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

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

doi:10.7554/elife.36405

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.

Highlights

Morphogenesis is guided by dynamic spatio-temporal regulation of gene expression patterns (Chan et al, 2017; Andrey and Mundlos, 2017), the zones within tissues where genes are expressed during specific periods in development
We propose to quantify the shape of developing organs in association with their underlying gene expression patterns by applying Geometric Morphometrics (GM), a set of statistical tools for measuring and comparing shapes with increased precision and efficiency (James Rohlf and Marcus, 1993; Klingenberg, 2002; Klingenberg, 2010; Adams et al, 2013; Hallgrimsson et al, 2015)
The methods that are currently used to assess gene expression patterns are mainly qualitative and focus only on shape and size differences that can be detected by eye

Summary

Introduction

Morphogenesis is guided by dynamic spatio-temporal regulation of gene expression patterns (Chan et al, 2017; Andrey and Mundlos, 2017), the zones within tissues where genes are expressed during specific periods in development. The current study is the first to combine OPT and GM to characterize the shape of gene expression patterns quantitatively in 3D and to associate these changes to phenotypic changes This approach provides the ability to replace qualitative observations with the quantification of subtle yet significant biological differences that underlie the processes through which morphogenesis is altered by disease. Our quantitative analyses demonstrate that the Apert syndrome Fgfr P253R mutation induces changes in the expression pattern of Dusp and that these genetic changes are associated with significant phenotypic alterations. These results provide insight into the origins of limb malformations in Apert syndrome

Results

Discussion

Materials and methods

Funding Funder European Commission