As a single cell divides and gives rise to multiple cell types in the adult, the developmental process is directed by intricate spatio-temporal gene expression patterns, which are controlled by transcriptional networks. This proposal uses the transcriptional network that specifies the anterior-posterior axis in Drosophila embryos as a model system to explore how regulatory circuits are encoded in the genome and how they change between species. Gene expression in animals is controlled by the interaction between transcription factors (TFs), cis-regulatory elements (CREs, also called enhancers), core promoters, untranslated regions (UTRs), regulatory RNAs, silencers, insulators, and chromatin structure. It is thought that core promoter elements and chromatin structure provide general competence for transcription at transcription start sites, while more distant CREs up-regulate expression of genes under specific conditions. We lack a complete framework that allows us to measure and understand how changes in different components of the network combine to maintain or alter output gene expression levels between individuals or species. The regulatory network that controls Drosophila anterior-posterior axis formation is highly conserved, yet using our sensitive imaging techniques, we observe many quantitative changes in the timing and spatial location of gene expression patterns between these different species of Drosophila. Using our precise measurements of gene expression patterns in 5 closely related Drosophila species, computational methods, and complementary transgenic animal experiments, we will determine the contributions of different components of the regulatory network (e.g., CREs, promoters) to the expression divergence we observe between species. Success in this endeavor will lead to a better understanding of how sequence divergence perturbs some aspects of early development while conserving others and will inform our understanding of the structure-function relationship of CREs, promoters, and other regulatory elements. The PI for this project, Dr. Wunderlich, aims to combine her graduate training in computational biology with her postdoctoral training in experimental Drosophila systems biology to lay the foundation for an independent research lab that will use a combination of experimental and computational techniques to study how the gene regulatory networks that direct development are encoded in the genome. Here I propose to complete a data set and initial computational analyses during the remainder of my postdoctoral training that will foster a large set of subsequent studies in my own lab. The environment provided by the Harvard University Systems Biology Department is uniquely suitable for this training, as it is comprised of faculty members, postdoctoral fellows, students and other researchers with a variety of backgrounds from biology to mathematics to physics. This interdisciplinary environment, with a focus on the application of quantitative methods to biology, is well-matched to my interests and provides a supportive environment for undertaking the work proposed here. The department and university has a number of faculty members with interests that overlap with mine and also provides the animal husbandry, microscopy, computational and administrative resources that will enable this project.

Public Health Relevance

During development, a fertilized egg divides many times to create the cells that will form the adult animal. To create different cell types, e.g. neurons and muscle cells, each cell expresses different combinations of genes at particular levels during different phases of development, and errors in this program can cause defects in development. This proposal aims to understand how information about this developmental gene expression program is encoded in the genome and to understand how changes in the genome sequence affect the patterns of gene expression.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Career Transition Award (K99)
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Pediatrics Subcommittee (CHHD)
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Coulombe, James N
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Harvard University
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Wunderlich, Zeba; Bragdon, Meghan D; DePace, Angela H (2014) Comparing mRNA levels using in situ hybridization of a target gene and co-stain. Methods 68:233-41