A cis-regulatory sequence of the selector gene vestigial drives the evolution of wing scaling in Drosophila species.

Scaling between specific organs and overall body size has long fascinated biologists, being a primary mechanism by which organ shapes evolve. Yet, the genetic mechanisms that underlie the evolution of scaling relationships remain elusive. Here, we compared wing and fore tibia lengths (the latter as a proxy of body size) in Drosophila melanogaster, Drosophila simulans, Drosophila ananassae and Drosophila virilis, and show that the first three of these species have roughly a similar wing-to-tibia scaling behavior. In contrast, D. virilis exhibits much smaller wings relative to their body size compared with the other species and this is reflected in the intercept of the wing-to-tibia allometry. We then asked whether the evolution of this relationship could be explained by changes in a specific cis-regulatory region or enhancer that drives expression of the wing selector gene, vestigial (vg), whose function is broadly conserved in insects and contributes to wing size. To test this hypothesis directly, we used CRISPR/Cas9 to replace the DNA sequence of the predicted Quadrant Enhancer (vgQE) from D. virilis for the corresponding vgQE sequence in the genome of D. melanogaster. Strikingly, we discovered that D. melanogaster flies carrying the D. virilis vgQE sequence have wings that are significantly smaller with respect to controls, partially shifting the intercept of the wing-to-tibia scaling relationship towards that observed in D. virilis. We conclude that a single cis-regulatory element in D. virilis contributes to constraining wing size in this species, supporting the hypothesis that scaling could evolve through genetic variations in cis-regulatory elements.

The vestigial Quadrant Enhancer is dispensable for pattern formation and development of the Drosophila wing.

In Drosophila , the pattern of the wing selector gene, vestigial ( vg ), is established by at least two enhancers: the Boundary Enhancer, which drives expression along the disc's Dorsal-Ventral boundary; and the Quadrant Enhancer (QE) that patterns the rest of the wing pouch. Using CRISPR/Cas9 editing, we deleted DNA fragments around the reported QE sequence and found that the full Vg pattern is formed. Furthermore, adult wings arising from these gene-edited animals are normal in shape and pattern, but slightly smaller in size, although this reduction is not wing-specific in males. We suggest that other enhancers act redundantly to establish the vg pattern and rescue wing development.

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.