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.

SummaryPhenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful model for studying morphogenesis, are limited in speed, versatility, and precision. To overcome these limitations, we developed MAPPER, a fully-automated machine learning-based pipeline that quantifies high dimensional phenotypic signatures, with each dimension representing a unique morphological feature. MAPPER magnifies the power of Drosophila genetics by rapidly identifying subtle phenotypic differences in sample populations. To demonstrate its widespread utility, we used MAPPER to reveal new insights connecting patterning and growth across Drosophila genotypes and species. The morphological features extracted using MAPPER identified the presence of a uniform scaling of proximal-distal axis length across four different species of Drosophila. Observation of morphological features extracted by MAPPER from Drosophila wings by modulating insulin signaling pathway activity revealed the presence of a scaling gradient across the anterior-posterior axis. Additionally, batch processing of samples with MAPPER revealed a key function for the mechanosensitive calcium channel, Piezo, in regulating bilateral symmetry and robust organ growth. MAPPER is an open source tool for rapid analysis of large volumes of imaging data. Overall, MAPPER provides new capabilities to rigorously and systematically identify genotype-to-phenotype relationships in an automated, high throughput fashion.Graphical abstract

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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 compare 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 their body size compared to 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.