Kazuhiko Kawasaki, Joan Richtsmeier, James Sharpe

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2 Scopus citations

Abstract

The earliest developmental origins of dysmorphologies are poorly understood in many congenital diseases. They often remain elusive because the first signs of genetic misregulation may initiate as subtle changes in gene expression, which are hard to detect and can be obscured later in development by secondary effects. Here, we develop a method to trace back the origins of phenotypic abnormalities by accurately quantifying the 3D spatial distribution of gene expression domains in developing organs. By applying Geometric Morphometrics to 3D gene expression data obtained by Optical Projection Tomography, we determined that our approach is sensitive enough to find regulatory abnormalities that have never been detected previously. We identified subtle but significant differences in the gene expression of a downstream target of a Fgfr2 mutation associated with Apert syndrome, demonstrating that these mouse models can further our understanding of limb defects in the human condition. Our method can be applied to different organ systems and models to investigate the etiology of malformations.

Original languageEnglish (US)
Article numbere36405
JournaleLife
Volume7
DOIs
StatePublished - Sep 2018

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)

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    Martínez-Abadías, N., Estivill, R. M., Tomas, J. S., Perrine, S. M., Yoon, M., Robert-Moreno, A., Swoger, J., Russo, L., Kawasaki, K., Richtsmeier, J., & Sharpe, J. (2018). Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis. eLife, 7, [e36405]. https://doi.org/10.7554/eLife.36405