Professor Angela DePace
Department of Systems Biology, Harvard Medical School
Friday, December 13, 2013 - 2:00pm
Ramsay Wright Building, Room 432
Enhancers direct the time and place of transcription by interpreting the concentrations of transcription factors (TFs) through DNA binding and interactions with their target promoter. The relationship between the concentration of regulatory TFs and the level of target gene expression is known as the gene regulatory function (GRF). We have built GRFs that quantitatively and accurately predict gene expression in single cells of developing Drosophila melanogaster embryos. These models do not incorporate DNA sequence; they relate input TF concentrations to output gene expression directly using statistical models. They therefore reflect how positional information is interpreted by individual enhancers in the embryo. I will describe our initial work fitting and validating these models using quantitative data from wildtype embryos and qualitative data from mutant embryos. I will then describe our more recent unpublished efforts to generate quantitative, cellular resolution expression data in Drosophila embryos where we have perturbed the expression patterns of key TFs, and how we used this data to challenge our models of enhancer function. Deploying a new shRNAi strategy, we depleted embryos of a key maternal patterning TF, bicoid, and measured the positions and levels of all the genes in the core anterior posterior patterning network. We also repeated a classic perturbation experiment, where key anterior/posterior TFs are expressed ventrally, and measured the effects on multiple target genes with high precision. We demonstrate how these data can 1) distinguish between alternative GRF models for enhancers, 2) reveal key differences in the GRFs encoded by minimal enhancer constructs and the endogenous locus and 3) that simple statistical models of positional information can predict the dramatic re-patterning events observed in mutant embryos.
Prof. Alan Moses <email@example.com>
Dept of Cell and Systems Biology