Dynamics of Developmental Defect Formation

PROJECT SUMMARY Recent advances in genome sequencing have led to the identification of many mutations linked to developmental disorders. Additionally, phenotypes associated with these diseases have been well characterized through endpoint assays. Thus, genotype and phenotype have been separately well defined, but the connection between the two is not clear. Identifying the point in development that is most vulnerable to the effects of these mutations, or the point at which there is a detectable difference from what is typically observed is essential for understanding the pathogenesis of developmental disorders. To address these outstanding questions, live imaging approaches are needed. The proposed work uses the larval tracheal system of Drosophila as a model for the study of phenotypic emergence. The development of the larval tracheal system is strikingly analogous to human angiogenesis, a process that is affected in a class of developmental diseases known as the RASopathies, the subject of this work. Using this model system in Drosophila gene edited to carry mutations leading to elevated Ras-MAPK signaling, the proposed work will identify the position and timing of defect formation as well as the magnitude of change in signaling that accompanies developmental defect formation. Specifically, Aim 1 will use endogenous live reporters of tracheal cell fates in combination with live imaging to identify the developmental event that is affected in a mutant background. This work will provide insight into the variability underlying phenotypic emergence. Additionally, Aim 2 will use live reporters of signaling pathways, live imaging, and quantitative image analysis to determine the magnitude of change in signaling activity that is associated with a change in cell fate or the formation of a defect. The work described in Aim 2 will identify the limits of robustness of developmental signaling pathways. The proposed studies, which are supported by strong preliminary results, including live imaging and an established image analysis pipeline, will provide a deeper understanding of the connection between genotype and phenotype.