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Developmental origin of phenotypic variation in Drosophila melanogaster

This project's overall goal is to help close the gap between the increasing ability to rapidly sequence the DNA, the genotype, of an organism, and the relative lack of techniques to measure the even more complex physical form of the organism, its phenotype. The measurement of complex, high-dimensional phenotypes is an essential complement to the genomic level data. We call the integration of such phenotypic data with genetics phenomics. This project exploits an existing system for automated wing measurement, and will develop techniques for the rapid measurement of other phenotypes, including whole flies. From a biological point of view, the overall aim of this project is to understand the genetic causes of phenotypic variation in the wings and other aspects of external morphology of Drosophila melanogaster . The proposed work will test the usefulness of a phenomic approach for the Drosophila wing, through three specific questions:
  1. What genetic changes can cause variation in wing shape? We will develop a “dictionary” of genetic effects on wing form by systematically manipulating gene expression at genetic loci hypothesized to be involved in wing development. These data will then be used to build predictive models of the connections between developmental pathways and phenotypic variation.
  2. What are the genetic causes of natural variation in wing shape? We will attempt to apply the phenomic approach to the genetic basis of natural variation in wing shape in D. melanogaster using the dictionary of genetic effects.
  3. How do genetic changes that cause variation in wing shape affect other body parts? The effects of a genetic variant on multiple traits is an important feature of genetic systems with profound implications for evolution. We will develop and generalize methods to measure variation in whole flies. A detailed quantitative atlas of Drosophila morphology will first be generated, then used to map 2-D images onto the atlas, allowing quantitative information on 3-D form to extracted while minimizing human involvement.