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Hefeweizen HFSP Team
(Tomancak lab, Ohler lab, Bergman lab)
Quantitative modeling of expression pattern evolution in insect development
Recent advances in technology have revolutionized our understanding of biological processes from the ecological to the molecular levels, however many fundamental questions concerning the evolution of organisms remain a mystery. The interdisciplinary field of "evo-devo" attempts to uncover the molecular and evolutionary mechanisms responsible for changes in organismal development, but has not yet adopted the quantitative rigor that is necessary to resolve competing hypotheses. For example, in 1828 Karl von Baer first proposed a model of embryonic development which states that divergent animal species pass through a similar period of development known as the "phylotypic stage." Although this long-standing model describes a fundamental pattern of animal development, no evidence currently exists to prove that the phylotypic stage is actively maintained by natural selection or, alternatively, if it is simply a consequence of mechanistic constraints during development.
Our project will combine novel experimental and computational methods to address the evolution of genes on the level of their expression patterns in a model species, the fruitfly Drosophila melanogaster. The central objective is to introduce quantitative precision to the comparative analysis of expression patterns in order to reveal how changes in gene regulation lead to the evolution of developmental processes. We will develop and apply advanced imaging and image analysis techniques in conjunction with quantitative models of evolution to test the hypothesis that natural selection maintains the "phylotypic stage". The combination of expertise in developmental, computational, and evolutionary biology will allow us to: image entire Drosophila embryos in 3D with cellular resolution, stained for expression of single genes; compare the exact details of expression patterns within and among related Drosophila species using advanced image analysis; and test quantitative genetic models to identify gene expression patterns that diverge under natural selection. Genes with divergent patterns will be analyzed to pinpoint sequence determinants and selective forces acting on gene expression innovations. Our work will establish a new paradigm in post-genomic evolutionary developmental biology and reveal the evolutionary mechanism that underpins one of the most fundamental laws of animal biology.
