Pavel Tomancak

Pavel Tomancak, MPI-CBG Dresden We are interested in understanding how genetic information contained in non-coding portion of the genome governs tissue specific gene expression and impacts cellular behavior during Drosophila embryo development. We collected high-resolution image data on gene expression patterns during embryogenesis on a genome wide scale; using RNA in situ hybridization to fixed staged tissue as a primary approach.

Currently, we are developing strategies to systematically visualize gene expression patterns in living embryos using live gene expression reporters. To that end we established a novel genomic library that allows seamless manipulation of large genomic neighborhoods by recombineering techniques and direct, site-specific transgenesis of modified clones into flies. The library allows us to fluorescently tag arbitrary genes in the Drosophila genome, in the context of their intact cis-regulatory sequence neighborhood, generating faithful reporters of gene expression specificity. These reporters will be imaged using Single Plane Illumination Microscopy that enables live in toto imaging of fluorescently labeled large biological specimens. We are developing sophisticated image analysis pipelines to transform the SPIM recordings into digital representation of embryonic development, where cells, tissues and associated, stained gene specific components are tracked across time in three dimensions.

These datasets will be supplemented by quantitative comparisons of gene expression patterns across multiple sequenced Drosophila species. We employ high-throughput microarray time-course analysis to identify genes that diverge among these highly related insect species and image them at cellular resolution with SPIM. Population genetics methods are used to detect the action of natural selection on these patterns and predictive bioinformatics pinpoints the sequence determinants of the observed expression pattern changes. The cis-regulatory evolution hypotheses will be tested in transgenic models.

The digital representation of development will enable the study of the relationship between dynamic gene expression regulation and morphogenetic events in the context of the entire living system. Once expanded to genome-wide scale it will provide a solid foundation for mathematical modeling of development.