Spatio-temporal expression analysis at cellular resolution in the Drosophila embryo reveals new dynamics of morphology and gene expression.
1) Life Sciences and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA.
2) Computer Science Division, University of California, Berkeley, CA.
3) Institute for Data Analysis and Visualization, University of California, Davis, CA.
4) Computer Science Department, University of Kaiserslautern, Germany.
Gene regulation is integrated at the level of individual cells. Thus, to understand which parts of a metazoan genome each cell uses we need quantitative expression data for each individual cell. The Berkeley Drosophila Transcription Network project has developed a set of computational tools for measuring and analyzing morphology and gene expression at cellular resolution in whole Drosophila blastoderm embryos. From a confocal image of an embryo stained for DNA and two gene products, RNA or protein, we can now segment the thousands of individual nuclei, measure the expression levels of the two gene products proximal to each nucleus, and convert this information into a computationally analyzable data table. Using embryo morphology and a common reference gene expression pattern present in each embryo imaged, hundreds of these data tables are then registered and mapped onto a single virtual embryo, in which the averaged expression patterns for many genes are painted onto the same cellular resolution morphological framework. Using a visualization tool we have developed, PointCloudXplore, our virtual embryos can be viewed in multiple ways, including as 2D and 3D renderings, parallel co-ordinate graphs, and 3D expression scatterplots, providing novel ways to detect and approach functional genomic problems. Our methods have revealed previously undetected changes in cell density patterns and embryo shape prior to gastrulation. Gene expression patterns move in part with changes in morphology, but additional shifts in expression positions are also seen, supporting a previously proposed expression flow model. Moreover, we show that mutations that disrupt either the anterior/posterior (a/p) or the dorsal/ventral (d/v) transcriptional cascades alter morphology along both the a/p and d/v axes, indicating that these two systems are less independent than usually thought.
Last modified May 12, 2006.