Automated single cell expression analysis in C. elegans

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The information stored in an organism's genome directs its development and behavior, but how that occurs is only beginning to be understood. Knowledge of what genes are used in each cell at every stage of development would be a significant step toward a comprehensive understanding. We propose to develop methods that will exploit the invariant lineage of the nematode C. elegans to define gene expression patterns throughout development at the single cell level with high temporal resolution. This will be achieved with two parallel reporter systems. We will computationally track each nucleus through movement, division and death in 3D movies of developing embryos expressing histone-GFP fusions in each cell, and thus automatically determine the lineage for each cell and hence its identity. Simultaneously, we will detect a second-color reporter expressed under the control of a candidate transcriptional regulatory region. By mapping the resulting temporal and spatial expression patterns onto the embryonic lineage, we will identify the cells expressing the reporter. These methods will require the creation of new techniques and the modification of existing one to enable the generation of new worm strains, live-cell fluorescence imaging and pattern recognition in images. We will assess the accuracy of the method through multiple quality control tests and begin to develop a pipeline to allow systematic application of the methods to large numbers of genes. The completed system will be useful for a wide variety of functional genomics applications and with further adaptation could provide an avenue to comprehensive analysis of gene expression in C. elegans. Knowledge of gene expression patterns in C. elegans would not only provide insights into the role of these genes in development, but would suggest roles of homologous genes in health and disease in other animals, including humans.