Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis
Year: 2018
Type: article
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 can be obscured later in development due to secondary phenotypic effects. We here 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, our approach is sensitive enough to find regulatory abnormalities never previously detected. We identified subtle but significant differences in gene expression of a downstream target of the Fgfr2 mutation associated with Apert syndrome. Challenging previous reports, we demonstrate that Apert syndrome mouse models can further our understanding of limb defects in the human condition. Our method can be applied to other organ systems and models to investigate the etiology of malformations.
Source: eLife
DOI: 10.7554/elife.36405
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funders: Burroughs Wellcome Fund, Centres de Recerca de Catalunya, National Institute for Health and Care Research, European Commission, Generalitat de Catalunya, Ministerio de Economía y Competitividad, National Institutes of Health, National Institute of Dental and Craniofacial Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, FP7 People: Marie-Curie Actions
Awards: G2217018754, G2537960588, G2973790809, G3207356259, G393177772, G4053127980, G5702163051, G682275100, G7083190786, G7833276827, Hearts and limbs: Linking morphometrics with 3D analysis of gene expression patterns, Midface and Upper Airway in Craniosynostosis, G9000243501, Craniosynostosis Network
OpenAlex ID: W2951882476
