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

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.

It’s about Time: Ossification Center Formation in C57BL/6 Mice from E12–E16

“…The methods established here are easily transferable for characterizing the temporal sequence of other events of interest. Limbstaging methodology is readily applicable to establishing temporal priority of gene expression sequences, patterns that shift rapidly during developmental events [19], yet are critical to understanding the nature of the relationship between genotype and phenotype.…”

Deciphering the regulatory logic of aDrosophilaenhancer through systematic sequence mutagenesis and quantitative image analysis

“…Several studies have successfully measured direct gene expression quantitatively during development and linked it to morphology. These attempts range from modeling a monotone gradient (Gregor et al, 2007), to quantifying variation in gene expression patterns Fowlkes et al, 2008;Knowles, 2012;Martinez-Abadias et al, 2018). To our knowledge, however, very few (Bentovim et al, 2017;Park et al, 2019) used comprehensive descriptors to thoroughly extract more information than possible from qualitative approaches, or exploited the statistical power offered by such descriptors.…”

Evolutionary Integration and Modularity in the Archosaur Cranium

“…Recent advances in geometric morphometric techniques have allowed complex phenotypes to be quantified with higher detail than before (Botton-Divet et al 2015;Parr et al 2016;Fabre et al 2018;Martınez-Abadıas et al 2018;Bardua et al 2019). At the same time, new approaches for testing hypotheses of modularity have allowed for more complex hypotheses of modularity to be evaluated using these data (Márquez 2008;Adams 2016;Goswami and Finarelli 2016;Larouche et al 2018).…”