Interplay between sex determination cascade and major signaling pathways during Drosophila eye development: Perspectives for future research

Distinct developmental patterns in Anopheles stephensi organ systems

Anatomical profiles of insects inform vector biology, comparative development and evolutionary studies with applications in forensics, agriculture and disease control. This study presents a comprehensive, high-resolution developmental profile of Anopheles stephensi, encompassing larval, pupal, and adult stages, obtained through microCT scanning. The results indicate in situ anatomical changes in most organ systems, including the central nervous system, eyes, musculature, alimentary canal, salivary glands, and ovaries, among other organ systems, except for the developing heart. We find significant differences in the mosquito gut, body-wall, and flight muscle development during metamorphosis from other dipterans like Drosophila. Specifically, indirect flight muscle specification and growth can be traced back at least to the 4th instar A. stephensi larvae, as opposed to post-puparial development in other Dipterans like Drosophila and Calliphora. Further, while Drosophila larval body-wall muscles and gut undergo histolysis, changes to these organs during mosquito metamorphosis are less pronounced. These observations, and raw data therein may serve as a reference for studies on the development and the genetics of mosquitoes. Overall, the detailed developmental profile of A. stephensi presented here illuminates the unique anatomy and developmental processes of Culicidae, with important implications for vector biology, disease control, and comparative evolutionary studies.

MAPPER: An Open-Source, High-Dimensional Image Analysis Pipeline Unmasks Differential Regulation of Drosophila Wing Features

Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful genetic model for studying the underlying genetics for a broad range of cellular and developmental processes, are limited in speed, precision, and functional versatility. To expand on the utility of the wing as a phenotypic screening system, we developed MAPPER, an automated machine learning-based pipeline that quantifies high-dimensional phenotypic signatures, with each dimension quantifying a unique morphological feature of the Drosophila wing. MAPPER magnifies the power of Drosophila phenomics by rapidly quantifying subtle phenotypic differences in sample populations. We benchmarked MAPPER's accuracy and precision in replicating manual measurements to demonstrate its widespread utility. The morphological features extracted using MAPPER reveal variable sexual dimorphism across Drosophila species and unique underlying sex-specific differences in morphogen signaling in male and female wings. Moreover, the length of the proximal-distal axis across the species and sexes shows a conserved scaling relationship with respect to the wing size. In sum, MAPPER is an open-source tool for rapid, high-dimensional analysis of large imaging datasets. These high-content phenomic capabilities enable rigorous and systematic identification of genotype-to-phenotype relationships in a broad range of screening and drug testing applications and amplify the potential power of multimodal genomic approaches.